Max Robotics — Global Service Robot Directory + US Certification

About

Baofang Wang is a leading researcher in mobile robotics, with a primary focus on path planning and formation control for car-like robots operating in challenging, unstructured environments. Wang’s most impactful work, "Car-like mobile robot path planning in rough terrain using multi-objective particle swarm optimization algorithm" (2017), has garnered 97 citations, establishing a foundational approach for navigating uneven ground. This contribution is extended in subsequent research that addresses the critical challenge of avoiding danger sources—such as enemy strongholds or explosives—during missions in rough terrain, a problem of high practical relevance for battlefield and rescue operations. Wang has also advanced multi-robot coordination, proposing a dynamics controller design method for formation control that accounts for time-varying parameters and rugged environments, moving beyond traditional kinematics-only approaches. Additionally, Wang’s work on fuzzy cross-coupling controllers for Cartesian robots addresses pose accuracy issues caused by mechanical inertia and load disturbances. Through these contributions, Wang has significantly improved the safety and reliability of autonomous ground vehicles in hazardous, real-world settings, making a lasting impact on the field of field robotics.