Whole-Body Trajectory Optimization for Robot Multimodal Locomotion

• Published in: 2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids) pp. 651 - 658
• Main Authors: L'Erario, Giuseppe, Nava, Gabriele, Romualdi, Giulio, Bergonti, Fabio, Razza, Valentino, Dafarra, Stefano, Pucci, Daniele
• Format: Conference Proceeding
• Language: English
• Published: IEEE 28-11-2022
• Subjects: Dynamics; Heuristic algorithms; Humanoid robots; Planning; Robot kinematics; Robot motion; Trajectory
• ISSN: 2164-0580
• DOI: 10.1109/Humanoids53995.2022.10000241

The general problem of planning feasible trajectories for multimodal robots is still an open challenge. This paper presents a whole-body trajectory optimisation approach that addresses this challenge by combining methods and tools developed for aerial and legged robots. First, robot models that enable the presented whole-body trajectory optimisation framework are presented. The key model is the so-called robot centroidal momentum, the dynamics of which is directly related to the models of the robot actuation for aerial and terrestrial locomotion. Then, the paper presents how these models can be employed in an optimal control problem to generate either terrestrial or aerial locomotion trajectories with a unified approach. The optimisation problem considers robot kinematics, momentum, thrust forces and their bounds. The overall approach is validated using the multimodal robot iRonCub, a flying humanoid robot that expresses a degree of terrestrial and aerial locomotion. To solve the associated optimal trajectory generation problem, we employ ADAM, a custom-made open-source library that implements a collection of algorithms for calculating rigid-body dynamics using CasADi.