Exploration of unknown environments is an important challenge in the field of robotics. While a single robot can achieve this task alone, evidence suggests it could be accomplished more efficiently by groups of robots, with advantages in terms of terrain coverage as well as robustness to failures. Exploration can be guided through belief maps, which provide probabilistic information about which part of the terrain is interesting to explore (either based on risk management or reward). This process can be centrally coordinated by building a collective belief map on a common server. However, relying on a central processing station creates a communication bottleneck and single point of failure for the system. In this paper, we present Distributed Online Risk-Aware (DORA) Explorer, an exploration system that leverages decentralized information sharing to update a common risk belief map. DORA Explorer allows a group of robots to explore an unknown environment discretized as a 2D grid with obstacles, with high coverage while minimizing exposure to risk, effectively reducing robot failures
翻译:探索未知环境是机器人领域的一项重要挑战。 虽然单一个机器人可以单独完成这项任务,但证据表明,这可由一组机器人更高效地完成,在地形覆盖和抵御失败方面都有优势。 探索可以通过信仰地图指导。 信仰地图可以提供概率性信息,说明哪些部分地形值得探索(基于风险管理或奖励)。 这一过程可以通过在共用服务器上建立集体信仰地图进行集中协调。 但是,依赖一个中央处理站为系统制造通信瓶颈和单一的故障点。 在本文中,我们介绍了分布式在线风险软件(DORA)探索器,这是一个利用分散式信息共享更新共同风险信任地图的探索系统。 DORA 探索器允许一组机器人探索一个与2D格分离的未知环境,该网有障碍,覆盖面大,同时尽量减少风险,有效减少机器人的故障。