Part of the book: Multi-Robot Systems
The motions of a formation of mobile robots along predetermined paths are optimized according to a tunable time-energy cost function using the cluster space approach to multiagent system specification and control. Upon path-parameterizing cluster state variables describing the geometry and pose of a multirobot group, an optimal control problem is formulated that incorporates formation dynamics and state constraints. The optimal trajectory is derived numerically via a gradient search, iterating over the initial value of one costate. A multirobot formation control simulation is then used to demonstrate the effectiveness of the technique. Results indicate that a substantial tradeoff is made between energy expenditure and motion time when considered as minimization criteria in varying proportions, allowing the operator to tailor mission trajectories according to desired levels of each.
Part of the book: Recent Advances in Robotic Systems
A unified motion control architecture is presented for dynamic, long-range multi-robot communications networks, incorporating task abstraction that disassociates goals from implementation. In the task space, communication link states are specified, directly measured, and explicitly controlled yielding well-behaved task state trajectories. The control architecture uses task-level compensation to generate multi-robot formation mobility commands, and a cluster space controller transforms those formation commands to mobility commands for individual robots. The number of robots are selected to meet communications requirements and controlled through a multi-task coordination capability incorporated within the architecture. Robustness to performance commands, system configuration parameters, and external disturbances is demonstrated through a variety of simulations and experiments. These show how robots are dynamically positioned and switched into or out of operation in order to meet communications requirements.
Part of the book: Multi-Robot Systems