A multi-robot system (MRS) is a group of coordinated robots designed to cooperate with each other and accomplish given tasks. Due to the uncertainties in operating environments, the system may encounter emergencies, such as unobserved obstacles, moving vehicles, and extreme weather. Animal groups such as bee colonies initiate collective emergency reaction behaviors such as bypassing obstacles and avoiding predators, similar to muscle-conditioned reflex which organizes local muscles to avoid hazards in the first response without delaying passage through the brain. Inspired by this, we develop a similar collective conditioned reflex mechanism for multi-robot systems to respond to emergencies. In this study, Collective Conditioned Reflex (CCR), a bio-inspired emergency reaction mechanism, is developed based on animal collective behavior analysis and multi-agent reinforcement learning (MARL). The algorithm uses a physical model to determine if the robots are experiencing an emergency; then, rewards for robots involved in the emergency are augmented with corresponding heuristic rewards, which evaluate emergency magnitudes and consequences and decide local robots' participation. CCR is validated on three typical emergency scenarios: \textit{turbulence, strong wind, and hidden obstacle}. Simulation results demonstrate that CCR improves robot teams' emergency reaction capability with faster reaction speed and safer trajectory adjustment compared with baseline methods.
翻译:多机器人系统(MRS)是一组协调的机器人,旨在彼此合作并完成既定任务。由于操作环境中的不确定性,该系统可能遇到紧急情况,如无观测障碍、移动车辆和极端天气。蜜蜂聚居地等动物群发起集体紧急反应行为,如绕过障碍和避免捕食者,类似于肌肉调节反应,组织当地肌肉以避免第一次反应时出现危险,而不会延误大脑的通过。受此启发,我们为多机器人系统开发了一个类似的集体条件反射机制,以应对紧急情况。在本研究中,集体调节反射(CRR),即生物激励应急反应机制,是在动物集体行为分析和多剂强化学习(MARL)的基础上开发的。算法使用物理模型来确定机器人是否正在经历紧急情况;然后,对参与紧急情况的机器人的奖励增加相应的超光度奖励,评估紧急情况的规模和后果,并决定当地机器人的参与。CRCR在三种典型的紧急情况假设下验证了集体调节:Cextiturity Reflex Reflex(CR), 集体受生物启发的应急反应机制,这是基于动物集体集体集体集体行为分析和多剂强化的强化的强化的强化模型,并显示隐藏的轨道反应能力。Simlaculturdestrucultal laudd) 和精确反应。