This letter presents an adaptive coverage control strategy for multi-agent systems with obstacle avoidance in the presence of actuator faults and time-varying uncertainties. The strategy is based on a leader-follower approach. Assuming that the motion of the leader is given, one distributes the followers within the leader's obstacle-free sensing range so that collisions with obstacles can be avoided. An optimized distribution is achieved through the Centroidal Voronoi Tessellation (CVT) and a function approximation technique based immersion and invariance (FATII) coverage controller is constructed to realize the CVT. The stability of the FATII coverage controller is established and its validity is tested by simulations.

This paper studies a novel fluid actuated system for a spherical mobile robot. The robot’s mechanism consists of two essential parts: circular pipes to lead spherical moving masses (cores) and an internal driving unit to propel the cores. The spherical shell of the robot is rolled by displacing the cores in the pipes filled with fluid. First, we describe the structure of the robot and derive its nonlinear dynamics using the D’Alembert principle. Next, we model the internal driving unit that actuates the core inside the pipe. The simulated driving unit is studied with respect to three important parameters—the input motor torque, the actuator size, and the fluid properties. The overall model of the robot is then used for analyzing motion patterns in the forward direction. Analytical studies show that the modeled robot can be implemented under the given design specifications.

This letter presents a safe adaptive coverage controller for multi-agent systems with actuator faults and time-varying uncertainties. The centroidal Voronoi tessellation (CVT) is applied to generate an optimal configuration of multi-agent systems for covering an area of interest. As conventional CVT based controller cannot prevent collisions between agents with non-zero size, a control barrier function (CBF) based controller is developed to ensure collision avoidance with a function approximation technique (FAT) based design to deal with system uncertainties. The proposed controller is verified under simulations.