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Adaptive Finite-Time Tracking Control of Nonholonomic Multirobot Formation Systems With Limited Field-of-View Sensors.
IEEE Transactions on Cybernetics ( IF 9.4 ) Pub Date : 2021-03-23 , DOI: 10.1109/tcyb.2021.3063481
Shi-Lu Dai , Ke Lu , Jun Fu

This article studies the vision-based tracking control problem for a nonholonomic multirobot formation system with uncertain dynamic models and visibility constraints. A fixed onboard vision sensor that provides the relative distance and bearing angle is subject to limited range and angle of view due to limited sensing capability. The constraint resulting from collision avoidance is also taken into account for safe operations of the formation system. Furthermore, the preselected specifications on transient and steady-state performance are provided by considering the time-varying and asymmetric constraint requirements on formation tracking errors for each robot. To address the constraint problems, we incorporate a novel barrier Lyapunov function into controller design and analysis. Based on the recursive adaptive backstepping procedure and neural-network approximation, we develop a vision-based formation tracking control protocol such that formation tracking errors can converge into a small neighborhood of the origin in finite time while meeting the requirements of visibility and performance constraints. The proposed protocol is decentralized in the sense that the control action on each robot only depends on the local relative information, without the need for explicit network communication. Moreover, the control protocol could extend to an unconstrained multirobot system. Both simulation and experimental results show the effectiveness of the control protocol.

中文翻译:

具有有限视场传感器的非完整多机器人编队系统的自适应有限时间跟踪控制。

本文研究了具有不确定动力学模型和可见性约束的非完整多机器人编队系统的基于视觉的跟踪控制问题。提供有限的距离和方位角的固定式车载视觉传感器由于感测能力有限而受到限制的范围和视角。为避免地层系统的安全运行,还应考虑到避免碰撞产生的约束。此外,通过考虑每个机器人对地层跟踪误差的时变和非对称约束要求,提供了有关瞬态和稳态性能的预选规范。为了解决约束问题,我们将新颖的障碍Lyapunov函数纳入控制器的设计和分析中。基于递归自适应反推过程和神经网络逼近,我们开发了一种基于视觉的编队跟踪控制协议,以使编队跟踪错误可以在有限时间内收敛到原点的一小部分,同时满足可见性和性能约束的要求。在每个机器人上的控制动作仅取决于本地相对信息而无需显式网络通信的意义上,建议的协议是分散的。而且,控制协议可以扩展到无约束的多机器人系统。仿真和实验结果均表明了该控制协议的有效性。我们开发了基于视觉的编队跟踪控制协议,以使编队跟踪错误可以在有限时间内收敛到原点的一小部分,同时满足可见性和性能约束的要求。在每个机器人上的控制动作仅取决于本地相对信息而无需显式网络通信的意义上,建议的协议是分散的。而且,控制协议可以扩展到无约束的多机器人系统。仿真和实验结果均表明了该控制协议的有效性。我们开发了基于视觉的编队跟踪控制协议,以使编队跟踪错误可以在有限时间内收敛到原点的一小部分,同时满足可见性和性能约束的要求。在每个机器人上的控制动作仅取决于本地相对信息而无需显式网络通信的意义上,建议的协议是分散的。而且,控制协议可以扩展到无约束的多机器人系统。仿真和实验结果均表明了该控制协议的有效性。无需明确的网络通信。而且,控制协议可以扩展到无约束的多机器人系统。仿真和实验结果均表明了该控制协议的有效性。无需明确的网络通信。而且,控制协议可以扩展到无约束的多机器人系统。仿真和实验结果均表明了该控制协议的有效性。
更新日期:2021-03-23
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