# Simultaneous Contact-Rich Grasping and Locomotion via Distributed Optimization Enabling Free-Climbing for Multi-Limbed Robots

arXiv: https://arxiv.org/abs/2207.01418 · HTML: https://mlsanity.com/paper/2207.01418/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 30 references that are in the map.
- First posted on arXiv 4 Jul 2022.

## Builds on (most cited first, 11 of 11)

- [Warm Start of Mixed-Integer Programs for Model Predictive Control of Hybrid Systems](https://mlsanity.com/paper/1910.08251/) (2019)
- [Circus ANYmal: A Quadruped Learning Dexterous Manipulation with Its Limbs](https://mlsanity.com/paper/2011.08811/) (2020)
- [Contact-timing and Trajectory Optimization for 3D Jumping on Quadruped Robots](https://mlsanity.com/paper/2110.06764/) (2021)
- [Simultaneous Contact, Gait and Motion Planning for Robust Multi-Legged Locomotion via Mixed-Integer Convex Optimization](https://mlsanity.com/paper/1904.04595/) (2019)
- [Robust Pivoting: Exploiting Frictional Stability Using Bilevel Optimization](https://mlsanity.com/paper/2203.11412/) (2022)
- [Real-Time Multi-Contact Model Predictive Control via ADMM](https://mlsanity.com/paper/2109.07076/) (2021)
- [Risk-Aware Motion Planning for a Limbed Robot with Stochastic Gripping Forces Using Nonlinear Programming](https://mlsanity.com/paper/2006.02656/) (2020)
- [PYROBOCOP : Python-based Robotic Control & Optimization Package for Manipulation and Collision Avoidance](https://mlsanity.com/paper/2106.03220/) (2021)
- [Accelerated ADMM based Trajectory Optimization for Legged Locomotion with Coupled Rigid Body Dynamics](https://mlsanity.com/paper/2003.08019/) (2020)
- [Chance-Constrained Optimization in Contact-Rich Systems for Robust Manipulation](https://mlsanity.com/paper/2203.02616/) (2022)
- [An Under-Actuated Whippletree Mechanism Gripper based on Multi-Objective Design Optimization with Auto-Tuned Weights](https://mlsanity.com/paper/2110.00083/) (2021)

## Built on by (most cited first, 5 of 5)

- [A Survey of Optimization-based Task and Motion Planning: From Classical To Learning Approaches](https://mlsanity.com/paper/2404.02817/) (2024)
- [Robust Pivoting Manipulation using Contact Implicit Bilevel Optimization](https://mlsanity.com/paper/2303.08965/) (2023)
- [Is Linear Feedback on Smoothed Dynamics Sufficient for Stabilizing Contact-Rich Plans?](https://mlsanity.com/paper/2411.06542/) (2024)
- [Hierarchical Contact-Rich Trajectory Optimization for Multi-Modal Manipulation using Tight Convex Relaxations](https://mlsanity.com/paper/2503.07963/) (2025)
- [Learning Pivoting Manipulation with Force and Vision Feedback Using Optimization-based Demonstrations](https://mlsanity.com/paper/2508.01082/) (2025)

## Abstract (arXiv)

While motion planning of locomotion for legged robots has shown great success, motion planning for legged robots with dexterous multi-finger grasping is not mature yet. We present an efficient motion planning framework for simultaneously solving locomotion (e.g., centroidal dynamics), grasping (e.g., patch contact), and contact (e.g., gait) problems. To accelerate the planning process, we propose distributed optimization frameworks based on Alternating Direction Methods of Multipliers (ADMM) to solve the original large-scale Mixed-Integer NonLinear Programming (MINLP). The resulting frameworks use Mixed-Integer Quadratic Programming (MIQP) to solve contact and NonLinear Programming (NLP) to solve nonlinear dynamics, which are more computationally tractable and less sensitive to parameters. Also, we explicitly enforce patch contact constraints from limit surfaces with micro-spine grippers. We demonstrate our proposed framework in the hardware experiments, showing that the multi-limbed robot is able to realize various motions including free-climbing at a slope angle 45deg with a much shorter planning time.