# CEER: Compliant End-Effector and Root Control as a Unified Interface for Hierarchical Humanoid Loco-Manipulation

arXiv: https://arxiv.org/abs/2605.19981 · HTML: https://mlsanity.com/paper/2605.19981/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 May 2026.

## Built on by (most cited first, 3 of 3)

- [CHOREO: Every Humanoid Skill as a Trajectory](https://mlsanity.com/paper/2609.22274/) (2026)
- [FRAMES: Failure Recovery And Monitoring of Embodied Skills for Humanoid Loco-Manipulation](https://mlsanity.com/paper/2609.22538/) (2026)
- [CoDance: Learning Reactive and Compliant Human-Humanoid Interaction from Video](https://mlsanity.com/paper/2610.05324/) (2026)

## Abstract (arXiv)

Humanoid robots have achieved impressive locomotion performance, yet contact-rich and long-horizon manipulation remains a major bottleneck. Manipulation is inherently contact-rich and demands compliant whole-body control for stable interaction, while its diversity and long-horizon nature favor modular, planner-compatible interfaces over joint-space tracking. We propose CEER, a compliant end-effector-root (EE-root) control abstraction for modular humanoid loco-manipulation within a hierarchical planning framework. CEER enables compliance-aware whole-body control in an interpretable task space defined by root motion commands and end-effector pose targets, and supports plug-and-play integration with heterogeneous high-level planners. A teacher-student framework is adopted to distill a general motion-tracking controller into a low-level policy that consumes only EE-root commands. We further construct a hierarchical system that integrates heterogeneous planners and task modules through the EE-root interface, enabling diverse manipulation tasks without retraining the underlying whole-body policy. Experiments in simulation and on hardware demonstrate 3.3 cm end-effector tracking accuracy with substantially reduced jerk compared to baselines, stable contact-rich manipulation under teleoperation, and up to 70% success in simulated single-object loco-manipulation tasks within a room-scale environment. These results indicate that compliant EE-root control provides a practical abstraction for humanoid loco-manipulation, enabling modular and scalable integration of diverse skills.