It is often desirable for a human to manage multiple robots. Autonomy is required to keep workload within tolerable ranges, and dynamically adapting the type of autonomy may be useful for responding to environment and workload changes. We identify two management styles for managing multiple robots and present results from four experiments that have relevance to dynamic autonomy within these two management styles. These experiments, which involved 80 subjects, suggest that individual and team autonomy benefit from attention management aids, adaptive autonomy, and proper information abstraction.

An autonomous control system designed for a non-holonomic wheeled mobile robot that is programmed to emulate a fixed-wing unmanned air vehicle (UAV) flying at constant altitude is experimentally validated. The overall system is capable of waypoint navigation, threat avoidance, real-time trajectory generation and trajectory tracking. Both the wheeled mobile robot experimental platform and the hierarchical autonomous control software architecture are introduced. Programmed to emulate a fixed-wing UAV flying at constant altitude, a non-holonomic mobile robot is assigned to follow a desired time-parameterised trajectory generated by a real-time trajectory generator to transition through a sequence of targets in the presence of static and popup threats. Hardware results of the autonomous control system where the trajectory tracker applies two velocity controllers accounting for fixed-wing UAV-like input constraints, are compared to simulation results of dynamic controllers that are based on non-smooth backstepping to demonstrate the effectiveness of the overall system.

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Multi-robot cooperation is a typical application of multi-robot system, which has strong potential applications in many special occasions. However, few scholars have considered cooperative optimization transportation from the perspective of optimization. This paper investigates the cooperative transportation optimization problem for multiple mobile robots with kinematically redundant manipulators. First, a discrete-time distributed optimization algorithm with fixed step size is proposed to achieve linear convergence. Second, by introducing a rotation variable into the optimization problem, the joint angular velocity of manipulator and the velocity of moving platform change more smoothly. Third, a virtual leader-follower transport strategy is used in this paper to improve the stability of the multi-robot system. In the physical experiment, the trajectory of each end-effector matches the expected trajectory, and the center trajectory of the transport object almost coincides with the virtual leader trajectory with acceptable error. Moreover, the simulation and physical example are provided to demonstrate the effectiveness of the proposed algorithm.