Max Robotics — Global Service Robot Directory + US Certification

About

F. Lingelbach is a pioneering researcher in autonomous robotics, with key contributions spanning path planning, mobile manipulation, and decision-making under uncertainty. Their most influential work, "Path planning using probabilistic cell decomposition" (2004), introduced a groundbreaking approach that combines cell decomposition with probabilistic sampling to navigate high-dimensional static configuration spaces. This method, enhanced by lazy evaluation and supervised sampling, has garnered 195 citations, establishing it as a foundational technique in the field. Lingelbach extended this framework to mobile manipulation in a 2005 paper (30 citations), addressing the critical challenge of connecting feasible paths for autonomous robots in complex environments. Beyond path planning, they developed a value iteration algorithm for Partially Observed Markov Decision Process (POMDP) multi-armed bandits (2004, 15 citations), advancing optimal resource allocation in dynamic systems. Their ongoing research on constrained path planning and task-consistent adaptation for mobile manipulators (2005, 9 citations) further demonstrates a commitment to designing versatile service robots for home and office settings. With a career focused on bridging theoretical algorithms and practical robotics, Lingelbach’s work has significantly influenced autonomous navigation and decision-making, inspiring subsequent research in high-dimensional planning and adaptive manipulation.