Max Robotics — Global Service Robot Directory + US Certification

About

Francisco Geu Flores is a researcher whose work sits at the intersection of robotics, motion planning, and human-robot interaction, with a particular focus on optimizing the performance and safety of dynamic systems. His key contributions lie in developing advanced algorithms for time-optimal path planning, where he has addressed complex constraints such as friction, power limitations, and actuator forces. Notably, his 2012 paper on "Time-Optimal Path Planning Along Specified Trajectories" and his 2011 work extending classical methods to include friction and power constraints have each garnered 11 citations, demonstrating their foundational impact in the field. Flores has also made significant strides in motion cueing for ride simulations, as seen in his 2015 paper on "Optimal Motion Cueing Algorithm Selection and Parameter Tuning for Sickness-Free Robocoaster Ride Simulations," which tackles the critical challenge of minimizing motion sickness in virtual environments. Additionally, his 2018 generalization of the Virtual Redundant Axis Method to multiple serial-robot singularities showcases his ability to address practical robotics limitations. Through this body of work, Flores has established himself as a thoughtful engineer bridging theoretical optimization with real-world applications in robotics and simulation.