Object Gathering with a Tethered Robot Duo

We devise a cooperative planning framework to generate optimal trajectories for tethered robot duo, who is tasked gather scattered objects spread in large area using flexible net. Specifically, the proposed first produces set of dense waypoints each robot, serving as initialization optimization. Next, we formulate an iterative optimization scheme smooth and collision-free while ensuring cooperation within duo efficiently properly avoid obstacles. validate generated simulation implement them physical robots Model Reference Adaptive Controller (MRAC) handle unknown dynamics carried payloads. In series studies, find that: (i) U-shape cost function effective (ii) task efficiency not always proportional net's length. Given environment configuration, our can gauge net To best knowledge, ours that provides such estimation duo.