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Gripping apparatus and method of producing a gripping apparatus
Gripping apparatus and method of producing a gripping apparatus

Song, S., Sitti, M., Drotlef, D., Majidi, C.

Google Patents, Febuary 2020, US Patent App. 16/610,209 (patent)

Abstract
The present invention relates to a gripping apparatus comprising a membrane; a flexible housing; with said membrane being fixedly connected to a periphery of the housing. The invention further relates to a method of producing a gripping apparatus.

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[BibTex]

[BibTex]


Method of actuating a shape changeable member, shape changeable member and actuating system
Method of actuating a shape changeable member, shape changeable member and actuating system

Hu, W., Lum, G. Z., Mastrangeli, M., Sitti, M.

Google Patents, January 2020, US Patent App. 16/477,593 (patent)

Abstract
The present invention relates to a method of actuating a shape changeable member of actuatable material. The invention further relates to a shape changeable member and to a system comprising such a shape changeable member and a magnetic field apparatus.

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[BibTex]


Thermal Effects on the Crystallization Kinetics, and Interfacial Adhesion of Single-Crystal Phase-Change Gallium
Thermal Effects on the Crystallization Kinetics, and Interfacial Adhesion of Single-Crystal Phase-Change Gallium

Yunusa, M., Lahlou, A., Sitti, M.

Advanced Materials, Wiley Online Library, 2020 (article)

Abstract
Although substrates play an important role upon crystallization of supercooled liquids, the influences of surface temperature and thermal property have remained elusive. Here, the crystallization of supercooled phase‐change gallium (Ga) on substrates with different thermal conductivity is studied. The effect of interfacial temperature on the crystallization kinetics, which dictates thermo‐mechanical stresses between the substrate and the crystallized Ga, is investigated. At an elevated surface temperature, close to the melting point of Ga, an extended single‐crystal growth of Ga on dielectric substrates due to layering effect and annealing is realized without the application of external fields. Adhesive strength at the interfaces depends on the thermal conductivity and initial surface temperature of the substrates. This insight can be applicable to other liquid metals for industrial applications, and sheds more light on phase‐change memory crystallization.

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[BibTex]


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Nanoerythrosome-functionalized biohybrid microswimmers

Nicole, Oncay, Yunus, Birgul, Metin Sitti

2020 (article) Accepted

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[BibTex]

[BibTex]


Learning Unsupervised Hierarchical Part Decomposition of 3D Objects from a Single RGB Image
Learning Unsupervised Hierarchical Part Decomposition of 3D Objects from a Single RGB Image

Paschalidou, D., Gool, L., Geiger, A.

In Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), IEEE International Conference on Computer Vision and Pattern Recognition (CVPR) 2020, 2020 (inproceedings)

Abstract
Humans perceive the 3D world as a set of distinct objects that are characterized by various low-level (geometry, reflectance) and high-level (connectivity, adjacency, symmetry) properties. Recent methods based on convolutional neural networks (CNNs) demonstrated impressive progress in 3D reconstruction, even when using a single 2D image as input. However, the majority of these methods focuses on recovering the local 3D geometry of an object without considering its part-based decomposition or relations between parts. We address this challenging problem by proposing a novel formulation that allows to jointly recover the geometry of a 3D object as a set of primitives as well as their latent hierarchical structure without part-level supervision. Our model recovers the higher level structural decomposition of various objects in the form of a binary tree of primitives, where simple parts are represented with fewer primitives and more complex parts are modeled with more components. Our experiments on the ShapeNet and D-FAUST datasets demonstrate that considering the organization of parts indeed facilitates reasoning about 3D geometry.

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pdf suppmat Video Project Page [BibTex]

pdf suppmat Video Project Page [BibTex]


Injectable Nanoelectrodes Enable Wireless Deep Brain Stimulation of Native Tissue in Freely Moving Mice
Injectable Nanoelectrodes Enable Wireless Deep Brain Stimulation of Native Tissue in Freely Moving Mice

Kozielski, K. L., Jahanshahi, A., Gilbert, H. B., Yu, Y., Erin, O., Francisco, D., Alosaimi, F., Temel, Y., Sitti, M.

bioRxiv, Cold Spring Harbor Laboratory, 2020 (article)

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[BibTex]

[BibTex]


Self-supervised motion deblurring
Self-supervised motion deblurring

Liu, P., Janai, J., Pollefeys, M., Sattler, T., Geiger, A.

IEEE Robotics and Automation Letters, 2020 (article)

Abstract
Motion blurry images challenge many computer vision algorithms, e.g., feature detection, motion estimation, or object recognition. Deep convolutional neural networks are state-of-the-art for image deblurring. However, obtaining training data with corresponding sharp and blurry image pairs can be difficult. In this paper, we present a differentiable reblur model for self-supervised motion deblurring, which enables the network to learn from real-world blurry image sequences without relying on sharp images for supervision. Our key insight is that motion cues obtained from consecutive images yield sufficient information to inform the deblurring task. We therefore formulate deblurring as an inverse rendering problem, taking into account the physical image formation process: we first predict two deblurred images from which we estimate the corresponding optical flow. Using these predictions, we re-render the blurred images and minimize the difference with respect to the original blurry inputs. We use both synthetic and real dataset for experimental evaluations. Our experiments demonstrate that self-supervised single image deblurring is really feasible and leads to visually compelling results.

