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About

Ricard Bordalba is a leading researcher in the field of robotic motion planning, with a primary focus on trajectory optimization and kinodynamic planning for constrained robotic systems. His work addresses the fundamental challenge of generating feasible, dynamic motions for robots with closed kinematic chains, such as parallel manipulators, collaborative arms, and legged robots. Bordalba’s major contributions include pioneering the use of direct collocation methods to solve trajectory optimization problems while mitigating kinematic errors, and developing randomized kinodynamic RRT planners that effectively handle holonomic constraints and forward singularities. His most cited paper, "Direct Collocation Methods for Trajectory Optimization in Constrained Robotic Systems" (2022), has garnered 42 citations, highlighting its impact on the field. Additionally, his work on singularity-robust LQR controllers and planning dynamic motions that avoid forward singularities has advanced the practical control of parallel robots. With over 98 total citations across his publications, Bordalba’s research is instrumental in enabling safer and more efficient motion planning for complex robotic systems, making him a key figure in modern robotics.