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This article addresses the problem of cooperative object transportation for multiple underwater vehicle manipulator systems (UVMSs) in a constrained workspace involving static obstacles. We propose a nonlinear model predictive control (NMPC) approach for a team of UVMSs in order to transport an object while avoiding significant constraints and limitations, such as kinematic and representation singularities, obstacles within the workspace, joint limits, and control input saturation. More precisely, by exploiting the coupled dynamics between the robots and the object and using certain load sharing coefficients, we design a predictive controller for each UVMS in order to cooperatively transport the object within the workspace’s feasible region. Moreover, the control scheme adopts load sharing among the UVMSs according to their specific payload capabilities. In addition, the feedback relies on each UVMS’s onboard measurements and no explicit data are exchanged online among the robots, thus reducing the required communication bandwidth. Finally, realistic simulation results conducted in the UwSim dynamic simulator running in robot operating system (ROS) environment as well as real-time experiments employing two small UVMSs and demonstrated the effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

SUMMARY: Cooperative transportation by human and robotic coworkers constitutes a challenging research field that could lead to promising technological achievements. Toward this direction, the present work demonstrates that, under a leader–follower architecture, where the human determines the object's desired trajectory, complex cooperative object manipulation with minimal human effort may be achieved. More specifically, the robot estimates the object's desired motion via a prescribed performance estimation law that drives the estimation error to an arbitrarily small residual set. Subsequently, the motion intention estimation is utilized in the object dynamics to determine the interaction force between the human and the object. Human effort reduction is then achieved via an impedance control scheme that employs the aforementioned estimations. The feedback relies exclusively on the robot's force/torque, position as well as velocity measurements at its end effector, without incorporating any other information on the task. Moreover, an adaptive control scheme is adopted to relax the need for exact knowledge of the object dynamics. Finally, an extension for multiple robotic coworkers is studied and verified via simulation, while extensive experimental results for the single robot case clarify the proposed method and corroborate its efficiency. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, a feedback control strategy that achieves convergence of a multi-agent system to a desired formation configuration is proposed for both the cases of agents with single integrator and nonholonomic unicycle-type kinematics. When inter-agent objectives that specify the desired formation cannot occur simultaneously in the state space the desired formation is infeasible. It is shown that under certain assumptions, formation infeasibility forces the agents’ velocity vectors to a common value at steady state. This provides a connection between formation infeasibility and flocking behavior for the multi-agent system. We finally also obtain an analytic expression of the common velocity vector in the case of formation infeasibility. [Copyright &y& Elsevier]

A distributed swarm aggregation algorithm is developed for a team of multiple kinematic agents. Specifically, each agent is assigned a control law, which is the sum of two elements: a repulsive potential field, which is responsible for the collision avoidance objective, and an attractive potential field, which forces the agents to converge to a configuration where they are close to each other. Furthermore, the attractive potential. field forces the agents that are initially located within the sensing radius of an agent to remain within this area for all time. In this way, the connectivity properties of the initially formed communication graph are rendered invariant for the trajectories of the closed-loop system. It is shown that under the proposed control law, agents converge to a configuration where each agent is located at a bounded distance from each of its neighbors. The results are also extended to the case of nonholonomic kinematic unicycle-type agents and to the case of dynamic edge addition. In the latter case, we derive a smaller bound in the swarm size than in the static case. [ABSTRACT FROM AUTHOR]

The dynamic equations of motion for a system of multiple mobile manipulators carrying a common deformable object are developed. The derived centralized model is based on Kane's approach to dynamics. The imposed kinematic nonholonomic constraints are included and incorporated into the dynamics. It is pointed out, however, that these kinematic constraints are only necessary, and they only become sufficient to impose nonholonomic motion when accompanied by the dynamic counterparts. Sufficient conditions for avoiding tipping over by the mechanisms are also provided. The whole set of constraint equations is analyzed and useful properties for the set of admissible solutions for the ground reaction forces are obtained. The deformable object under manipulation is modeled and the simplest approximating grid structure is indicated. © 1998 John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]