首页 /研究 /Energy-Optimal Motion Planning for Agents: Barycentric Motion and Collision Avoidance Constraints
SWARM

Energy-Optimal Motion Planning for Agents: Barycentric Motion and Collision Avoidance Constraints

Logan E. Beaver, Michael Dorothy, Christopher Kroninger, Andreas A. Malikopoulos

发表年份
2021
引用次数
2

摘要

As robotic swarm systems emerge, it is increasingly important to provide strong guarantees on energy consumption and safety to maximize system performance. One approach to achieve these guarantees is through constraint-driven control, where agents seek to minimize energy consumption subject to a set of safety and task constraints. In this paper, we provide an equivalent sufficient and necessary optimality condition for an energy-minimizing agent with integrator dynamics that only depends on the state and control actions of the agent. In particular, we show that the agent must have a continuous control input at the transition between unconstrained and constrained trajectories. In addition, we present and analyze barycentric motion and collision avoidance constraints to be used in constraint-driven control of swarms.

关键词

Collision avoidanceConstraint (computer-aided design)Computer scienceMathematical optimizationEnergy consumptionMotion planningControl theory (sociology)CollisionBarycentric coordinate systemSet (abstract data type)

相关论文

查看 SWARM 分类全部论文