# Unleashing Humanoid Reaching Potential via Real-world-Ready Skill Space

arXiv: https://arxiv.org/abs/2505.10918 · HTML: https://mlsanity.com/paper/2505.10918/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 May 2025.

## Built on by (most cited first, 14 of 14)

- [OmniRetarget: Interaction-Preserving Data Generation for Humanoid Whole-Body Loco-Manipulation and Scene Interaction](https://mlsanity.com/paper/2509.26633/) (2025)
- [WholeBodyVLA: Towards Unified Latent VLA for Whole-Body Loco-Manipulation Control](https://mlsanity.com/paper/2512.11047/) (2025)
- [PhysHSI: Towards a Real-World Generalizable and Natural Humanoid-Scene Interaction System](https://mlsanity.com/paper/2510.11072/) (2025)
- [DreamControl: Human-Inspired Whole-Body Humanoid Control for Scene Interaction via Guided Diffusion](https://mlsanity.com/paper/2509.14353/) (2025)
- [DemoHLM: From One Demonstration to Generalizable Humanoid Loco-Manipulation](https://mlsanity.com/paper/2510.11258/) (2025)
- [Humanoid-GPT: Scaling Data and Structure for Zero-Shot Motion Tracking](https://mlsanity.com/paper/2606.03985/) (2026)
- [InterReal: A Unified Physics-Based Imitation Framework for Learning Human-Object Interaction Skills](https://mlsanity.com/paper/2603.07516/) (2026)
- [TrajBooster: Boosting Humanoid Whole-Body Manipulation via Trajectory-Centric Learning](https://mlsanity.com/paper/2509.11839/) (2025)
- [PhyGile: Physics-Prefix Guided Motion Generation for Agile General Humanoid Motion Tracking](https://mlsanity.com/paper/2603.19305/) (2026)
- [HANDOFF: Humanoid Agentic Task-Space Whole-Body Control via Distilled Complementary Teachers](https://mlsanity.com/paper/2606.06493/) (2026)
- [HAFO: A Force-Adaptive Control Framework for Humanoid Robots in Intense Interaction Environments](https://mlsanity.com/paper/2511.20275/) (2025)
- [HERO: Learning Humanoid End-Effector Control for Visual Whole-Body Open-Vocabulary Object Grasping](https://mlsanity.com/paper/2602.16705/) (2026)
- [HAF: Adapting Generalist VLAs to Humanoid Whole-Body Loco-manipulation via Hierarchical Action Flow and Spectral Latent RL](https://mlsanity.com/paper/2608.16837/) (2026)
- [Switch-JustDance: Benchmarking Whole Body Motion Tracking Controllers Using a Commercial Console Game](https://mlsanity.com/paper/2511.17925/) (2025)

## Abstract (arXiv)

Humans possess a large reachable space in the 3D world, enabling interaction with objects at varying heights and distances. However, realizing such large-space reaching on humanoids is a complex whole-body control problem and requires the robot to master diverse skills simultaneously-including base positioning and reorientation, height and body posture adjustments, and end-effector pose control. Learning from scratch often leads to optimization difficulty and poor sim2real transferability. To address this challenge, we propose Real-world-Ready Skill Space (R2S2). Our approach begins with a carefully designed skill library consisting of real-world-ready primitive skills. We ensure optimal performance and robust sim2real transfer through individual skill tuning and sim2real evaluation. These skills are then ensembled into a unified latent space, serving as a structured prior that helps task execution in an efficient and sim2real transferable manner. A high-level planner, trained to sample skills from this space, enables the robot to accomplish real-world goal-reaching tasks. We demonstrate zero-shot sim2real transfer and validate R2S2 in multiple challenging goal-reaching scenarios.