Wolfgang Hoenig

Papers

Total Citations

139

H-Index

About

Wolfgang Hoenig is a leading researcher at the intersection of artificial intelligence and robotics, whose work fundamentally bridges the gap between theoretical multi-agent planning and real-world physical constraints. His primary research areas include Multi-Agent Path Finding (MAPF), motion planning, and autonomous systems. Hoenig’s most impactful contribution is his pioneering work on integrating kinematic constraints into MAPF, as demonstrated in his highly cited 2016 paper (139 citations). While traditional AI-based MAPF solvers could efficiently coordinate hundreds of agents in discretized grids, they assumed instantaneous turns and unrealistic motion. Hoenig’s breakthrough showed how to adapt these powerful algorithms to account for acceleration, velocity limits, and non-holonomic dynamics, making them viable for actual robots. This work has been instrumental in enabling coordinated navigation for warehouse robots, autonomous vehicles, and drone swarms. Beyond this, his research continues to push the boundaries of scalable, safe, and physically feasible multi-agent coordination, earning him recognition as a key figure in modern robotics and AI planning.