진학프로석·박사 채용 접수 플랫폼

The integration of task and motion planning is considered one the most important problems in robotics nowadays. 

Robots have sizes, heading, and velocity, and their motion can often be described only according to non-linear differential equations. 

The dynamics of movements, existing obstacles and many waypoints to visit are only some of the challenges to face. In real-world problems, we often have additional constraints like inspecting areas of interest in some certain order, while still minimizing the time for the travel. 

The trickiest part is to solve the hard combinatorial discrete tasks like the generalized and clustered TSPs, and - at the same time - providing valid trajectories for the robot. We extend a framework in which a motion tree is steadily grown, and abstractions to discrete planning problems are used as a heuristic guidance for the on-going solution process to eventually visit all waypoints. 

In case of inspection, we generate the waypoints fully automatically.