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pdf Project Page Blog [BibTex]

pdf Project Page Blog [BibTex]


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Statistical reprogramming of macroscopic self-assembly with dynamic boundaries

Utku, , Massimo, , Zoey, , Sitti,

2020 (article) Accepted

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[BibTex]

[BibTex]


Controlling two-dimensional collective formation and cooperative behavior of magnetic microrobot swarms
Controlling two-dimensional collective formation and cooperative behavior of magnetic microrobot swarms

Dong, X., Sitti, M.

The International Journal of Robotics Research, 2020 (article)

Abstract
Magnetically actuated mobile microrobots can access distant, enclosed, and small spaces, such as inside microfluidic channels and the human body, making them appealing for minimally invasive tasks. Despite their simplicity when scaling down, creating collective microrobots that can work closely and cooperatively, as well as reconfigure their formations for different tasks, would significantly enhance their capabilities such as manipulation of objects. However, a challenge of realizing such cooperative magnetic microrobots is to program and reconfigure their formations and collective motions with under-actuated control signals. This article presents a method of controlling 2D static and time-varying formations among collective self-repelling ferromagnetic microrobots (100 μm to 350 μm in diameter, up to 260 in number) by spatially and temporally programming an external magnetic potential energy distribution at the air–water interface or on solid surfaces. A general design method is introduced to program external magnetic potential energy using ferromagnets. A predictive model of the collective system is also presented to predict the formation and guide the design procedure. With the proposed method, versatile complex static formations are experimentally demonstrated and the programmability and scaling effects of formations are analyzed. We also demonstrate the collective mobility of these magnetic microrobots by controlling them to exhibit bio-inspired collective behaviors such as aggregation, directional motion with arbitrary swarm headings, and rotational swarming motion. Finally, the functions of the produced microrobotic swarm are demonstrated by controlling them to navigate through cluttered environments and complete reconfigurable cooperative manipulation tasks.

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DOI [BibTex]


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Analytical classical density functionals from an equation learning network

Lin, S., Martius, G., Oettel, M.

The Journal of Chemical Physics, 152(2):021102, 2020, arXiv preprint \url{https://arxiv.org/abs/1910.12752} (article)

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Preprint_PDF DOI [BibTex]

Preprint_PDF DOI [BibTex]


Characterization and Thermal Management of a DC Motor-Driven Resonant Actuator for Miniature Mobile Robots with Oscillating Limbs
Characterization and Thermal Management of a DC Motor-Driven Resonant Actuator for Miniature Mobile Robots with Oscillating Limbs

Colmenares, D., Kania, R., Liu, M., Sitti, M.

arXiv preprint arXiv:2002.00798, 2020 (article)

Abstract
In this paper, we characterize the performance of and develop thermal management solutions for a DC motor-driven resonant actuator developed for flapping wing micro air vehicles. The actuator, a DC micro-gearmotor connected in parallel with a torsional spring, drives reciprocal wing motion. Compared to the gearmotor alone, this design increased torque and power density by 161.1% and 666.8%, respectively, while decreasing the drawn current by 25.8%. Characterization of the actuator, isolated from nonlinear aerodynamic loading, results in standard metrics directly comparable to other actuators. The micro-motor, selected for low weight considerations, operates at high power for limited duration due to thermal effects. To predict system performance, a lumped parameter thermal circuit model was developed. Critical model parameters for this micro-motor, two orders of magnitude smaller than those previously characterized, were identified experimentally. This included the effects of variable winding resistance, bushing friction, speed-dependent forced convection, and the addition of a heatsink. The model was then used to determine a safe operation envelope for the vehicle and to design a weight-optimal heatsink. This actuator design and thermal modeling approach could be applied more generally to improve the performance of any miniature mobile robot or device with motor-driven oscillating limbs or loads.

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[BibTex]


Magnetic Resonance Imaging System--Driven Medical Robotics
Magnetic Resonance Imaging System–Driven Medical Robotics

Erin, O., Boyvat, M., Tiryaki, M. E., Phelan, M., Sitti, M.

Advanced Intelligent Systems, 2, Wiley Online Library, 2020 (article)

Abstract
Magnetic resonance imaging (MRI) system–driven medical robotics is an emerging field that aims to use clinical MRI systems not only for medical imaging but also for actuation, localization, and control of medical robots. Submillimeter scale resolution of MR images for soft tissues combined with the electromagnetic gradient coil–based magnetic actuation available inside MR scanners can enable theranostic applications of medical robots for precise image‐guided minimally invasive interventions. MRI‐driven robotics typically does not introduce new MRI instrumentation for actuation but instead focuses on converting already available instrumentation for robotic purposes. To use the advantages of this technology, various medical devices such as untethered mobile magnetic robots and tethered active catheters have been designed to be powered magnetically inside MRI systems. Herein, the state‐of‐the‐art progress, challenges, and future directions of MRI‐driven medical robotic systems are reviewed.

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[BibTex]

[BibTex]


Pros and Cons: Magnetic versus Optical Microrobots
Pros and Cons: Magnetic versus Optical Microrobots

Sitti, M., Wiersma, D. S.

