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2014


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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]

2014


DOI [BibTex]


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Probabilistic Progress Bars

Kiefel, M., Schuler, C., Hennig, P.

In Conference on Pattern Recognition (GCPR), 8753, pages: 331-341, Lecture Notes in Computer Science, (Editors: Jiang, X., Hornegger, J., and Koch, R.), Springer, GCPR, September 2014 (inproceedings)

Abstract
Predicting the time at which the integral over a stochastic process reaches a target level is a value of interest in many applications. Often, such computations have to be made at low cost, in real time. As an intuitive example that captures many features of this problem class, we choose progress bars, a ubiquitous element of computer user interfaces. These predictors are usually based on simple point estimators, with no error modelling. This leads to fluctuating behaviour confusing to the user. It also does not provide a distribution prediction (risk values), which are crucial for many other application areas. We construct and empirically evaluate a fast, constant cost algorithm using a Gauss-Markov process model which provides more information to the user.

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website+code pdf DOI [BibTex]

website+code pdf DOI [BibTex]


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Probabilistic Solutions to Differential Equations and their Application to Riemannian Statistics

Hennig, P., Hauberg, S.

In Proceedings of the 17th International Conference on Artificial Intelligence and Statistics, 33, pages: 347-355, JMLR: Workshop and Conference Proceedings, (Editors: S Kaski and J Corander), Microtome Publishing, Brookline, MA, AISTATS, April 2014 (inproceedings)

Abstract
We study a probabilistic numerical method for the solution of both boundary and initial value problems that returns a joint Gaussian process posterior over the solution. Such methods have concrete value in the statistics on Riemannian manifolds, where non-analytic ordinary differential equations are involved in virtually all computations. The probabilistic formulation permits marginalising the uncertainty of the numerical solution such that statistics are less sensitive to inaccuracies. This leads to new Riemannian algorithms for mean value computations and principal geodesic analysis. Marginalisation also means results can be less precise than point estimates, enabling a noticeable speed-up over the state of the art. Our approach is an argument for a wider point that uncertainty caused by numerical calculations should be tracked throughout the pipeline of machine learning algorithms.

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pdf Youtube Supplements Project page link (url) [BibTex]

pdf Youtube Supplements Project page link (url) [BibTex]


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Probabilistic ODE Solvers with Runge-Kutta Means

Schober, M., Duvenaud, D., Hennig, P.

In Advances in Neural Information Processing Systems 27, pages: 739-747, (Editors: Z. Ghahramani, M. Welling, C. Cortes, N.D. Lawrence and K.Q. Weinberger), Curran Associates, Inc., 28th Annual Conference on Neural Information Processing Systems (NIPS), 2014 (inproceedings)

ei pn

Web link (url) [BibTex]

Web link (url) [BibTex]


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Active Learning of Linear Embeddings for Gaussian Processes

Garnett, R., Osborne, M., Hennig, P.

In Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, pages: 230-239, (Editors: NL Zhang and J Tian), AUAI Press , Corvallis, Oregon, UAI2014, 2014, another link: http://arxiv.org/abs/1310.6740 (inproceedings)

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PDF Web [BibTex]

PDF Web [BibTex]


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Probabilistic Shortest Path Tractography in DTI Using Gaussian Process ODE Solvers

Schober, M., Kasenburg, N., Feragen, A., Hennig, P., Hauberg, S.

In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014, Lecture Notes in Computer Science Vol. 8675, pages: 265-272, (Editors: P. Golland, N. Hata, C. Barillot, J. Hornegger and R. Howe), Springer, Heidelberg, MICCAI, 2014 (inproceedings)

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DOI [BibTex]

DOI [BibTex]


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Sampling for Inference in Probabilistic Models with Fast Bayesian Quadrature

Gunter, T., Osborne, M., Garnett, R., Hennig, P., Roberts, S.

In Advances in Neural Information Processing Systems 27, pages: 2789-2797, (Editors: Z. Ghahramani, M. Welling, C. Cortes, N.D. Lawrence and K.Q. Weinberger), Curran Associates, Inc., 28th Annual Conference on Neural Information Processing Systems (NIPS), 2014 (inproceedings)

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Web link (url) [BibTex]

Web link (url) [BibTex]


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Incremental Local Gaussian Regression

Meier, F., Hennig, P., Schaal, S.

