A vision-based formation control framework

TLDR

The modular approach is attractive due to its potential for reusability. The authors present a framework for cooperative control of nonholonomic mobile robots that builds complex systems from simple controllers and estimators. The framework switches between decentralized controllers to change formations, relies on omnidirectional camera data, and uses estimators that abstract sensory information at multiple levels for both decentralized and centralized control. The composition guarantees stability and convergence across many tasks, as demonstrated by numerical simulations and experiments with a three‑robot testbed.

Abstract

We describe a framework for cooperative control of a group of nonholonomic mobile robots that allows us to build complex systems from simple controllers and estimators. The resultant modular approach is attractive because of the potential for reusability. Our approach to composition also guarantees stability and convergence in a wide range of tasks. There are two key features in our approach: 1) a paradigm for switching between simple decentralized controllers that allows for changes in formation; 2) the use of information from a single type of sensor, an omnidirectional camera, for all our controllers. We describe estimators that abstract the sensory information at different levels, enabling both decentralized and centralized cooperative control. Our results include numerical simulations and experiments using a testbed consisting of three nonholonomic robots.