Decentralized, Adaptive Control for Coverage with Networked Robots

A decentralized, adaptive control law is presented to drive a network of mobile robots to a near-optimal sensing configuration. The control law is adaptive in that it integrates sensor measurements to provide a converging estimate of the distribution of sensory information in the environment. It is decentralized in that it requires only information local to each robot. A Lyapunov-type proof is used to show that the control law causes the network to converge to a near-optimal sensing configuration, and the controller is demonstrated in numerical simulations. This technique suggests a broader application of adaptive control methodologies to decentralized control problems in unknown dynamical environments.

Authors

• Mac Schwager
• Jean-Jacques E. Slotine
• Daniela Rus

Keywords

• Adaptive control
• Robot sensing systems
• Control systems
• Robotics and automation
• Distributed control
• Automatic control
• Mobile robots
• Programmable control
• Robot control
• Stability
• Networked Robotic
• Numerical Simulations
• Dynamical
• Optimal Control
• Sensory Information
• Distribution Information
• Sensor Measurements
• Adaptive Law
• Decentralized Control
• Adaptive Control Law
• Robotic Network
• Bimodal
• Local Information
• Sensory Function
• Control Performance
• Mobile Network
• Position Of The Robot
• Robot Dynamics
• Swarm Robotics
• Robotic Group
• Unit Square