Multi-robot formation control has various applications in domains such as vehicle troops, platoons, payload transportation, and surveillance. Maintaining formation in a vehicle platoon requires designing a suitable control scheme that can tackle external disturbances and uncertain system parameters while maintaining a predefined safe distance between the robots. A crucial challenge in this context is dealing with the unknown/uncertain friction forces between wheels and the ground, which vary with changes in road surface, wear in tires, and speed of the vehicle. Although state-of-the-art adaptive controllers can handle a priori bounded uncertainties, they struggle with accurately modeling and identifying frictional forces, which are often state-dependent and cannot be a priori bounded. This thesis proposes a new adaptive sliding mode controller for wheeled mobile robot-based vehicle platoons that can handle the unknown and complex behavior of frictional forces without prior knowledge of their parameters and structures. The controller uses the adaptive sliding mode control techniques to regulate the platoon's speed and maintain a predefined inter-robot distance, even in the presence of external disturbances and uncertain system parameters. This approach involves a two-stage process: first, the kinematic controller calculates the desired velocities based on the desired trajectory; and second, the dynamics model generates the commands to achieve the desired motion. By separating the kinematics and dynamics of the robot, this approach can simplify the control problem and allow for more efficient and robust control of the wheeled mobile robot.

翻译：多机器人编队控制在车辆编队、队列、载荷运输及监控等领域具有广泛应用。维持车辆队列的编队需要设计合适的控制方案，既能处理外部扰动和不确定的系统参数，又能保持机器人之间预定义的安全距离。此背景下的关键挑战在于处理车轮与地面之间未知/不确定的摩擦力，该摩擦力随路面变化、轮胎磨损及车速改变而波动。尽管现有自适应控制器能够处理先验有界的不确定性，但在准确建模与辨识摩擦力（通常具有状态依赖性且无法先验有界）方面仍存在困难。本文针对基于轮式移动机器人的车辆队列，提出了一种新型自适应滑模控制器，可在无需预知摩擦参数及结构信息的情况下处理其未知复杂行为。该控制器采用自适应滑模控制技术调节队列速度并维持预定义的机器人间距离，即便存在外部扰动和不确定的系统参数时依然有效。该方法包含两阶段过程：首先，运动学控制器根据期望轨迹计算出期望速度；其次，动力学模型生成指令以实现期望运动。通过分离机器人的运动学与动力学模型，该方法可简化控制问题，并实现轮式移动机器人更高效、鲁棒的控制。