Max Robotics — Global Service Robot Directory + US Certification

About

Maxime Adjigble is a robotics researcher whose work sits at the intersection of robotic manipulation, autonomous grasping, and human-robot collaboration. His research has made significant contributions to the challenge of enabling robots to reliably grasp and manipulate objects in complex, real-world environments — from factory floors to hazardous nuclear facilities. Adjigble's most influential work, "Dynamic Grasp and Trajectory Planning for Moving Objects" (2018, 102 citations), demonstrated how robotic arms can track and grasp objects handed over by human co-workers in real time, a critical capability for safe collaborative robotics. Complementing this, his model-free grasping framework using Local Contact Moment matching (2018, 42 citations) tackled object manipulation without requiring prior training data or physical models — a notable achievement in generalized robot learning. His contributions to nuclear decommissioning robotics (2016, 83 citations) highlight the real-world stakes of his research, helping advance autonomous and teleoperated solutions in one of the world's most demanding environments. Across multiple papers, he has further refined telemanipulation through haptic guidance, singularity-robust kinematics, and belief-space planning. With over 300 cumulative citations, Adjigble's body of work represents a meaningful advance in making robots more capable, adaptable partners for both industry and human collaboration.