Title: Mechanical intelligence in locomotion: from information theory to multi-legged robots

Speaker: Prof. Baxi Chong (Penn State)

Location: Gates Computer Science, B3 (link)

Attendance Link: https://tinyurl.com/robosem-spr-2026

Time: Friday Apr 3rd, 3:00-4:00PM

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.

Bio:

Dr. Baxi Chong is an assistant professor of mechanical engineering at Penn State University. 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 20 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. Dr. Chong has been recently recognized by the Forbes 30 Under 30 List for his contribution in fundamental science and industry.

Please visit https://stanfordasl.github.io/robotics_seminar/ for this quarter’s lineup of speakers. Although we encourage live in-person attendance, recordings of talks will be posted also.

If you’re interested, you’re welcome to join Baxi for lunch at Blend Cafe at 12 PM. Please let Hao Li (li2053@stanford.edu) know if you plan to join.