Research

Nature showcases small organisms with remarkable individual locomotion capabilities and collective behaviors — from hummingbirds displaying exceptional agility and precise hovering, to schools of fish navigating thousands of miles in coordinated, adaptive group patterns. These collectives demonstrate an incredible level of **self-organization**, where large numbers of relatively simple agents rely on local interactions to produce complex global behaviors. As a result, the system as a whole becomes greater than the sum of its parts. What makes these systems so fascinating to scientists and engineers is that, despite each individual having limited capabilities, the collective achieves a remarkable degree of autonomy and complexity. My research draws inspiration from biological systems and aims to develop artificial collectives of our own. I focus on creating cost-effective, small-scale robots that can form robotic fleets mimicking biological collectives in several highly desirable ways: (1) exhibiting complex and coherent behavior across large physical scales despite each individual's severely limited perception; (2) achieving decentralized coordination with high robustness to individual failures; (3) leveraging collective action and sensing to enhance efficiency and adaptability.

Research Areas

Formation Control in Underwater Swarm

The schooling behavior of fish is hypothesized to confer many survival benefits, including foraging success, safety from predators, and energy savings through hydrodynamic interactions when swimming in formation. Underwater robot collectives may achieve similar benefits using formation control in future applications, e.g. efficient spatial sampling for environmental monitoring. Although many theoretical algorithms exist for multi-robot formation control, few have been tested in the underwater domain due to fundamental challenges in underwater communication.

We introduce a leader-follower strategy that enables the first realizations of complex three-dimensional (3D) underwater formations using visual information alone. We successfully demonstrate leader-follower pairs executing various 3D following configurations (inline, staggered, and side-by-side formations) and further showcase a multi-robot diamond formation. Comparisons between experimental results and simulation predictions highlight formation-specific challenges for underwater environments, particularly in visual perception, fluid dynamic control, and resource-constrained onboard computing. These findings lay the foundation for future applications of underwater robot swarms in aquatic environments with minimal communication.

Future work will focus on advancing underwater perception through natural-light vision systems and data-driven approaches to handle challenging optical conditions and complex enviornments. These developments will support more scalable and sophisticated swarm behaviors, bringing us closer to using robot collectives to study and interact with natural biological systems.

Fish-inspired Miniaturized Robotic Platform

(Coming soon) Improvements in robot maneuverability—via better control algorithms and hardware design—will further enable agile, fish-inspired actuation.

Actuation and Power in mm-cm Scale

(Coming soon) Despite significant progress in small-sized robotic systems over the past two decades, most platforms lack sufficient payload capacity for onboard power due to size constraints. Developing strong actuators and compact power supplies is thus crucial for realizing full autonomous operation in small robots.