Advanced Materials, Wiley Online Library, 2020 (article)

Abstract
Mobile microrobotics has emerged as a new robotics field within the last decade to create untethered tiny robots that can access and operate in unprecedented, dangerous, or hard‐to‐reach small spaces noninvasively toward disruptive medical, biotechnology, desktop manufacturing, environmental remediation, and other potential applications. Magnetic and optical actuation methods are the most widely used actuation methods in mobile microrobotics currently, in addition to acoustic and biological (cell‐driven) actuation approaches. The pros and cons of these actuation methods are reported here, depending on the given context. They can both enable long‐range, fast, and precise actuation of single or a large number of microrobots in diverse environments. Magnetic actuation has unique potential for medical applications of microrobots inside nontransparent tissues at high penetration depths, while optical actuation is suitable for more biotechnology, lab‐/organ‐on‐a‐chip, and desktop manufacturing types of applications with much less surface penetration depth requirements or with transparent environments. Combining both methods in new robot designs can have a strong potential of combining the pros of both methods. There is still much progress needed in both actuation methods to realize the potential disruptive applications of mobile microrobots in real‐world conditions.

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[BibTex]

[BibTex]


Towards Unsupervised Learning of Generative Models for 3D Controllable Image Synthesis
Towards Unsupervised Learning of Generative Models for 3D Controllable Image Synthesis

Liao, Y., Schwarz, K., Mescheder, L., Geiger, A.

In Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), IEEE International Conference on Computer Vision and Pattern Recognition (CVPR) 2020, 2020 (inproceedings)

Abstract
In recent years, Generative Adversarial Networks have achieved impressive results in photorealistic image synthesis. This progress nurtures hopes that one day the classical rendering pipeline can be replaced by efficient models that are learned directly from images. However, current image synthesis models operate in the 2D domain where disentangling 3D properties such as camera viewpoint or object pose is challenging. Furthermore, they lack an interpretable and controllable representation. Our key hypothesis is that the image generation process should be modeled in 3D space as the physical world surrounding us is intrinsically three-dimensional. We define the new task of 3D controllable image synthesis and propose an approach for solving it by reasoning both in 3D space and in the 2D image domain. We demonstrate that our model is able to disentangle latent 3D factors of simple multi-object scenes in an unsupervised fashion from raw images. Compared to pure 2D baselines, it allows for synthesizing scenes that are consistent wrt. changes in viewpoint or object pose. We further evaluate various 3D representations in terms of their usefulness for this challenging task.

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pdf suppmat Video Project Page [BibTex]

pdf suppmat Video Project Page [BibTex]


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Selectively Controlled Magnetic Microrobots with Opposing Helices

Joshua, , Wendong, , Panayiota, , Eric, , Sitti,

2020 (article) Accepted

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[BibTex]

[BibTex]


Acoustically powered surface-slipping mobile microrobots
Acoustically powered surface-slipping mobile microrobots

Aghakhani, A., Yasa, O., Wrede, P., Sitti, M.

Proceedings of the National Academy of Sciences, 117, National Acad Sciences, 2020 (article)

Abstract
Untethered synthetic microrobots have significant potential to revolutionize minimally invasive medical interventions in the future. However, their relatively slow speed and low controllability near surfaces typically are some of the barriers standing in the way of their medical applications. Here, we introduce acoustically powered microrobots with a fast, unidirectional surface-slipping locomotion on both flat and curved surfaces. The proposed three-dimensionally printed, bullet-shaped microrobot contains a spherical air bubble trapped inside its internal body cavity, where the bubble is resonated using acoustic waves. The net fluidic flow due to the bubble oscillation orients the microrobot's axisymmetric axis perpendicular to the wall and then propels it laterally at very high speeds (up to 90 body lengths per second with a body length of 25 µm) while inducing an attractive force toward the wall. To achieve unidirectional locomotion, a small fin is added to the microrobot’s cylindrical body surface, which biases the propulsion direction. For motion direction control, the microrobots are coated anisotropically with a soft magnetic nanofilm layer, allowing steering under a uniform magnetic field. Finally, surface locomotion capability of the microrobots is demonstrated inside a three-dimensional circular cross-sectional microchannel under acoustic actuation. Overall, the combination of acoustic powering and magnetic steering can be effectively utilized to actuate and navigate these microrobots in confined and hard-to-reach body location areas in a minimally invasive fashion.

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[BibTex]

[BibTex]


Bio-inspired Flexible Twisting Wings Increase Lift and Efficiency of a Flapping Wing Micro Air Vehicle
Bio-inspired Flexible Twisting Wings Increase Lift and Efficiency of a Flapping Wing Micro Air Vehicle

Colmenares, D., Kania, R., Zhang, W., Sitti, M.

arXiv preprint arXiv:2001.11586, 2020 (article)

Abstract
We investigate the effect of wing twist flexibility on lift and efficiency of a flapping-wing micro air vehicle capable of liftoff. Wings used previously were chosen to be fully rigid due to modeling and fabrication constraints. However, biological wings are highly flexible and other micro air vehicles have successfully utilized flexible wing structures for specialized tasks. The goal of our study is to determine if dynamic twisting of flexible wings can increase overall aerodynamic lift and efficiency. A flexible twisting wing design was found to increase aerodynamic efficiency by 41.3%, translational lift production by 35.3%, and the effective lift coefficient by 63.7% compared to the rigid-wing design. These results exceed the predictions of quasi-steady blade element models, indicating the need for unsteady computational fluid dynamics simulations of twisted flapping wings.

