RT Journal Article
T1 Multi-stage warm started optimal motion planning for over-actuated mobile platforms
A1 Paz-Delgado, Gonzalo Jesús
A1 Pérez-del-Pulgar-Mancebo, Carlos Jesús
A1 Azkarate, Martin
A1 Kirchner, Frank
A1 García-Cerezo, Alfonso José
K1 Robótica espacial
K1 Mecatrónica
AB This work presents a computationally lightweight motion planner for over-actuated platforms. For this purpose, a general state-space model for mobile platforms with several kinematic chains is defined, which considers dynamics, nonlinearities and constraints. The proposed motion planner is based on a sequential multi-stage approach that takes advantage of the warm start on each step. Firstly, a globally optimal and smooth 2D/3D trajectory is generated using the Fast Marching Method. This trajectory is fed as a warm start to a sequential linear quadratic regulator that is able to generate an optimal motion plan without constraints for all the platform actuators. Finally, a feasible motion plan is generated considering the constraints defined in the model. In this respect, the sequential linear quadratic regulator is employed again, taking the previously generated unconstrained motion plan as a warm start. The motion planner has been deployed into the Exomars Testing Rover of the European Space Agency. This rover is an Ackermann-capable planetary exploration testbed that is equipped with a robotic arm. Several experiments were carried out demonstrating that the proposed approach speeds up the computation time and increases the success ratio for a martian sample retrieval mission, which can be considered as a representative use case of goal-constrained trajectory generation for an over-actuated mobile platform.
PB Springer
YR 2023
FD 2023
LK https://hdl.handle.net/10630/26403
UL https://hdl.handle.net/10630/26403
LA eng
NO Paz-Delgado, G.J., Pérez-del-Pulgar, C.J., Azkarate, M. et al. Multi-stage warm started optimal motion planning for over-actuated mobile platforms. Intel Serv Robotics (2023). https://doi.org/10.1007/s11370-023-00461-x
NO This work has been partially funded by the EU-H2020 project entitled “Cooperative Robots for Extreme Environments” (CoRob-X) under grant agreement: 101004130.Funding for open access charge: Universidad de Málaga / CBUA”.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 1 mar 2026