Farimah received her BSc and MSc degrees in Mechanical Engineering from Shiraz University in 2014 and 2017. She is now a Ph.D. researcher in the Haptic Intelligence Department at the Max Planck Institute for Intelligent Systems. She is interested in haptics, robotics, dynamics, mechanism design, and sensor fusion.
Creating haptic experiences often entails inventing, modifying, or selecting specialized hardware. However, experience designers are rarely engineers, and 30 years of haptic inventions are buried in the fragmented literature that describes devices mechanically rather...
Fluidic actuators allow versatile, agile, and powerful motions and are commonly applied in robotics and automation. Likewise, many biological systems use fluidic actuators implemented with tissue for a wealth of tasks and performances.
Spiders apply a hybrid mechanism of hydraulically actuated joint extension and...
In Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems (CHI), Glasgow, Scotland, May 2019 (inproceedings)
Creating haptic experiences often entails inventing, modifying, or selecting specialized hardware. However, experience designers are rarely engineers, and 30 years of haptic inventions are buried in a fragmented literature that describes devices mechanically rather than by potential purpose. We conceived of Haptipedia to unlock this trove of examples: Haptipedia presents a device corpus for exploration through metadata that matter to both device and experience designers. It is a taxonomy of device attributes that go beyond physical description to capture potential utility, applied to a growing database of 105 grounded force-feedback devices, and accessed through a public visualization that links utility to morphology. Haptipedia's design was driven by both systematic review of the haptic device literature and rich input from diverse haptic designers. We describe Haptipedia's reception (including hopes it will redefine device reporting standards) and our plans for its sustainability through community participation.
Hands-on demonstration presented at EuroHaptics, Pisa, Italy, June 2018 (misc)
How many haptic devices have been proposed in the last 30 years? How can we leverage this rich source of design knowledge to inspire future innovations? Our goal is to make historical haptic invention accessible through interactive visualization of a comprehensive library – a Haptipedia – of devices that have been annotated with designer-relevant metadata. In this demonstration, participants can explore Haptipedia’s growing library of grounded force feedback devices through several prototype visualizations, interact with 3D simulations of the device mechanisms and movements, and tell us about the attributes and devices that could make Haptipedia a useful resource for the haptic design community.
Iranian Journal of Science and Technology, Transactions of Mechanical Engineering, 40, pages: 77–85, Springer International Publishing, March 2016 (article)
Gas and liquid pipelines surround us. To ensure reliable product delivery and to maintain pipeline integrity, asset managers should consider routine pipeline inspection and holistic management programs to extend pipeline life and prevent risk. Therefore, pipe inspection robots are of special interest to industries. In this paper, we present a new and simple locomotion strategy for an out-pipe inspection robot which can provide adjustable tractive force and can also be utilized to support active diameter adaptability. The advantages proposed by this design include simplicity, low manufacturing costs, online inspection capability and short operational time. Here a dynamic model of the robot is presented with the required assumptions. The mathematical model of 2-DOF robot is obtained using the well-known Lagrange equation. Modeling and simulations were conducted to test the validity and practicality of the proposed design and strategies. The prototype has successfully traveled along a pipe of 20 cm diameter. The results obtained from our dynamic model are then validated by experimental data.
Our goal is to understand the principles of Perception, Action and Learning in autonomous systems that successfully interact with complex environments and to use this understanding to design future systems