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KLEIYN : A Quadruped Robot with an Active Waist for Both Locomotion and Wall Climbing

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arxiv 2507.06562 v2 pith:N6C472UW submitted 2025-07-09 cs.RO

KLEIYN : A Quadruped Robot with an Active Waist for Both Locomotion and Wall Climbing

classification cs.RO
keywords locomotionquadrupedclimbingkleiynlearningrobotswaistbeen
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In recent years, advancements in hardware have enabled quadruped robots to operate with high power and speed, while robust locomotion control using reinforcement learning (RL) has also been realized. As a result, expectations are rising for the automation of tasks such as material transport and exploration in unknown environments. However, autonomous locomotion in rough terrains with significant height variations requires vertical movement, and robots capable of performing such movements stably, along with their control methods, have not yet been fully established. In this study, we developed the quadruped robot KLEIYN, which features a waist joint, and aimed to expand quadruped locomotion by enabling chimney climbing through RL. To facilitate the learning of vertical motion, we introduced Contact-Guided Curriculum Learning (CGCL). As a result, KLEIYN successfully climbed walls ranging from 800 mm to 1000 mm in width at an average speed of 150 mm/s, 50 times faster than conventional robots. Furthermore, we demonstrated that the introduction of a waist joint improves climbing performance, particularly enhancing tracking ability on narrow walls.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Multi-Rate Nonlinear Model Predictive Control for Wall-Supported Bipedal Locomotion of Quadrupedal Robots

    cs.RO 2026-07 unverdicted novelty 6.0

    A two-layer system uses multi-rate NMPC to jointly plan contact points and body trajectories for wall-supported bipedal walking in quadrupeds, showing 2.9 times higher simulation success than heuristic MPC on rough terrain.

  2. WARL: Wrench-Augmented Reinforcement Learning for Task-Agnostic Learning in Legged Robots

    cs.RO 2026-07 conditional novelty 4.0

    Adding a simulated torso wrench during early RL training and gradually removing it lets a quadruped learn six locomotion tasks with a shared reward, yielding a joint-only policy in simulation.