# Planning and Execution of Dynamic Whole-Body Locomotion for a Hydraulic Quadruped on Challenging Terrain

arXiv: https://arxiv.org/abs/1904.03695 · HTML: https://mlsanity.com/paper/1904.03695/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Apr 2019.

## Built on by (most cited first, 2 of 2)

- [Controlling the Solo12 Quadruped Robot with Deep Reinforcement Learning](https://mlsanity.com/paper/2309.16683/) (2023)
- [Learning Quadrupedal Locomotion for a Heavy Hydraulic Robot Using an Actuator Model](https://mlsanity.com/paper/2601.11143/) (2026)

## Abstract (arXiv)

We present a framework for dynamic quadrupedal locomotion over challenging terrain, where the choice of appropriate footholds is crucial for the success of the behaviour. We build a model of the environment on-line and on-board using an efficient occupancy grid representation. We use Any-time-Repairing A* (ARA*) to search over a tree of possible actions, choose a rough body path and select the locally-best footholds accordingly. We run a n-step lookahead optimization of the body trajectory using a dynamic stability metric, the Zero Moment Point (ZMP), that generates natural dynamic whole-body motions. A combination of floating-base inverse dynamics and virtual model control accurately executes the desired motions on an actively compliant system. Experimental trials show that this framework allows us to traverse terrains at nearly 6 times the speed of our previous work, evaluated over the same set of trials.