In Advances in Neural Information Processing Systems 27, pages: 972-980, (Editors: Z. Ghahramani, M. Welling, C. Cortes, N.D. Lawrence and K.Q. Weinberger), 28th Annual Conference on Neural Information Processing Systems (NIPS), 2014, clmc (inproceedings)

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PDF link (url) [BibTex]

PDF link (url) [BibTex]


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Efficient Bayesian Local Model Learning for Control

Meier, F., Hennig, P., Schaal, S.

In Proceedings of the IEEE International Conference on Intelligent Robots and Systems, pages: 2244 - 2249, IROS, 2014, clmc (inproceedings)

Abstract
Model-based control is essential for compliant controland force control in many modern complex robots, like humanoidor disaster robots. Due to many unknown and hard tomodel nonlinearities, analytical models of such robots are oftenonly very rough approximations. However, modern optimizationcontrollers frequently depend on reasonably accurate models,and degrade greatly in robustness and performance if modelerrors are too large. For a long time, machine learning hasbeen expected to provide automatic empirical model synthesis,yet so far, research has only generated feasibility studies butno learning algorithms that run reliably on complex robots.In this paper, we combine two promising worlds of regressiontechniques to generate a more powerful regression learningsystem. On the one hand, locally weighted regression techniquesare computationally efficient, but hard to tune due to avariety of data dependent meta-parameters. On the other hand,Bayesian regression has rather automatic and robust methods toset learning parameters, but becomes quickly computationallyinfeasible for big and high-dimensional data sets. By reducingthe complexity of Bayesian regression in the spirit of local modellearning through variational approximations, we arrive at anovel algorithm that is computationally efficient and easy toinitialize for robust learning. Evaluations on several datasetsdemonstrate very good learning performance and the potentialfor a general regression learning tool for robotics.

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PDF link (url) DOI [BibTex]

PDF link (url) DOI [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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Dual Execution of Optimized Contact Interaction Trajectories

Toussaint, M., Ratliff, N., Bohg, J., Righetti, L., Englert, P., Schaal, S.

In 2014 IEEE/RSJ Conference on Intelligent Robots and Systems, pages: 47-54, IEEE, Chicago, USA, 2014 (inproceedings)

Abstract
Efficient manipulation requires contact to reduce uncertainty. The manipulation literature refers to this as funneling: a methodology for increasing reliability and robustness by leveraging haptic feedback and control of environmental interaction. However, there is a fundamental gap between traditional approaches to trajectory optimization and this concept of robustness by funneling: traditional trajectory optimizers do not discover force feedback strategies. From a POMDP perspective, these behaviors could be regarded as explicit observation actions planned to sufficiently reduce uncertainty thereby enabling a task. While we are sympathetic to the full POMDP view, solving full continuous-space POMDPs in high-dimensions is hard. In this paper, we propose an alternative approach in which trajectory optimization objectives are augmented with new terms that reward uncertainty reduction through contacts, explicitly promoting funneling. This augmentation shifts the responsibility of robustness toward the actual execution of the optimized trajectories. Directly tracing trajectories through configuration space would lose all robustness-dual execution achieves robustness by devising force controllers to reproduce the temporal interaction profile encoded in the dual solution of the optimization problem. This work introduces dual execution in depth and analyze its performance through robustness experiments in both simulation and on a real-world robotic platform.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Robotic assembly of hydrogels for tissue engineering and regenerative medicine

Tasoglu, S, Diller, E, Guven, S, Sitti, M, Demirci, U

In Journal of Tissue Engineering and Regenerative Medicine, 8, pages: 181-182, 2014 (inproceedings)

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Project Page [BibTex]

Project Page [BibTex]


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Versatile non-contact micro-manipulation method using rotational flows locally induced by magnetic microrobots

Ye, Z., Edington, C., Russell, A. J., Sitti, M.

