Chikaha Tsuji
Papers
2
Total Citations
12
H-Index
2
About
Chikaha Tsuji is a leading researcher in intelligent robotics, specializing in general-purpose service robots, imitation learning, and adaptive manipulation. His most impactful work centers on developing systems that enable robots to operate with high generalizability and resilience in unstructured human environments. Tsuji’s seminal paper, "Self-Recovery Prompting," introduces a top-level system for the RoboCup@Home 2023 competition, leveraging foundation models to create a promptable robot capable of autonomously recovering from failures—a critical step toward practical home assistants. This work has garnered 9 citations since 2024. In parallel, his research on "Adaptive Contact-Rich Manipulation" pioneers a few-shot imitation learning framework that integrates force-torque feedback with pre-trained object representations, drastically reducing the need for extensive human demonstrations. This approach, with 3 citations, addresses the sim-to-real gap in contact-rich tasks, enabling robots to adapt to novel environments with minimal data. Tsuji’s contributions are notable for bridging high-level task planning and low-level physical interaction, pushing the boundaries of deployable service robotics. His work is essential reading for researchers aiming to build robust, generalist robotic systems.
Research Focus
Key Achievements
Top Papers
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