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[BibTex]

[BibTex]


Cohesive self-organization of mobile microrobotic swarms
Cohesive self-organization of mobile microrobotic swarms

Yigit, B., Alapan, Y., Sitti, M.

arXiv preprint arXiv:1907.05856, 2020 (article)

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[BibTex]

[BibTex]


Exploring Data Aggregation in Policy Learning for Vision-based Urban Autonomous Driving
Exploring Data Aggregation in Policy Learning for Vision-based Urban Autonomous Driving

Prakash, A., Behl, A., Ohn-Bar, E., Chitta, K., Geiger, A.

In Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), IEEE International Conference on Computer Vision and Pattern Recognition (CVPR) 2020, 2020 (inproceedings)

Abstract
Data aggregation techniques can significantly improve vision-based policy learning within a training environment, e.g., learning to drive in a specific simulation condition. However, as on-policy data is sequentially sampled and added in an iterative manner, the policy can specialize and overfit to the training conditions. For real-world applications, it is useful for the learned policy to generalize to novel scenarios that differ from the training conditions. To improve policy learning while maintaining robustness when training end-to-end driving policies, we perform an extensive analysis of data aggregation techniques in the CARLA environment. We demonstrate how the majority of them have poor generalization performance, and develop a novel approach with empirically better generalization performance compared to existing techniques. Our two key ideas are (1) to sample critical states from the collected on-policy data based on the utility they provide to the learned policy in terms of driving behavior, and (2) to incorporate a replay buffer which progressively focuses on the high uncertainty regions of the policy's state distribution. We evaluate the proposed approach on the CARLA NoCrash benchmark, focusing on the most challenging driving scenarios with dense pedestrian and vehicle traffic. Our approach improves driving success rate by 16% over state-of-the-art, achieving 87% of the expert performance while also reducing the collision rate by an order of magnitude without the use of any additional modality, auxiliary tasks, architectural modifications or reward from the environment.

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pdf suppmat Video Project Page [BibTex]

pdf suppmat Video Project Page [BibTex]


Bioinspired underwater locomotion of light-driven liquid crystal gels
Bioinspired underwater locomotion of light-driven liquid crystal gels

Shahsavan, H., Aghakhani, A., Zeng, H., Guo, Y., Davidson, Z. S., Priimagi, A., Sitti, M.

Proceedings of the National Academy of Sciences, National Acad Sciences, 2020 (article)

Abstract
Untethered dynamic shape programming and control of soft materials have significant applications in technologies such as soft robots, medical devices, organ-on-a-chip, and optical devices. Here, we present a solution to remotely actuate and move soft materials underwater in a fast, efficient, and controlled manner using photoresponsive liquid crystal gels (LCGs). LCG constructs with engineered molecular alignment show a low and sharp phase-transition temperature and experience considerable density reduction by light exposure, thereby allowing rapid and reversible shape changes. We demonstrate different modes of underwater locomotion, such as crawling, walking, jumping, and swimming, by localized and time-varying illumination of LCGs. The diverse locomotion modes of smart LCGs can provide a new toolbox for designing efficient light-fueled soft robots in fluid-immersed media.

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[BibTex]

[BibTex]


Differentiation of blackbox combinatorial solvers
Differentiation of blackbox combinatorial solvers

Vlastelica, M., Paulus, A., Musil, V., Martius, G., Rolı́nek, M.

In International Conference on Learning Representations, ICLR’20, 2020 (incollection)

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link (url) [BibTex]

link (url) [BibTex]


Learning Situational Driving
Learning Situational Driving

Ohn-Bar, E., Prakash, A., Behl, A., Chitta, K., Geiger, A.

In Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), IEEE International Conference on Computer Vision and Pattern Recognition (CVPR) 2020, 2020 (inproceedings)

Abstract
Human drivers have a remarkable ability to drive in diverse visual conditions and situations, e.g., from maneuvering in rainy, limited visibility conditions with no lane markings to turning in a busy intersection while yielding to pedestrians. In contrast, we find that state-of-the-art sensorimotor driving models struggle when encountering diverse settings with varying relationships between observation and action. To generalize when making decisions across diverse conditions, humans leverage multiple types of situation-specific reasoning and learning strategies. Motivated by this observation, we develop a framework for learning a situational driving policy that effectively captures reasoning under varying types of scenarios. Our key idea is to learn a mixture model with a set of policies that can capture multiple driving modes. We first optimize the mixture model through behavior cloning, and show it to result in significant gains in terms of driving performance in diverse conditions. We then refine the model by directly optimizing for the driving task itself, i.e., supervised with the navigation task reward. Our method is more scalable than methods assuming access to privileged information, e.g., perception labels, as it only assumes demonstration and reward-based supervision. We achieve over 98% success rate on the CARLA driving benchmark as well as state-of-the-art performance on a newly introduced generalization benchmark.

