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Fall 2024 GRASP SFI: Baxi Chong, Georgia Institute of Technology, “Mechanical intelligence in locomotion: from information theory to mesoscale robots”

September 25 at 3:00 PM - 4:00 PM

This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom.

ABSTRACT

Locomotion in complex environments (e.g., rubble, leaf litter, granular media) is essential to mobile engineered systems such as robots. Effective locomotion requires complex control strategies to interact with terrain heterogeneity. Computational intelligence (CI), which typically includes rapid terrain sensing and active feedback controls, is a widely recognized component in locomotion strategy. Alternatively, mechanical intelligence (MI) – passive response to environmental perturbation governed by physics laws or mechanical constraints – is an important yet less studied component. In this talk, I will discuss “why” and “how” MI can contribute to effective locomotion using the examples of multi-legged robots (redundantly segmented bodies with simple legs). For the “why,” I will quantify a specific MI that emerges from leg redundancy. By modeling locomotion as a stochastic process (analogous to signal transmission over noisy channels), I will show that MI, without any CI, is sufficient to generate reliable and effective locomotion. To explore the “how,” I will take a quantitative analogy to signal transmission algorithms (e.g., error correcting/detecting codes) and propose a co-design coding scheme for multi-legged locomotion. Specifically, my talk will cover that (i) additional legs, with higher control dimensions, can enable a broader spectrum of capabilities, including load carrying/pulling, sidewinding, rolling, and obstacle-climbing; (ii) the inclusion of CI (feedback controls) can enhance multi-legged locomotion speed while preserving the feature of robustness; and (iii) CI might reduce the number of redundant legs required to navigate a particular terrain. Finally, I will discuss the coordination and competition between MI and CI in a broader framework termed Embedded Intelligence (EI) and illustrate the applications of MI-dominated systems in fields like search-and-rescue, agriculture, and the development of soft, micro, and modular robots.

Baxi Chong

Georgia Institute of Technology

Dr. Baxi Chong is a postdoctoral fellow at the CRAB (Complex Rheology And Biomechanics) Lab in the School of Physics at Georgia Tech. His research focuses on locomotion with mechanical intelligence. Specifically, Dr. Chong studies a diversity of unconventional (e.g., multi-legged, elongated, or cable-driven) robots, and how/why their special body plans can introduce benefits to locomotion in specific environments. Dr. Chong contributed to over 10 research articles on high-impact journals such as Science, Science Robotics, PNAS, and IJRR. His scientific work has been featured in several media outlets, including BBC, Physics World, Forbes, and Nature Research Highlight. Besides the contribution to science, Dr. Chong’s research laid the theoretical foundation for a start-up company (Ground Control Robotics, Ltd) where he currently serves as the leader in the robophysics research team. Dr. Chong has been recently recognized by the Forbes 30 Under 30 List for his contribution in fundamental science and industry.

Details

Date:
September 25
Time:
3:00 PM - 4:00 PM
Event Category:
Website:
https://www.grasp.upenn.edu/events/fall-2024-grasp-sfi-baxi-chong/

Organizer

General Robotics, Automation, Sensing and Perception (GRASP) Lab
Email
grasplab@seas.upenn.edu
View Organizer Website

Venue

Levine 307
3330 Walnut Street
Philadelphia, PA 19104 United States
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