School of Physics Thesis Dissertation Defense

Akash Vardhan 
Advisor: Dr. Daniel Goldman, School of Physics, Georgia Institute of Technology

Collision induced self-organization in shape changing robots

Date: Wednesday, April 23, 2025
Time: 2:00 p.m.
Location: Howey N201/N202

Zoom link: https://gatech.zoom.us/j/91089082896?pwd=7IPNp2p8OedISbSopdgWa0G6m5cB01.1

 Meeting ID: 910 8908 2896

Passcode: 275189

Committee members:
Dr. Zeb Rocklin, School of Physics, Georgia Institute of Technology
Dr. Kurt Wiesenfeld, School of Physics, Georgia Institute of Technology

Dr. Dana Randall, College of Computing, Georgia Institute of Technology

Dr. Kirstin H. Petersen, School of Electrical and Computer Engineering, Cornell University

Abstract:
This dissertation explores how collective behaviors emerge in ensembles of active, shape-changing robots that interact through collisions on a frictional substrate. This work extends the granular matter paradigm to encompass internally actuated, concave robots, enabling dynamic self-organization via shape and gait coordination. Initial studies reveal how pinned robot collectives spontaneously settle into low-rattling, repeatable motion patterns, highlighting the role of environmental coupling in selecting stable configurations. Focusing next on minimal interaction units, the work uncovers a novel binding mechanism in gliding dyads, where timed, repulsive contacts and shape-induced concavity produce long-lived, gliders. Further analysis shows that breaking time-reversal symmetry via non-reciprocal gaits enables robust, steerable transport through non-commutative dynamics. In both studies, minimal feedback aids in harnessing and tuning emergent behavior, laying the groundwork for task-oriented control. Finally, the study extends to many-body systems, revealing how local interactions scale up to complex structures—such as chains and loops—whose morphologies depend on gait design. Across all regimes, template dictated collisional interactions guide the emergence of persistent, programmable behaviors in robotic granular systems.