44 papers
Robust Brachiation on a Life-Sized Dual-Arm Robot Using Waypoint-Guided Reinforcement Learning
Ayumu Iwata, Kento Kawaharazuka, Keita Yoneda +2
Brachiation is a form of locomotion in which primates move primarily using their arms, enabling traversal in environments without footholds. However, this motion requires highly co…
Neural Introspection Gating for Adaptive KV-Cache Reuse in Vision-Language-Action Models
Zhijie Wu, Kento Kawaharazuka, Kei Okada
Vision-Language-Action(VLA) models map camera images and language instructions directly to motor commands through a single autoregressive transformer. In real-time control, they st…
VLAff: Vision-Language-Affordance Model for Unified Actionable Affordances
Jihoon Oh, Kento Kawaharazuka, Kei Okada
Learning manipulation skills from human videos is promising for scalable robot learning. However, the embodiment mismatch between humans and robots makes this challenging. One prom…
Diffusion-Based Body Schema Learning Enabling Abnormal-State Adaptation in Musculoskeletal Robots
Kento Kawaharazuka, Shuhei Ikemoto
Musculoskeletal robots require an internal body schema that remains consistent under a wide range of physical state changes, including abnormalities such as muscle rupture and actu…
TRACT: Temporally Routed Action Chunks with Chronological Phase Authority for Contact-Rich Manipulation
Jiahao Liu, Kento Kawaharazuka, Tasuku Makabe +1
Action chunking shortens the effective decision horizon of robot imitation learning by predicting multiple future actions, while conventional phase conditioning describes the curre…
MDIR: A Task-Manifold Impedance Retargeting Method for Contact-Rich Teleoperation
Liu Jiahao, Kento Kawaharazuka, Tasuku Makabe +1
Fixed Cartesian impedance makes contact-rich teleoperation demonstrations practical, but gains that secure progress and contact support also determine impact and force variability.…