Toshimitsu Tsuboi

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About

Toshimitsu Tsuboi is a leading roboticist whose research bridges whole-body control, motion planning, and dexterous manipulation. His most influential work, "Whole-body cooperative force control for a two-armed and two-wheeled mobile robot using Generalized Inverse Dynamics and Idealized Joint Units" (2010, 36 citations), introduced a unified framework that coordinates all joint forces to simultaneously achieve position, velocity, acceleration, force, and impedance objectives—enabling mobile manipulators to perform complex, multi-contact tasks with unprecedented stability. Building on this foundation, Tsuboi has advanced motion planning with his 2020 paper on "3D-CNN Based Heuristic Guided Task-Space Planner for Faster Motion Planning" (26 citations), which integrates deep learning with sampling-based planners to dramatically reduce computation time for collision-free paths in cluttered environments. His work on adaptive grasping, notably "Theoretical Derivation and Realization of Adaptive Grasping Based on Rotational Incipient Slip Detection" (2020, 15 citations), provides a rigorous theoretical basis for controlling grasp force on unknown objects by detecting rotational slip before failure—a critical step toward truly autonomous manipulation. Tsuboi’s contributions are widely cited in robotics, control, and AI communities, and his research continues to shape how robots interact safely and efficiently with the physical world.