In Advanced Intelligent Mechatronics (AIM), 2014 IEEE/ASME International Conference on, pages: 26-31, 2014 (inproceedings)

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Project Page [BibTex]

Project Page [BibTex]


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Balancing experiments on a torque-controlled humanoid with hierarchical inverse dynamics

Herzog, A., Righetti, L., Grimminger, F., Pastor, P., Schaal, S.

In 2014 IEEE/RSJ Conference on Intelligent Robots and Systems, pages: 981-988, IEEE, Chicago, USA, 2014 (inproceedings)

Abstract
Recently several hierarchical inverse dynamics controllers based on cascades of quadratic programs have been proposed for application on torque controlled robots. They have important theoretical benefits but have never been implemented on a torque controlled robot where model inaccuracies and real-time computation requirements can be problematic. In this contribution we present an experimental evaluation of these algorithms in the context of balance control for a humanoid robot. The presented experiments demonstrate the applicability of the approach under real robot conditions (i.e. model uncertainty, estimation errors, etc). We propose a simplification of the optimization problem that allows us to decrease computation time enough to implement it in a fast torque control loop. We implement a momentum-based balance controller which shows robust performance in face of unknown disturbances, even when the robot is standing on only one foot. In a second experiment, a tracking task is evaluated to demonstrate the performance of the controller with more complicated hierarchies. Our results show that hierarchical inverse dynamics controllers can be used for feedback control of humanoid robots and that momentum-based balance control can be efficiently implemented on a real robot.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Full Dynamics LQR Control of a Humanoid Robot: An Experimental Study on Balancing and Squatting

Mason, S., Righetti, L., Schaal, S.

In 2014 IEEE-RAS International Conference on Humanoid Robots, pages: 374-379, IEEE, Madrid, Spain, 2014 (inproceedings)

Abstract
Humanoid robots operating in human environments require whole-body controllers that can offer precise tracking and well-defined disturbance rejection behavior. In this contribution, we propose an experimental evaluation of a linear quadratic regulator (LQR) using a linearization of the full robot dynamics together with the contact constraints. The advantage of the controller is that it explicitly takes into account the coupling between the different joints to create optimal feedback controllers for whole-body control. We also propose a method to explicitly regulate other tasks of interest, such as the regulation of the center of mass of the robot or its angular momentum. In order to evaluate the performance of linear optimal control designs in a real-world scenario (model uncertainty, sensor noise, imperfect state estimation, etc), we test the controllers in a variety of tracking and balancing experiments on a torque controlled humanoid (e.g. balancing, split plane balancing, squatting, pushes while squatting, and balancing on a wheeled platform). The proposed control framework shows a reliable push recovery behavior competitive with more sophisticated balance controllers, rejecting impulses up to 11.7 Ns with peak forces of 650 N, with the added advantage of great computational simplicity. Furthermore, the controller is able to track squatting trajectories up to 1 Hz without relinearization, suggesting that the linearized dynamics is sufficient for significant ranges of motion.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Structural optimization method towards synthesis of small scale flexure-based mobile grippers

Lum, G. Z., Diller, E., Sitti, M.

In Robotics and Automation (ICRA), 2014 IEEE International Conference on, pages: 2339-2344, 2014 (inproceedings)

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[BibTex]

[BibTex]


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Six-Degrees-of-Freedom Remote Actuation of Magnetic Microrobots.

Diller, E. D., Giltinan, J., Lum, G. Z., Ye, Z., Sitti, M.

In Robotics: Science and Systems, 2014 (inproceedings)

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[BibTex]

[BibTex]


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State Estimation for a Humanoid Robot

Rotella, N., Bloesch, M., Righetti, L., Schaal, S.

In 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, pages: 952-958, IEEE, Chicago, USA, 2014 (inproceedings)

Abstract
This paper introduces a framework for state estimation on a humanoid robot platform using only common proprioceptive sensors and knowledge of leg kinematics. The presented approach extends that detailed in prior work on a point-foot quadruped platform by adding the rotational constraints imposed by the humanoid's flat feet. As in previous work, the proposed Extended Kalman Filter accommodates contact switching and makes no assumptions about gait or terrain, making it applicable on any humanoid platform for use in any task. A nonlinear observability analysis is performed on both the point-foot and flat-foot filters and it is concluded that the addition of rotational constraints significantly simplifies singular cases and improves the observability characteristics of the system. Results on a simulated walking dataset demonstrate the performance gain of the flat-foot filter as well as confirm the results of the presented observability analysis.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]

2011


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Optimal Reinforcement Learning for Gaussian Systems

Hennig, P.