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pdf suppmat Video Project Page [BibTex]

pdf suppmat Video Project Page [BibTex]


On Joint Estimation of Pose, Geometry and svBRDF from a Handheld Scanner
On Joint Estimation of Pose, Geometry and svBRDF from a Handheld Scanner

Schmitt, C., Donne, S., Riegler, G., Koltun, V., Geiger, A.

In Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), IEEE International Conference on Computer Vision and Pattern Recognition (CVPR) 2020, 2020 (inproceedings)

Abstract
We propose a novel formulation for joint recovery of camera pose, object geometry and spatially-varying BRDF. The input to our approach is a sequence of RGB-D images captured by a mobile, hand-held scanner that actively illuminates the scene with point light sources. Compared to previous works that jointly estimate geometry and materials from a hand-held scanner, we formulate this problem using a single objective function that can be minimized using off-the-shelf gradient-based solvers. By integrating material clustering as a differentiable operation into the optimization process, we avoid pre-processing heuristics and demonstrate that our model is able to determine the correct number of specular materials independently. We provide a study on the importance of each component in our formulation and on the requirements of the initial geometry. We show that optimizing over the poses is crucial for accurately recovering fine details and that our approach naturally results in a semantically meaningful material segmentation.

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pdf Project Page [BibTex]

pdf Project Page [BibTex]


Additive manufacturing of cellulose-based materials with continuous, multidirectional stiffness gradients
Additive manufacturing of cellulose-based materials with continuous, multidirectional stiffness gradients

Giachini, P., Gupta, S., Wang, W., Wood, D., Yunusa, M., Baharlou, E., Sitti, M., Menges, A.

Science Advances, 6, American Association for the Advancement of Science, 2020 (article)

Abstract
Functionally graded materials (FGMs) enable applications in fields such as biomedicine and architecture, but their fabrication suffers from shortcomings in gradient continuity, interfacial bonding, and directional freedom. In addition, most commercial design software fail to incorporate property gradient data, hindering explorations of the design space of FGMs. Here, we leveraged a combined approach of materials engineering and digital processing to enable extrusion-based multimaterial additive manufacturing of cellulose-based tunable viscoelastic materials with continuous, high-contrast, and multidirectional stiffness gradients. A method to engineer sets of cellulose-based materials with similar compositions, yet distinct mechanical and rheological properties, was established. In parallel, a digital workflow was developed to embed gradient information into design models with integrated fabrication path planning. The payoff of integrating these physical and digital tools is the ability to achieve the same stiffness gradient in multiple ways, opening design possibilities previously limited by the rigid coupling of material and geometry.

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[BibTex]

[BibTex]


Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervision
Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervision

Niemeyer, M., Mescheder, L., Oechsle, M., Geiger, A.

In Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), IEEE International Conference on Computer Vision and Pattern Recognition (CVPR) 2020, 2020 (inproceedings)

Abstract
Learning-based 3D reconstruction methods have shown impressive results. However, most methods require 3D supervision which is often hard to obtain for real-world datasets. Recently, several works have proposed differentiable rendering techniques to train reconstruction models from RGB images. Unfortunately, these approaches are currently restricted to voxel- and mesh-based representations, suffering from discretization or low resolution. In this work, we propose a differentiable rendering formulation for implicit shape and texture representations. Implicit representations have recently gained popularity as they represent shape and texture continuously. Our key insight is that depth gradients can be derived analytically using the concept of implicit differentiation. This allows us to learn implicit shape and texture representations directly from RGB images. We experimentally show that our single-view reconstructions rival those learned with full 3D supervision. Moreover, we find that our method can be used for multi-view 3D reconstruction, directly resulting in watertight meshes.

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pdf suppmat Video Project Page [BibTex]

pdf suppmat Video Project Page [BibTex]

2014


Series of Multilinked Caterpillar Track-type Climbing Robots
Series of Multilinked Caterpillar Track-type Climbing Robots

Lee, G., Kim, H., Seo, K., Kim, J., Sitti, M., Seo, T.

Journal of Field Robotics, November 2014 (article)

Abstract
Climbing robots have been widely applied in many industries involving hard to access, dangerous, or hazardous environments to replace human workers. Climbing speed, payload capacity, the ability to overcome obstacles, and wall-to-wall transitioning are significant characteristics of climbing robots. Here, multilinked track wheel-type climbing robots are proposed to enhance these characteristics. The robots have been developed for five years in collaboration with three universities: Seoul National University, Carnegie Mellon University, and Yeungnam University. Four types of robots are presented for different applications with different surface attachment methods and mechanisms: MultiTank for indoor sites, Flexible caterpillar robot (FCR) and Combot for heavy industrial sites, and MultiTrack for high-rise buildings. The method of surface attachment is different for each robot and application, and the characteristics of the joints between links are designed as active or passive according to the requirement of a given robot. Conceptual design, practical design, and control issues of such climbing robot types are reported, and a proper choice of the attachment methods and joint type is essential for the successful multilink track wheel-type climbing robot for different surface materials, robot size, and computational costs.

