arXiv Machine Learning By Siheng Zhao, Yuanhang Zhang, Ziqi Lu, Pieter Abbeel, Rocky Duan, Koushil Sreenath, Yue Wang, C. Karen Liu, Guanya Shi

LadderMan: Learning Humanoid Perceptive Ladder Climbing

Read the original on arXiv Machine Learning →

arXiv:2606. 05873v1 Announce Type: cross Abstract: Humanoid robots hold great promise for operating in human-centered environments, yet ladder climbing remains one of the most challenging tasks due to sparse footholds and handholds, complex whole-body coordination, and sensitivity to perception and control errors.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

arXiv AI
Jul 16

Agile perceptive multi-skill locomotion for quadrupedal robots in the wild

arXiv:2607. 13579v1 Announce Type: cross Abstract: Enabling quadrupedal robots to traverse complex terrains-from rugged outdoor environments to urban landscapes-requires seamless integration of multiple motor skills, smooth transitions between gaits, and high-speed perceptive locomotion using only onboard sensors.

By Jun-Gill Kang, Jaehyun Park, Tae-Gyu Song, Joon-Ha Kim, Seungwoo Hong, Hae-Won Park
arXiv Machine Learning
1d ago

AdaptManip: Learning Adaptive Whole-Body Object Lifting and Delivery with Online Recurrent State Estimation

AdaptManip is a fully autonomous framework that enables humanoid robots to navigate, lift, and deliver objects without human demonstrations. It combines a recurrent state estimator for real‑time object tracking, a whole‑body locomotion policy with residual manipulation control, and a LiDAR‑based global position estimator. Trained entirely in simulation with reinforcement learning, the system achieves zero‑shot deployment on real hardware, outperforming imitation‑learning baselines in adaptability and success rate.

By Morgan Byrd, Donghoon Baek, Kartik Garg, Hyunyoung Jung, Daesol Cho, Maks Sorokin, Robert Wright, Sehoon Ha
arXiv AI
Jul 9

Behavior Foundations for Quadruped Robots: ABot-C0 Technical Report

arXiv:2607. 07370v1 Announce Type: cross Abstract: In embodied intelligence systems, the motion controller serves as the critical bridge between semantic reasoning and physical execution.

By Xufeng Zhao, Fuzhi Yang, Jianhui Chen, Li Gao, Zhang Meng, Jie Gao, Yao Zheng, Wenyu Liu, Menglin Yang, Minqi Gu, Yaru Zhao, Honglin Han, Shihui Su, Zixiao Tang, Liu Liu, Mu Xu, Yang Cai, Wenbin Tang
arXiv Computer Vision
Aug 25

TONAV: Task-Oriented Navigation and Action-Velocity Chunk Learning for Articulated Object Quadrupedal Mobile Manipulation

arXiv:2608.22296v1 Announce Type: cross Abstract: Quadruped mobile manipulation requires two tightly coupled capabilities: reaching manipulation-ready configurations and maintaining stable contact th...

By Haoran Lin, Mingyu Yang, Pengfei Qi, Kehan Chen, Qiang Diao, Liangji Zeng, Wenrui Chen, Yaonan Wang, Kailun Yang