In Advances in Neural Information Processing Systems 24, pages: 325-333, (Editors: J Shawe-Taylor and RS Zemel and P Bartlett and F Pereira and KQ Weinberger), Twenty-Fifth Annual Conference on Neural Information Processing Systems (NIPS), 2011 (inproceedings)

Abstract
The exploration-exploitation trade-off is among the central challenges of reinforcement learning. The optimal Bayesian solution is intractable in general. This paper studies to what extent analytic statements about optimal learning are possible if all beliefs are Gaussian processes. A first order approximation of learning of both loss and dynamics, for nonlinear, time-varying systems in continuous time and space, subject to a relatively weak restriction on the dynamics, is described by an infinite-dimensional partial differential equation. An approximate finitedimensional projection gives an impression for how this result may be helpful.

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PDF Web [BibTex]

2011


PDF Web [BibTex]


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Design and analysis of a magnetically actuated and compliant capsule endoscopic robot

Yim, S., Sitti, M.

In Robotics and Automation (ICRA), 2011 IEEE International Conference on, pages: 4810-4815, 2011 (inproceedings)

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[BibTex]

[BibTex]


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Micro-scale propulsion using multiple flexible artificial flagella

Singleton, J., Diller, E., Andersen, T., Regnier, S., Sitti, M.

In Intelligent Robots and Systems (IROS), 2011 IEEE/RSJ International Conference on, pages: 1687-1692, 2011 (inproceedings)

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Project Page [BibTex]

Project Page [BibTex]


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Control of multiple heterogeneous magnetic micro-robots on non-specialized surfaces

Diller, E., Floyd, S., Pawashe, C., Sitti, M.

In Robotics and Automation (ICRA), 2011 IEEE International Conference on, pages: 115-120, 2011 (inproceedings)

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[BibTex]

[BibTex]


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Tip based robotic precision micro/nanomanipulation systems

Onal, C., Sumer, B., Ozcan, O., Nain, A., Sitti, M.

In SPIE Defense, Security, and Sensing, pages: 80580M-80580M, 2011 (inproceedings)

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[BibTex]

[BibTex]


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Design of a miniature integrated multi-modal jumping and gliding robot

Woodward, M. A., Sitti, M.

In Intelligent Robots and Systems (IROS), 2011 IEEE/RSJ International Conference on, pages: 556-561, 2011 (inproceedings)

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Project Page [BibTex]

Project Page [BibTex]


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Learning Force Control Policies for Compliant Manipulation

Kalakrishnan, M., Righetti, L., Pastor, P., Schaal, S.

In 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, pages: 4639-4644, IEEE, San Francisco, USA, sep 2011 (inproceedings)

Abstract
Developing robots capable of fine manipulation skills is of major importance in order to build truly assistive robots. These robots need to be compliant in their actuation and control in order to operate safely in human environments. Manipulation tasks imply complex contact interactions with the external world, and involve reasoning about the forces and torques to be applied. Planning under contact conditions is usually impractical due to computational complexity, and a lack of precise dynamics models of the environment. We present an approach to acquiring manipulation skills on compliant robots through reinforcement learning. The initial position control policy for manipulation is initialized through kinesthetic demonstration. We augment this policy with a force/torque profile to be controlled in combination with the position trajectories. We use the Policy Improvement with Path Integrals (PI2) algorithm to learn these force/torque profiles by optimizing a cost function that measures task success. We demonstrate our approach on the Barrett WAM robot arm equipped with a 6-DOF force/torque sensor on two different manipulation tasks: opening a door with a lever door handle, and picking up a pen off the table. We show that the learnt force control policies allow successful, robust execution of the tasks.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Control of legged robots with optimal distribution of contact forces

Righetti, L., Buchli, J., Mistry, M., Schaal, S.

