Multi-robot teams have attracted attention from industry and academia for their ability to perform collaborative tasks in unstructured environments, such as wilderness rescue and collaborative transportation.In this paper, we propose a trajectory planning method for a non-holonomic robotic team with collaboration in unstructured environments.For the adaptive state collaboration of a robot team to catch and transport targets to be rescued using a net, we model the process of catching the falling target with a net in a continuous and differentiable form.This enables the robot team to fully exploit the kinematic potential, thereby adaptively catching the target in an appropriate state.Furthermore, the size safety and topological safety of the net, resulting from the collaborative support of the robots, are guaranteed through geometric constraints.We integrate our algorithm on a car-like robot team and test it in simulations and real-world experiments to validate our performance.Our method is compared to state-of-the-art multi-vehicle trajectory planning methods, demonstrating significant performance in efficiency and trajectory quality.

翻译：多机器人团队因其在非结构化环境（如野外救援与协同运输）中执行协作任务的能力，受到工业界与学术界的关注。本文针对非完整约束机器人团队在非结构化环境下的协同问题，提出一种轨迹规划方法。为了实现机器人团队自适应状态协作，利用网具捕捉并运输待救援目标，我们将使用网具捕捉下落目标的过程建模为连续可微形式。这使得机器人团队能够充分发挥运动学潜力，从而在合适状态下自适应地捕捉目标。此外，通过几何约束确保了由机器人协同支撑的网具的尺寸安全性与拓扑安全性。我们将所提算法集成于类车机器人团队，并在仿真与真实实验中验证其性能。与当前最先进的多车辆轨迹规划方法相比，本方法在效率与轨迹质量方面展现出显著优势。