Martinez Jose Bernardo, Becerra Hector M, Gomez-Gutierrez David
Centro de Investigación en Matemáticas (CIMAT), Jalisco S/N, Guanajuato, Gto. 36023, Mexico.
Multi-agent Autonomous Systems Lab, Intel Labs, Intel Tecnología de México, Av. del Bosque 1001, Zapopan, Jalisco 45019, Mexico.
Sensors (Basel). 2021 Jun 26;21(13):4374. doi: 10.3390/s21134374.
In this paper, we addressed the problem of controlling the position of a group of unicycle-type robots to follow in formation a time-varying reference avoiding obstacles when needed. We propose a kinematic control scheme that, unlike existing methods, is able to simultaneously solve the both tasks involved in the problem, effectively combining control laws devoted to achieve formation tracking and obstacle avoidance. The main contributions of the paper are twofold: first, the advantages of the proposed approach are not all integrated in existing schemes, ours is fully distributed since the formulation is based on consensus including the leader as part of the formation, scalable for a large number of robots, generic to define a desired formation, and it does not require a global coordinate system or a map of the environment. Second, to the authors' knowledge, it is the first time that a distributed formation tracking control is combined with obstacle avoidance to solve both tasks simultaneously using a hierarchical scheme, thus guaranteeing continuous robots velocities in spite of activation/deactivation of the obstacle avoidance task, and stability is proven even in the transition of tasks. The effectiveness of the approach is shown through simulations and experiments with real robots.
在本文中,我们解决了控制一组独轮车式机器人的位置问题,使其在需要时能够编队跟随一个时变参考轨迹并避开障碍物。我们提出了一种运动控制方案,与现有方法不同的是,该方案能够同时解决问题中涉及的两个任务,有效地结合了用于实现编队跟踪和避障的控制律。本文的主要贡献有两个方面:第一,所提出方法的优点并非都集成在现有方案中,我们的方案是完全分布式的,因为其公式基于一致性,将领导者作为编队的一部分包含在内,可扩展到大量机器人,可通用地定义期望编队,并且不需要全局坐标系或环境地图。第二,据作者所知,这是首次使用分层方案将分布式编队跟踪控制与避障相结合以同时解决这两个任务,从而保证即使在避障任务激活/停用的情况下机器人速度也能连续,并且即使在任务转换时也能证明稳定性。通过对真实机器人的模拟和实验展示了该方法的有效性。