In 2011 11th IEEE-RAS International Conference on Humanoid Robots, pages: 318-324, IEEE, Bled, Slovenia, 2011 (inproceedings)

Abstract
The development of agile and safe humanoid robots require controllers that guarantee both high tracking performance and compliance with the environment. More specifically, the control of contact interaction is of crucial importance for robots that will actively interact with their environment. Model-based controllers such as inverse dynamics or operational space control are very appealing as they offer both high tracking performance and compliance. However, while widely used for fully actuated systems such as manipulators, they are not yet standard controllers for legged robots such as humanoids. Indeed such robots are fundamentally different from manipulators as they are underactuated due to their floating-base and subject to switching contact constraints. In this paper we present an inverse dynamics controller for legged robots that use torque redundancy to create an optimal distribution of contact constraints. The resulting controller is able to minimize, given a desired motion, any quadratic cost of the contact constraints at each instant of time. In particular we show how this can be used to minimize tangential forces during locomotion, therefore significantly improving the locomotion of legged robots on difficult terrains. In addition to the theoretical result, we present simulations of a humanoid and a quadruped robot, as well as experiments on a real quadruped robot that demonstrate the advantages of the controller.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Learning Motion Primitive Goals for Robust Manipulation

Stulp, F., Theodorou, E., Kalakrishnan, M., Pastor, P., Righetti, L., Schaal, S.

In IEEE/RSJ International Conference on Intelligent Robots and Systems, pages: 325-331, IEEE, San Francisco, USA, sep 2011 (inproceedings)

Abstract
Applying model-free reinforcement learning to manipulation remains challenging for several reasons. First, manipulation involves physical contact, which causes discontinuous cost functions. Second, in manipulation, the end-point of the movement must be chosen carefully, as it represents a grasp which must be adapted to the pose and shape of the object. Finally, there is uncertainty in the object pose, and even the most carefully planned movement may fail if the object is not at the expected position. To address these challenges we 1) present a simplified, computationally more efficient version of our model-free reinforcement learning algorithm PI2; 2) extend PI2 so that it simultaneously learns shape parameters and goal parameters of motion primitives; 3) use shape and goal learning to acquire motion primitives that are robust to object pose uncertainty. We evaluate these contributions on a manipulation platform consisting of a 7-DOF arm with a 4-DOF hand.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Inverse Dynamics Control of Floating-Base Robots with External Constraints: a Unified View

Righetti, L., Buchli, J., Mistry, M., Schaal, S.

In 2011 IEEE International Conference on Robotics and Automation, pages: 1085-1090, IEEE, Shanghai, China, 2011 (inproceedings)

Abstract
Inverse dynamics controllers and operational space controllers have proved to be very efficient for compliant control of fully actuated robots such as fixed base manipulators. However legged robots such as humanoids are inherently different as they are underactuated and subject to switching external contact constraints. Recently several methods have been proposed to create inverse dynamics controllers and operational space controllers for these robots. In an attempt to compare these different approaches, we develop a general framework for inverse dynamics control and show that these methods lead to very similar controllers. We are then able to greatly simplify recent whole-body controllers based on operational space approaches using kinematic projections, bringing them closer to efficient practical implementations. We also generalize these controllers such that they can be optimal under an arbitrary quadratic cost in the commands.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Free flight simulations and pitch and roll control experiments of a sub-gram flapping-flight micro aerial vehicle

Hines, L. L., Arabagi, V., Sitti, M.

In Robotics and Automation (ICRA), 2011 IEEE International Conference on, pages: 1-7, 2011 (inproceedings)

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Project Page [BibTex]

Project Page [BibTex]


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Chemotactic behavior and dynamics of bacteria propelled microbeads

Kim, Dongwook, Liu, Albert, Stitti, Metin

In Intelligent Robots and Systems (IROS), 2011 IEEE/RSJ International Conference on, pages: 1674-1679, 2011 (inproceedings)

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Project Page [BibTex]

Project Page [BibTex]


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Operational Space Control of Constrained and Underactuated Systems

Mistry, M., Righetti, L.

