A Terrain-Adaptive epsilon-Constraint MPC for Uneven Terrain Kinodynamic Planning

Otobong Jerome; Geesara Kalathunga; Tiago Nascimento

doi:10.1109/lra.2026.3728313

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arXiv · 2605.21188

A Terrain-Adaptive epsilon-Constraint MPC for Uneven Terrain Kinodynamic Planning

Otobong Jerome·Geesara Kalathunga·Tiago Nascimento

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Abstract

Kinodynamic planning for car-like vehicles on uneven terrain requires simultaneously optimizing competing objectives such as path efficiency and pose stability. This work presents an adaptive epsilon-constraint method integrated into a Model Predictive Control (MPC) framework, where the epsilon bounds are dynamically adjusted based on terrain descriptors to explore the Pareto front in real time. To capture vehicle-terrain dynamics, we develop a semi-parametric model combining analytical vehicle dynamics with a Sparse Gaussian Process (SGP) trained on the same terrain descriptors. The proposed epsilon-MPC is evaluated against MPPI and GAKD baselines, achieving a 94% navigation success rate while reducing maximum orientation deviation by 24% and improving multi-objective trade-off quality by 23%.

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Otobong Jerome, Geesara Kalathunga, Tiago Nascimento. 2026-08-29. A Terrain-Adaptive epsilon-Constraint MPC for Uneven Terrain Kinodynamic Planning. https://doi.org/10.1109/lra.2026.3728313

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