Automatic Centralized Control of Underactuated Large-scale Multi-robot Systems using a Generalized Coordinate Transformation
This addresses energy-efficient control for underactuated robots in gathering tasks, but it is incremental as it builds on centralized methods for a specific scenario.
The paper tackles the problem of controlling large-scale underactuated multi-robot systems by proposing a centralized stochastic approach with a generalized coordinate transformation and optimal control for energy efficiency, demonstrating feasibility in simulations.
Controlling large-scale particle or robot systems is challenging because of their high dimensionality. We use a centralized stochastic approach that allows for optimal control at the cost of a central element instead of a decentralized approach. Previous works are often restricted to the assumption of fully actuated robots. Here we propose an approach for underactuated robots that allows for energy-efficient control of the robot system. We consider a simple task of gathering the robots (minimizing positional variance) and steering them towards a goal point within a bounded area without obstacles. We make two main contributions. First, we present a generalized coordinate transformation for underactuated robots, whose physical properties should be considered. We choose Euler- Lagrange systems that describe a large class of robot systems. Second, we propose an optimal control mechanism with the prime objective of energy efficiency. We show the feasibility of our approach in numerical simulations and robot simulations.