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DOI [BibTex]

2014


DOI [BibTex]


Omnidirectional 3D Reconstruction in Augmented Manhattan Worlds
Omnidirectional 3D Reconstruction in Augmented Manhattan Worlds

Schoenbein, M., Geiger, A.

International Conference on Intelligent Robots and Systems, pages: 716 - 723, IEEE, Chicago, IL, USA, IEEE/RSJ International Conference on Intelligent Robots and System, October 2014 (conference)

Abstract
This paper proposes a method for high-quality omnidirectional 3D reconstruction of augmented Manhattan worlds from catadioptric stereo video sequences. In contrast to existing works we do not rely on constructing virtual perspective views, but instead propose to optimize depth jointly in a unified omnidirectional space. Furthermore, we show that plane-based prior models can be applied even though planes in 3D do not project to planes in the omnidirectional domain. Towards this goal, we propose an omnidirectional slanted-plane Markov random field model which relies on plane hypotheses extracted using a novel voting scheme for 3D planes in omnidirectional space. To quantitatively evaluate our method we introduce a dataset which we have captured using our autonomous driving platform AnnieWAY which we equipped with two horizontally aligned catadioptric cameras and a Velodyne HDL-64E laser scanner for precise ground truth depth measurements. As evidenced by our experiments, the proposed method clearly benefits from the unified view and significantly outperforms existing stereo matching techniques both quantitatively and qualitatively. Furthermore, our method is able to reduce noise and the obtained depth maps can be represented very compactly by a small number of image segments and plane parameters.

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pdf DOI [BibTex]

pdf DOI [BibTex]


Geckogripper: A soft, inflatable robotic gripper using gecko-inspired elastomer micro-fiber adhesives
Geckogripper: A soft, inflatable robotic gripper using gecko-inspired elastomer micro-fiber adhesives

Song, S., Majidi, C., Sitti, M.

In Intelligent Robots and Systems (IROS 2014), 2014 IEEE/RSJ International Conference on, pages: 4624-4629, September 2014 (inproceedings)

Abstract
This paper proposes GeckoGripper, a novel soft, inflatable gripper based on the controllable adhesion mechanism of gecko-inspired micro-fiber adhesives, to pick-and-place complex and fragile non-planar or planar parts serially or in parallel. Unlike previous fibrillar structures that use peel angle to control the manipulation of parts, we developed an elastomer micro-fiber adhesive that is fabricated on a soft, flexible membrane, increasing the adaptability to non-planar three-dimensional (3D) geometries and controllability in adhesion. The adhesive switching ratio (the ratio between the maximum and minimum adhesive forces) of the developed gripper was measured to be around 204, which is superior to previous works based on peel angle-based release control methods. Adhesion control mechanism based on the stretch of the membrane and superior adaptability to non-planar 3D geometries enable the micro-fibers to pick-and-place various 3D parts as shown in demonstrations.

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DOI [BibTex]

DOI [BibTex]


Segmented molecular design of self-healing proteinaceous materials.
Segmented molecular design of self-healing proteinaceous materials.

Sariola, V., Pena-Francesch, A., Jung, H., Çetinkaya, M., Pacheco, C., Sitti, M., Demirel, M. C.

Scientific reports, 5, pages: 13482-13482, Nature Publishing Group, July 2014 (article)

Abstract
Hierarchical assembly of self-healing adhesive proteins creates strong and robust structural and interfacial materials, but understanding of the molecular design and structure–property relationships of structural proteins remains unclear. Elucidating this relationship would allow rational design of next generation genetically engineered self-healing structural proteins. Here we report a general self-healing and -assembly strategy based on a multiphase recombinant protein based material. Segmented structure of the protein shows soft glycine- and tyrosine-rich segments with self-healing capability and hard beta-sheet segments. The soft segments are strongly plasticized by water, lowering the self-healing temperature close to body temperature. The hard segments self-assemble into nanoconfined domains to reinforce the material. The healing strength scales sublinearly with contact time, which associates with diffusion and wetting of autohesion. The finding suggests that recombinant structural proteins from heterologous expression have potential as strong and repairable engineering materials.

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DOI [BibTex]

DOI [BibTex]


Bio-Hybrid Cell-Based Actuators for Microsystems
Bio-Hybrid Cell-Based Actuators for Microsystems

Carlsen, R. W., Sitti, M.

Small, 10(19):3831-3851, June 2014 (article)

Abstract
As we move towards the miniaturization of devices to perform tasks at the nano and microscale, it has become increasingly important to develop new methods for actuation, sensing, and control. Over the past decade, bio-hybrid methods have been investigated as a promising new approach to overcome the challenges of scaling down robotic and other functional devices. These methods integrate biological cells with artificial components and therefore, can take advantage of the intrinsic actuation and sensing functionalities of biological cells. Here, the recent advancements in bio-hybrid actuation are reviewed, and the challenges associated with the design, fabrication, and control of bio-hybrid microsystems are discussed. As a case study, focus is put on the development of bacteria-driven microswimmers, which has been investigated as a targeted drug delivery carrier. Finally, a future outlook for the development of these systems is provided. The continued integration of biological and artificial components is envisioned to enable the performance of tasks at a smaller and smaller scale in the future, leading to the parallel and distributed operation of functional systems at the microscale.