In Proceedings of Robotics: Science and Systems, Los Angeles, CA, USA, June 2011 (inproceedings)

Abstract
The operational space formulation (Khatib, 1987), applied to rigid-body manipulators, describes how to decouple task-space and null-space dynamics, and write control equations that correspond only to forces at the end-effector or, alternatively, only to motion within the null-space. We would like to apply this useful theory to modern humanoids and other legged systems, for manipulation or similar tasks, however these systems present additional challenges due to their underactuated floating bases and contact states that can dynamically change. In recent work, Sentis et al. derived controllers for such systems by implementing a task Jacobian projected into a space consistent with the supporting constraints and underactuation (the so called "support consistent reduced Jacobian"). Here, we take a new approach to derive operational space controllers for constrained underactuated systems, by first considering the operational space dynamics within "projected inverse-dynamics" (Aghili, 2005), and subsequently resolving underactuation through the addition of dynamically consistent control torques. Doing so results in a simplified control solution compared with previous results, and importantly yields several new insights into the underlying problem of operational space control in constrained environments: 1) Underactuated systems, such as humanoid robots, cannot in general completely decouple task and null-space dynamics. However, 2) there may exist an infinite number of control solutions to realize desired task-space dynamics, and 3) these solutions involve the addition of dynamically consistent null-space motion or constraint forces (or combinations of both). In light of these findings, we present several possible control solutions, with varying optimization criteria, and highlight some of their practical consequences.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Under-actuated tank-like climbing robot with various transitioning capabilities

Seo, T., Sitti, M.

In Robotics and Automation (ICRA), 2011 IEEE International Conference on, pages: 777-782, 2011 (inproceedings)

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[BibTex]

[BibTex]


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Rotating magnetic micro-robots for versatile non-contact fluidic manipulation of micro-objects

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

In Intelligent Robots and Systems (IROS), 2011 IEEE/RSJ International Conference on, pages: 1291-1296, 2011 (inproceedings)

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Project Page [BibTex]

Project Page [BibTex]


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Online movement adaptation based on previous sensor experiences

Pastor, P., Righetti, L., Kalakrishnan, M., Schaal, S.

In 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, pages: 365-371, IEEE, San Francisco, USA, sep 2011 (inproceedings)

Abstract
Personal robots can only become widespread if they are capable of safely operating among humans. In uncertain and highly dynamic environments such as human households, robots need to be able to instantly adapt their behavior to unforseen events. In this paper, we propose a general framework to achieve very contact-reactive motions for robotic grasping and manipulation. Associating stereotypical movements to particular tasks enables our system to use previous sensor experiences as a predictive model for subsequent task executions. We use dynamical systems, named Dynamic Movement Primitives (DMPs), to learn goal-directed behaviors from demonstration. We exploit their dynamic properties by coupling them with the measured and predicted sensor traces. This feedback loop allows for online adaptation of the movement plan. Our system can create a rich set of possible motions that account for external perturbations and perception uncertainty to generate truly robust behaviors. As an example, we present an application to grasping with the WAM robot arm.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Assembly and disassembly of magnetic mobile micro-robots towards deterministic 2-D reconfigurable micro-systems

Pawashe, C., Diller, E., Floyd, S., Sitti, M.

In Robotics and Automation (ICRA), 2011 IEEE International Conference on, pages: 261-266, 2011 (inproceedings)

pi

[BibTex]

[BibTex]


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Stochastic dynamics of bacteria propelled spherical micro-robots

Arabagi, V., Behkam, B., Sitti, M.

In Intelligent Robots and Systems (IROS), 2011 IEEE/RSJ International Conference on, pages: 3937-3942, 2011 (inproceedings)

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[BibTex]

[BibTex]

2009


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Characterization of bacterial actuation of micro-objects

Behkam, B., Sitti, M.

In Robotics and Automation, 2009. ICRA’09. IEEE International Conference on, pages: 1022-1027, 2009 (inproceedings)

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[BibTex]

2009


[BibTex]


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Compliant footpad design analysis for a bio-inspired quadruped amphibious robot

Park, H. S., Sitti, M.

In Intelligent Robots and Systems, 2009. IROS 2009. IEEE/RSJ International Conference on, pages: 645-651, 2009 (inproceedings)

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[BibTex]

[BibTex]


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Modelling the interplay of central pattern generation and sensory feedback in the neuromuscular control of running

Daley, M., Righetti, L., Ijspeert, A.

