# A Unified MPC Framework for Whole-Body Dynamic Locomotion and Manipulation

arXiv: https://arxiv.org/abs/2103.00946 · HTML: https://mlsanity.com/paper/2103.00946/

## Key facts

- Cited by 38 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Mar 2021.

## Built on by (most cited first, 30 of 38)

- [Advancing Humanoid Locomotion: Mastering Challenging Terrains with Denoising World Model Learning](https://mlsanity.com/paper/2408.14472/) (2024)
- [Articulated Object Interaction in Unknown Scenes with Whole-Body Mobile Manipulation](https://mlsanity.com/paper/2103.10534/) (2021)
- [Learning Force Control for Legged Manipulation](https://mlsanity.com/paper/2405.01402/) (2024)
- [Dexterous Manipulation through Imitation Learning: A Survey](https://mlsanity.com/paper/2504.03515/) (2025)
- [Learning coordinated badminton skills for legged manipulators](https://mlsanity.com/paper/2505.22974/) (2025)
- [N2M2: Learning Navigation for Arbitrary Mobile Manipulation Motions in Unseen and Dynamic Environments](https://mlsanity.com/paper/2206.08737/) (2022)
- [Evaluating model-based planning and planner amortization for continuous control](https://mlsanity.com/paper/2110.03363/) (2021)
- [Bridging the Sim-to-Real Gap for Athletic Loco-Manipulation](https://mlsanity.com/paper/2502.10894/) (2025)
- [Robotic Table Wiping via Reinforcement Learning and Whole-body Trajectory Optimization](https://mlsanity.com/paper/2210.10865/) (2022)
- [A Unified and General Humanoid Whole-Body Controller for Versatile Locomotion](https://mlsanity.com/paper/2502.03206/) (2025)
- [Humanoid Whole-Body Locomotion on Narrow Terrain via Dynamic Balance and Reinforcement Learning](https://mlsanity.com/paper/2502.17219/) (2025)
- [Sim-to-Real Learning for Bipedal Locomotion Under Unsensed Dynamic Loads](https://mlsanity.com/paper/2204.04340/) (2022)
- [Guided Reinforcement Learning for Robust Multi-Contact Loco-Manipulation](https://mlsanity.com/paper/2410.13817/) (2024)
- [Jacta: A Versatile Planner for Learning Dexterous and Whole-body Manipulation](https://mlsanity.com/paper/2408.01258/) (2024)
- [Whole-body End-Effector Pose Tracking](https://mlsanity.com/paper/2409.16048/) (2024)
- [Ego-Vision World Model for Humanoid Contact Planning](https://mlsanity.com/paper/2510.11682/) (2025)
- [Predicting Motion Plans for Articulating Everyday Objects](https://mlsanity.com/paper/2303.01484/) (2023)
- [Dynamic object goal pushing with mobile manipulators through model-free constrained reinforcement learning](https://mlsanity.com/paper/2502.01546/) (2025)
- [HiLMa-Res: A General Hierarchical Framework via Residual RL for Combining Quadrupedal Locomotion and Manipulation](https://mlsanity.com/paper/2407.06584/) (2024)
- [Diffusion-Informed Probabilistic Contact Search for Multi-Finger Manipulation](https://mlsanity.com/paper/2410.00841/) (2024)
- [ZipMPC: Compressed Context-Dependent MPC Cost via Imitation Learning](https://mlsanity.com/paper/2507.13088/) (2025)
- [Bipedalism for Quadrupedal Robots: Versatile Loco-Manipulation through Risk-Adaptive Reinforcement Learning](https://mlsanity.com/paper/2507.20382/) (2025)
- [A Transferable Legged Mobile Manipulation Framework Based on Disturbance Predictive Control](https://mlsanity.com/paper/2203.03391/) (2022)
- [Dynamic Non-Prehensile Object Transport via Model-Predictive Reinforcement Learning](https://mlsanity.com/paper/2412.00086/) (2024)
- [Cost-Matching Model Predictive Control for Efficient Reinforcement Learning in Humanoid Locomotion](https://mlsanity.com/paper/2603.28243/) (2026)
- [Kinematically-Decoupled Impedance Control for Fast Object Visual Servoing and Grasping on Quadruped Manipulators](https://mlsanity.com/paper/2307.04918/) (2023)
- [Opening Articulated Structures in the Real World](https://mlsanity.com/paper/2402.17767/) (2024)
- [Learning Rapid Turning, Aerial Reorientation, and Balancing using Manipulator as a Tail](https://mlsanity.com/paper/2407.10420/) (2024)
- [INTENTION: Inferring Tendencies of Humanoid Robot Motion Through Interactive Intuition and Grounded VLM](https://mlsanity.com/paper/2508.04931/) (2025)
- [Optimal Gait Control for a Tendon-driven Soft Quadruped Robot by Model-based Reinforcement Learning](https://mlsanity.com/paper/2406.07069/) (2024)

## Abstract (arXiv)

In this paper, we propose a whole-body planning framework that unifies dynamic locomotion and manipulation tasks by formulating a single multi-contact optimal control problem. We model the hybrid nature of a generic multi-limbed mobile manipulator as a switched system, and introduce a set of constraints that can encode any pre-defined gait sequence or manipulation schedule in the formulation. Since the system is designed to actively manipulate its environment, the equations of motion are composed by augmenting the robot's centroidal dynamics with the manipulated-object dynamics. This allows us to describe any high-level task in the same cost/constraint function. The resulting planning framework could be solved on the robot's onboard computer in real-time within a model predictive control scheme. This is demonstrated in a set of real hardware experiments done in free-motion, such as base or end-effector pose tracking, and while pushing/pulling a heavy resistive door. Robustness against model mismatches and external disturbances is also verified during these test cases.