Toshisada Mariyama

About

Toshisada Mariyama is a leading roboticist whose research lies at the intersection of manipulation, soft robotics, and intelligent motion planning. His work is defined by a dual focus: developing novel hardware for dexterous manipulation and creating learning-based algorithms for autonomous control. Mariyama has made major contributions to the manipulation of flexible flat cables (FFCs)—a critical, labor-intensive task in electronics manufacturing—by designing a multi-modal gripper with dexterous tips, active nails, and a reconfigurable suction cup module (2022, 8 citations). He also pioneered a parallel-jaw gripper with soft, rolling fingertips for fine FFC manipulation (2021, 17 citations) and introduced a reconfigurable, anthropomorphic robot hand capable of both power grasping and interdigitated precision tasks (2021, 14 citations). On the algorithmic side, he developed a reinforcement learning framework for trajectory optimization under unknown dynamics (2019, 31 citations) and a fast multi-robot motion planner that uses imitation learning to approximate mixed-integer programs (2021, 9 citations). His innovative kirigami-based grippers—soft, multi-layer, and sensorized—enable delicate yet robust grasping and single-grasp object identification (2024, 6 citations). With over 100 total citations and a portfolio spanning hardware and software, Mariyama is shaping the future of autonomous manipulation in manufacturing and service robotics.

Research Focus

Key Achievements

Top Papers

1. 1
   Trajectory Optimization for Unknown Constrained Systems using Reinforcement Learning

   31 citations · 2019
2. 2
   A Locally-Adaptive, Parallel-Jaw Gripper with Clamping and Rolling Capable, Soft Fingertips for Fine Manipulation of Flexible Flat Cables

   17 citations · 2021
3. 3
   A Dexterous, Reconfigurable, Adaptive Robot Hand Combining Anthropomorphic and Interdigitated Configurations

   14 citations · 2021
4. 4
   Fast Multi-Robot Motion Planning via Imitation Learning of Mixed-Integer Programs

   9 citations · 2021
5. 5
   On Robotic Manipulation of Flexible Flat Cables: Employing a Multi-Modal Gripper with Dexterous Tips, Active Nails, and a Reconfigurable Suction Cup Module

   8 citations · 2022
6. 6
   Soft, Multi-Layer, Disposable, Kirigami Based Robotic Grippers: On Handling of Delicate, Contaminated, and Everyday Objects

   8 citations · 2022
7. 7
   Multi-Layer, Sensorized Kirigami Grippers for Delicate Yet Robust Robot Grasping and Single-Grasp Object Identification

   6 citations · 2024
8. 8
   Combining Programming by Demonstration with Path Optimization and Local Replanning to Facilitate the Execution of Assembly Tasks

   5 citations · 2020
9. 9
   Deep Reactive Planning in Dynamic Environments

   5 citations · 2020
10. 10
    A Soft, Multi-Layer, Kirigami Inspired Robotic Gripper with a Compact, Compression-Based Actuation System

    4 citations · 2023

Key Collaborators

Contact & Links