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DOI [BibTex]

DOI [BibTex]


Simultaneous Underwater Visibility Assessment, Enhancement and Improved Stereo
Simultaneous Underwater Visibility Assessment, Enhancement and Improved Stereo

Roser, M., Dunbabin, M., Geiger, A.

IEEE International Conference on Robotics and Automation, pages: 3840 - 3847 , Hong Kong, China, IEEE International Conference on Robotics and Automation, June 2014 (conference)

Abstract
Vision-based underwater navigation and obstacle avoidance demands robust computer vision algorithms, particularly for operation in turbid water with reduced visibility. This paper describes a novel method for the simultaneous underwater image quality assessment, visibility enhancement and disparity computation to increase stereo range resolution under dynamic, natural lighting and turbid conditions. The technique estimates the visibility properties from a sparse 3D map of the original degraded image using a physical underwater light attenuation model. Firstly, an iterated distance-adaptive image contrast enhancement enables a dense disparity computation and visibility estimation. Secondly, using a light attenuation model for ocean water, a color corrected stereo underwater image is obtained along with a visibility distance estimate. Experimental results in shallow, naturally lit, high-turbidity coastal environments show the proposed technique improves range estimation over the original images as well as image quality and color for habitat classification. Furthermore, the recursiveness and robustness of the technique allows real-time implementation onboard an Autonomous Underwater Vehicles for improved navigation and obstacle avoidance performance.

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pdf DOI [BibTex]

pdf DOI [BibTex]


Calibrating and Centering Quasi-Central Catadioptric Cameras
Calibrating and Centering Quasi-Central Catadioptric Cameras

Schoenbein, M., Strauss, T., Geiger, A.

IEEE International Conference on Robotics and Automation, pages: 4443 - 4450, Hong Kong, China, IEEE International Conference on Robotics and Automation, June 2014 (conference)

Abstract
Non-central catadioptric models are able to cope with irregular camera setups and inaccuracies in the manufacturing process but are computationally demanding and thus not suitable for robotic applications. On the other hand, calibrating a quasi-central (almost central) system with a central model introduces errors due to a wrong relationship between the viewing ray orientations and the pixels on the image sensor. In this paper, we propose a central approximation to quasi-central catadioptric camera systems that is both accurate and efficient. We observe that the distance to points in 3D is typically large compared to deviations from the single viewpoint. Thus, we first calibrate the system using a state-of-the-art non-central camera model. Next, we show that by remapping the observations we are able to match the orientation of the viewing rays of a much simpler single viewpoint model with the true ray orientations. While our approximation is general and applicable to all quasi-central camera systems, we focus on one of the most common cases in practice: hypercatadioptric cameras. We compare our model to a variety of baselines in synthetic and real localization and motion estimation experiments. We show that by using the proposed model we are able to achieve near non-central accuracy while obtaining speed-ups of more than three orders of magnitude compared to state-of-the-art non-central models.

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pdf DOI [BibTex]

pdf DOI [BibTex]


3D Traffic Scene Understanding from Movable Platforms
3D Traffic Scene Understanding from Movable Platforms

Geiger, A., Lauer, M., Wojek, C., Stiller, C., Urtasun, R.

IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 36(5):1012-1025, published, IEEE, Los Alamitos, CA, May 2014 (article)

Abstract
In this paper, we present a novel probabilistic generative model for multi-object traffic scene understanding from movable platforms which reasons jointly about the 3D scene layout as well as the location and orientation of objects in the scene. In particular, the scene topology, geometry and traffic activities are inferred from short video sequences. Inspired by the impressive driving capabilities of humans, our model does not rely on GPS, lidar or map knowledge. Instead, it takes advantage of a diverse set of visual cues in the form of vehicle tracklets, vanishing points, semantic scene labels, scene flow and occupancy grids. For each of these cues we propose likelihood functions that are integrated into a probabilistic generative model. We learn all model parameters from training data using contrastive divergence. Experiments conducted on videos of 113 representative intersections show that our approach successfully infers the correct layout in a variety of very challenging scenarios. To evaluate the importance of each feature cue, experiments using different feature combinations are conducted. Furthermore, we show how by employing context derived from the proposed method we are able to improve over the state-of-the-art in terms of object detection and object orientation estimation in challenging and cluttered urban environments.

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pdf link (url) [BibTex]

pdf link (url) [BibTex]


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Fibrillar structures to reduce viscous drag on aerodynamic and hydrodynamic wall surfaces

Castillo, L., Aksak, B., Sitti, M.

March 2014, US Patent App. 14/774,767 (misc)

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[BibTex]

[BibTex]


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The design of microfibers with mushroom-shaped tips for optimal adhesion

Sitti, M., Aksak, B.

February 2014, US Patent App. 14/766,561 (misc)

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[BibTex]

[BibTex]


Continuously distributed magnetization profile for millimeter-scale elastomeric undulatory swimming
Continuously distributed magnetization profile for millimeter-scale elastomeric undulatory swimming

Diller, E., Zhuang, J., Zhan Lum, G., Edwards, M. R., Sitti, M.

