Collision-Free Navigation in Human-Following Task Using a Cognitive Robotic System on Differential Drive Vehicles

As human-robot collaboration increases tremendously in real-world applications, a fully autonomous and reliable mobile robot for the collaboration has been a central research topic and investigated extensively in a large number of studies. One of the most pressing issues in such topic is the collision-free navigation that has a moving goal and unknown obstacles under the unstructured environment. In this article, a cognitive robotic system (CRS) is proposed for the robot to navigate itself to the moving target person without obstacle collision. This CRS consists of a cognitive agent, which is created based on the Soar cognitive architecture to reason its current situation and make action decision for the robot to avoid obstacles and reach the target position, and a speed planning module, which is based on dynamic window approach (DWA) to generate appropriate linear and angular velocities for driving the robot's motors. For the implementation of the proposed system, we use a differential drive wheel robot equipped with two ultrawideband (UWB) sensors and a color depth camera as the experimental platform. Finally, to evaluate the performance of our system in actual operating conditions, we conduct experiments with a scenario that includes main tasks: avoiding consecutive unknown obstacles and turning at corner while the robot follows continuously human user along the corridor.