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20242026
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cs.RO2026

Differentiable Object Pose Connectivity Metrics for Regrasp Sequence Optimization

Liang Qin, Weiwei Wan, Kensuke Harada

Regrasp planning is often required when one pick-and-place cannot transfer an object from an initial pose to a goal pose while maintaining grasp feasibility. The main challenge is…

cs.RO2026

Industrial-Grade Robust Robot Vision for Screw Detection and Removal under Uneven Conditions

Tomoki Ishikura, Genichiro Matsuda, Takuya Kiyokawa +1

As the amount of used home appliances is expected to increase despite the decreasing labor force in Japan, there is a need to automate disassembling processes at recycling plants.…

cs.RO2026

Generalizable task-oriented object grasping through LLM-guided ontology and similarity-based planning

Hao Chen, Takuya Kiyokawa, Weiwei Wan +1

Task-oriented grasping (TOG) is more challenging than simple object grasping because it requires precise identification of object parts and careful selection of grasping areas to e…

cs.RO2026

Affordance-Guided Enveloping Grasp Demonstration Toward Non-destructive Disassembly of Pinch-Infeasible Mating Parts

Masaki Tsutsumi, Takuya Kiyokawa, Gen Sako +1

Robotic disassembly of complex mating components often renders pinch grasping infeasible, necessitating multi-fingered enveloping grasps. However, visual occlusions and geometric c…

cs.RO2026

Designing and Validating a Self-Aligning Tool Changer for Modular Reconfigurable Manipulation Robots

Mahfudz Maskur, Takuya Kiyokawa, Kensuke Harada

Modular reconfigurable robots require reliable mechanisms for automated module exchange, but conventional rigid active couplings often fail due to inevitable positioning and orient…

cs.RO2026

Gait Generation Balancing Joint Load and Mobility for Legged Modular Robots with Easily Detachable Joints

Kennosuke Chihara, Takuya Kiyokawa, Kensuke Harada

While modular robots offer versatility, excessive joint torque during locomotion poses a significant risk of mechanical failure, especially for detachable joints. To address this,…