[Submitted on 3 Nov 2026]
Title:Contact-Implicit Whole-Body Trajectory Optimization for Dynamic Humanoid Locomotion on Parameterizable Uneven Terrain
View a PDF of the paper titled Contact-Implicit Whole-Body Trajectory Optimization for Dynamic Humanoid Locomotion on Parameterizable Uneven Terrain, by Roberto Mauceri and 4 other authors
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Abstract:This letter presents a trajectory planner for humanoid robots to perform dynamic motions on complex, parameterizable terrains using a contact-implicit whole-body optimization framework. The planner generates feasible movements without predefined contact sequences, considering the robot's full dynamics and kinematics. To plan bipedal locomotion on steps, ramps, and other terrains, we propose a mathematical model to approximate ground geometry with a smooth surface. The rigid interaction between the robot and the ground is modeled via novel contact constraints, extending the domain of applicability from flat and horizontal surfaces to any arbitrary smooth surface. Effectiveness is demonstrated using nonlinear programming to plan motions on various terrain topologies. We also explore dynamic trajectory generation by embedding high-level requirements in the cost function and the initial guess. Preliminary feasibility tests were conducted over non-coplanar terrains, both in simulation and on the real robot ErgoCub.
Comments: Author-corrected version of the article published in IEEE Robotics and Automation Letters, vol. 10, no. 11, pp. 11674-11681, November 2025. Typos corrected in Eqs. (7)-(8), with minor textual clarifications. Implementation and results unchanged
Subjects:
Robotics (cs.RO)
Cite as: arXiv:2611.05585 [cs.RO]
(or arXiv:2611.05585v1 [cs.RO] for this version)
https://doi.org/10.48550/arXiv.2611.05585
arXiv-issued DOI via DataCite (pending registration)
Journal reference: IEEE Robotics and Automation Letters, vol. 10, no. 11, pp. 11674-11681, November 2025
Related DOI:
https://doi.org/10.1109/LRA.2025.3614066
DOI(s) linking to related resources
Submission history
From: Roberto Mauceri [view email] [v1] Tue, 3 Nov 2026 20:17:00 UTC (6,948 KB)
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