Cameraman robot: Dynamic trajectory tracking with final time constraint using state-time space stochastic approach

Abstract

This paper describes an approach to realize a cameraman robot. Here a robot is given a task to follow a certain trajectory for taking the video of an actor in a designated time. The trajectory is relative to the actor, so that the robot has to take into account the actor's movement. We map the given trajectory to a new one in the state-time space based on the prediction of the actor's pose. We then build a trajectory tracking system using a 3D time-space wavefront potential considering the robot kinematic, trajectory cost, obstacles, and visibility constraints. This potential is then used for generating the robot motion control by using a modified random tree search algorithm with the control law. Simulation results show the effectiveness and feasibility of our approach.