# EHC-MM: Embodied Holistic Control for Mobile Manipulation

arXiv: https://arxiv.org/abs/2409.08527 · HTML: https://mlsanity.com/paper/2409.08527/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Sep 2024.

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

- [M4Diffuser: Multi-View Diffusion Policy with Manipulability-Aware Control for Robust Mobile Manipulation](https://mlsanity.com/paper/2509.14980/) (2025)
- [ObstaDiff: Generalizable Diffusion Policy Learning via Obstacle-aware Representations](https://mlsanity.com/paper/2609.10918/) (2026)

## Abstract (arXiv)

Mobile manipulation typically entails the base for mobility, the arm for accurate manipulation, and the camera for perception. The principle of Distant Mobility, Close Grasping(DMCG) is essential for holistic control. We propose Embodied Holistic Control for Mobile Manipulation(EHC-MM) with the embodied function of sig(w): By formulating the DMCG principle as a Quadratic Programming (QP) problem, sig(w) dynamically balances the robot's emphasis between movement and manipulation with the consideration of the robot's state and environment. In addition, we propose the Monitor-Position-Based Servoing (MPBS) with sig(w), enabling the tracking of the target during the operation. This approach enables coordinated control among the robot's base, arm, and camera, enhancing task efficiency. Through extensive simulations and real-world experiments, our approach significantly improves both the success rate and efficiency of mobile manipulation tasks, achieving a 95.6% success rate in real-world scenarios and a 52.8% increase in time efficiency.