In Comparative Biochemistry and Physiology - Part A: Molecular & Integrative Physiology. Annual Main Meeting for the Society for Experimental Biology, 153, Glasgow, Scotland, 2009 (inproceedings)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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A novel artificial hair receptor based on aligned PVDF micro/nano fibers

Weiting, Liu, Bilsay, Sumer, Cesare, Stefanini, Arianna, Menciassi, Fei, Li, Dajing, Chen, Paolo, Dario, Metin, Sitti, Xin, Fu

In Robotics and Biomimetics, 2008. ROBIO 2008. IEEE International Conference on, pages: 49-54, 2009 (inproceedings)

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[BibTex]

[BibTex]


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Waalbot: Agile climbing with synthetic fibrillar dry adhesives

Murphy, M. P., Sitti, M.

In Robotics and Automation, 2009. ICRA’09. IEEE International Conference on, pages: 1599-1600, 2009 (inproceedings)

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[BibTex]

[BibTex]


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Piezoelectric ultrasonic resonant micromotor with a volume of less than 1 mm 3 for use in medical microbots

Watson, B., Friend, J., Yeo, L., Sitti, M.

In Robotics and Automation, 2009. ICRA’09. IEEE International Conference on, pages: 2225-2230, 2009 (inproceedings)

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[BibTex]

[BibTex]


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Dynamic modeling and analysis of pitch motion of a basilisk lizard inspired quadruped robot running on water

Park, H. S., Floyd, S., Sitti, M.

In Robotics and Automation, 2009. ICRA’09. IEEE International Conference on, pages: 2655-2660, 2009 (inproceedings)

pi

[BibTex]

[BibTex]


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A miniature ceiling walking robot with flat tacky elastomeric footpads

Unver, O., Sitti, M.

In Robotics and Automation, 2009. ICRA’09. IEEE International Conference on, pages: 2276-2281, 2009 (inproceedings)

pi

[BibTex]

[BibTex]


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Tankbot: A miniature, peeling based climber on rough and smooth surfaces

Unver, O., Sitti, M.

In Robotics and Automation, 2009. ICRA’09. IEEE International Conference on, pages: 2282-2287, 2009 (inproceedings)

pi

[BibTex]

[BibTex]


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Automated 2-D nanoparticle manipulation with an atomic force microscope

Onal, C. D., Ozcan, O., Sitti, M.

In Robotics and Automation, 2009. ICRA’09. IEEE International Conference on, pages: 1814-1819, 2009 (inproceedings)

pi

[BibTex]

[BibTex]


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Microparticle manipulation using multiple untethered magnetic micro-robots on an electrostatic surface

Floyd, S., Pawashe, C., Sitti, M.

In Intelligent Robots and Systems, 2009. IROS 2009. IEEE/RSJ International Conference on, pages: 528-533, 2009 (inproceedings)

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[BibTex]

[BibTex]

2005


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Modeling and testing of a biomimetic flagellar propulsion method for microscale biomedical swimming robots

Behkam, B., Sitti, M.

In Proceedings of Advanced Intelligent Mechatronics Conference, pages: 37-42, 2005 (inproceedings)

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Project Page [BibTex]

2005


Project Page [BibTex]


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Biologically inspired adhesion based surface climbing robots

Menon, C., Sitti, M.

In Robotics and Automation, 2005. ICRA 2005. Proceedings of the 2005 IEEE International Conference on, pages: 2715-2720, 2005 (inproceedings)

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[BibTex]

[BibTex]


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Claytronics: highly scalable communications, sensing, and actuation networks

Aksak, Burak, Bhat, Preethi Srinivas, Campbell, Jason, DeRosa, Michael, Funiak, Stanislav, Gibbons, Phillip B, Goldstein, Seth Copen, Guestrin, Carlos, Gupta, Ashish, Helfrich, Casey, others

In Proceedings of the 3rd international conference on Embedded networked sensor systems, pages: 299-299, 2005 (inproceedings)

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[BibTex]

[BibTex]