Applied Physics Letters, 104(17):174101, AIP, 2014 (article)

Abstract
We have developed a millimeter-scale magnetically driven swimming robot for untethered motion at mid to low Reynolds numbers. The robot is propelled by continuous undulatory deformation, which is enabled by the distributed magnetization profile of a flexible sheet. We demonstrate control of a prototype device and measure deformation and speed as a function of magnetic field strength and frequency. Experimental results are compared with simple magnetoelastic and fluid propulsion models. The presented mechanism provides an efficient remote actuation method at the millimeter scale that may be suitable for further scaling down in size for microrobotics applications in biotechnology and healthcare

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Biopsy using a Magnetic Capsule Endoscope Carrying, Releasing and Retrieving Untethered Micro-Grippers

Yim, S., Gultepe, E., Gracias, D. H., Sitti, M.

IEEE Trans. on Biomedical Engineering, 61(2):513-521, IEEE, 2014 (article)

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Project Page [BibTex]

Project Page [BibTex]


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Investigation of tip current and normal force measured simultaneously during local oxidation of titanium using dual-mode scanning probe microscopy

Ozcan, O., Hu, W., Sitti, M., Bain, J., Ricketts, D.

IET Micro \& Nano Letters, 9(5):332-336, IET, 2014 (article)

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[BibTex]

[BibTex]


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Three-dimensional robotic manipulation and transport of micro-scale objects by a magnetically driven capillary micro-gripper

Giltinan, J., Diller, E., Mayda, C., Sitti, M.

In Robotics and Automation (ICRA), 2014 IEEE International Conference on, pages: 2077-2082, 2014 (inproceedings)

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Project Page [BibTex]

Project Page [BibTex]


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SoftCubes: Stretchable and self-assembling three-dimensional soft modular matter

Yim, S., Sitti, M.

The International Journal of Robotics Research, 33(8):1083-1097, SAGE Publications Sage UK: London, England, 2014 (article)

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Project Page [BibTex]

Project Page [BibTex]


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Bio-Hybrid Cell-Based Actuators for Microsystems

Carlsen, Rika Wright, Sitti, Metin

Small, 10(19):3831-3851, 2014 (article)

Abstract
As we move towards the miniaturization of devices to perform tasks at the nano and microscale, it has become increasingly important to develop new methods for actuation, sensing, and control. Over the past decade, bio-hybrid methods have been investigated as a promising new approach to overcome the challenges of scaling down robotic and other functional devices. These methods integrate biological cells with artificial components and therefore, can take advantage of the intrinsic actuation and sensing functionalities of biological cells. Here, the recent advancements in bio-hybrid actuation are reviewed, and the challenges associated with the design, fabrication, and control of bio-hybrid microsystems are discussed. As a case study, focus is put on the development of bacteria-driven microswimmers, which has been investigated as a targeted drug delivery carrier. Finally, a future outlook for the development of these systems is provided. The continued integration of biological and artificial components is envisioned to enable the performance of tasks at a smaller and smaller scale in the future, leading to the parallel and distributed operation of functional systems at the microscale.

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link (url) DOI Project Page [BibTex]

link (url) DOI Project Page [BibTex]


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Addressing of Micro-robot Teams and Non-contact Micro-manipulation

Diller, E., Ye, Z., Giltinan, J., Sitti, M.

In Small-Scale Robotics. From Nano-to-Millimeter-Sized Robotic Systems and Applications, pages: 28-38, Springer Berlin Heidelberg, 2014 (incollection)

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Project Page [BibTex]

Project Page [BibTex]


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Staying sticky: contact self-cleaning of gecko-inspired adhesives

Mengüç, Y., Röhrig, M., Abusomwan, U., Hölscher, H., Sitti, M.

Journal of The Royal Society Interface, 11(94):20131205, The Royal Society, 2014 (article)

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Project Page [BibTex]

Project Page [BibTex]


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Dynamic Trapping and Two-Dimensional Transport of Swimming Microorganisms Using a Rotating Magnetic Micro-Robot

Ye, Z., Sitti, M.

Lab on a Chip, 14(13):2177-2182, Royal Society of Chemistry, 2014 (article)

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Project Page [BibTex]


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STRIDE II: a water strider-inspired miniature robot with circular footpads

Ozcan, O., Wang, H., Taylor, J. D., Sitti, M.

International Journal of Advanced Robotic Systems, 11(6):85, SAGE Publications Sage UK: London, England, 2014 (article)

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[BibTex]

[BibTex]


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Soft Grippers Using Micro-Fibrillar Adhesives for Transfer Printing

Song, S., Sitti, M.

Advanced Materials, 26(28):4901-4906, 2014 (article)

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[BibTex]

[BibTex]


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Self-Exploration of the Stumpy Robot with Predictive Information Maximization

Martius, G., Jahn, L., Hauser, H., V. Hafner, V.

In Proc. From Animals to Animats, SAB 2014, 8575, pages: 32-42, LNCS, Springer, 2014 (inproceedings)

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[BibTex]

[BibTex]


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Can DC motors directly drive flapping wings at high frequency and large wing strokes?

Campolo, D., Azhar, M., Lau, G., Sitti, M.

IEEE/ASME Trans. on Mechatronics, 19(1):109-120, 2014 (article)

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[BibTex]

[BibTex]