Local and Global Sensors for Collision Avoidance

Abstract

Implementation of safe and efficient human robot collaboration for agile production cells with heavy-duty industrial robots, having large stopping distances and large self-occlusion areas, is a challenging task. Collision avoidance is the main functionality required to realize this task. In fact, it requires accurate estimation of shortest distance between known (robot) and unknown (human or anything else) objects in a large area. This work proposes a selective fusion of global and local sensors, representing a large range 360° LiDAR and a small range RGB camera respectively, in the context of dynamic speed and separation monitoring. Safety functionality has been evaluated for collision detection between unknown dynamic object to manipulator joints. The system yields 29-40% efficiency compared to fenced system. Heavy-duty industrial robot and a controlled linear axis dummy is used for evaluating different robot and scenario configurations. Results suggest higher efficiency and safety when using local and global setup.