2 research outputs found
Robust Decentralized Abstractions for Multiple Mobile Manipulators
This paper addresses the problem of decentralized abstractions for multiple
mobile manipulators with 2nd order dynamics. In particular, we propose
decentralized controllers for the navigation of each agent among predefined
regions of interest in the workspace, while guaranteeing at the same time
inter-agent collision avoidance and connectivity maintenance for a subset of
initially connected agents. In that way, the motion of the coupled multi-agent
system is abstracted into multiple finite transition systems for each agent,
which are then suitable for the application of temporal logic-based high level
plans. The proposed methodology is decentralized, since each agent uses local
information based on limited sensing capabilities. Finally, simulation studies
verify the validity of the approach.Comment: Accepted for publication in the IEEE Conference on Decision and
Control, Melbourne, Australia, 201
Adaptive Robot Navigation with Collision Avoidance subject to 2nd-order Uncertain Dynamics
This paper considers the problem of robot motion planning in a workspace with
obstacles for systems with uncertain 2nd-order dynamics. In particular, we
combine closed form potential-based feedback controllers with adaptive control
techniques to guarantee the collision-free robot navigation to a predefined
goal while compensating for the dynamic model uncertainties. We base our
findings on sphere world-based configuration spaces, but extend our results to
arbitrary star-shaped environments by using previous results on configuration
space transformations. Moreover, we propose an algorithm for extending the
control scheme to decentralized multi-robot systems. Finally, extensive
simulation results verify the theoretical findings