Generating Desired Robot Movements from Complex Environment

Guest Speaker:
Feifei Qian — Dept. of Electrical and Computer Engineering – USC

Wednesday, September 16th, 2020
Zoom Webinar Link
2:00PM – 3:00PM

Webinar Link:

Abstract: Robots nowadays are expected to take on increasingly important roles in human society. However, state-of-the-art robots still struggle to move on natural terrains such as soft sand and rubble field, due to the lack of understanding of the interactions between robots and non-flat, non-rigid surfaces. In this talk, I will use a few examples from my recent work to illustrate how I use a “robophysics” approach – an integration of robotics, terradynamics, and locomotion biomechanics — to create interaction models and frameworks that can guide design and control of bio-inspired robots to enable effective movements on challenging terrains.

First, I will briefly review my previous work of modelling animal and robot locomotion on granular terrains such as sand, debris, and gravel, and discuss how legged locomotors could manipulate sand responses through adjustments in morphological parameters or contact strategy. These robot-sand interacting mechanisms have recently enabled development of desert-exploring robot assistants that can use their leg as soil strength sensors, and help human scientists generate erodibility maps by walking around the desert. I will then discuss my recent and on-going work on creating simplified representations for robot locomotion on perturbation-rich environments such as cluttered rubble field or fallen tree trunks, and demonstrate how a multi-legged robot could use different gait patterns to take advantage of obstacle collisions and generate desired motion under repeated disturbances. I will conclude with a vision of how these models and representations are leading to innovative strategies for environment-aided robot locomotion, better understandings of animal gait transition behaviors, and new cognitive workflows of human-robot collaborative explorations.

Biography: Feifei Qian is an Assistant Professor of Electrical Engineering at USC. She received her PhD in Electrical Engineering and M.S. in Physics from Georgia Institute of Technology, in 2015 and 2011, respectively. Prior to her appointment at USC, she worked in the GRASP lab at University of Pennsylvania as a postdoctoral fellow. Her expertise is in analyzing and modeling the complex interactions between robots and environments, and developing innovative control and sensing strategies to improve robot mobility on challenging terrains. Her work has been featured in BBC News and R&D Magazine, and was awarded the best student paper of Robotics: Science & Systems.

Host: Pierluigi Nuzzo
Center for Cyber-Physical Systems and the Internet of Things (CCI)
Ming Hsieh Institute for Electrical and Computer Engineering (MHI)