Matthew Ishige
Papers
6
Total Citations
73
H-Index
4
About
Matthew Ishige is a robotics researcher whose work lies at the intersection of soft robotics, bio-inspired control, and dexterous manipulation. His primary research areas include developing controllers for soft-bodied robots using central pattern generators and reinforcement learning, as well as advancing tactile sensing for robotic manipulation tasks. Ishige’s most impactful contribution is his work on caterpillar-like soft robots, where he pioneered the use of a central pattern generator-based controller combined with reinforcement learning to achieve diverse behaviors in a single soft body—a paper that has garnered 42 citations. He has also made significant strides in industrial automation through his work on blind bin picking of small screws using compliant robotic fingers and tactile feedback (11 citations), and in developing oscillator-based gait controllers for string-form soft robots (9 citations). His more recent work explores neuromorphic control through echo state networks for soft actuators and in-hand object counting using tactile sensor arrays. Ishige’s research demonstrates a unique ability to bridge biological principles with practical robotic applications, addressing fundamental challenges in both soft robotics and precision manipulation.
Research Focus
Key Achievements
Top Papers
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- 4Echo State Network for Soft Actuator Control7 citations · 2022
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