# Stability Constrained Mobile Manipulation Planning on Rough Terrain

arXiv: https://arxiv.org/abs/2105.04396 · HTML: https://mlsanity.com/paper/2105.04396/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 55 references that are in the map.
- First posted on arXiv 10 May 2021.

## Builds on (most cited first, 2 of 2)

- [A Real-Time Approach for Chance-Constrained Motion Planning with Dynamic Obstacles](https://mlsanity.com/paper/2001.08012/) (2020)
- [Quasi-static Analysis of Planar Sliding Using Friction Patches](https://mlsanity.com/paper/1904.06677/) (2019)

## Abstract (arXiv)

This paper presents a framework that allows online dynamic-stability-constrained optimal trajectory planning of a mobile manipulator robot working on rough terrain. First, the kinematics model of a mobile manipulator robot, and the Zero Moment Point (ZMP) stability measure are presented as theoretical background. Then, a sampling-based quasi-static planning algorithm modified for stability guarantee and traction optimization in continuous dynamic motion is presented along with a mathematical proof. The robot's quasi-static path is then used as an initial guess to warm-start a nonlinear optimal control solver which may otherwise have difficulties finding a solution to the stability-constrained formulation efficiently. The performance and computational efficiency of the framework are demonstrated through an application to a simulated timber harvesting mobile manipulator machine working on varying terrain. The results demonstrate feasibility of online trajectory planning on varying terrain while satisfying the dynamic stability constraint.