Towards safe robot-human collaboration systems using human pose detection

This paper proposes a human detection-based cognitive system for robots to work in human-existing environment and keep the safety of humans. An integrated system is implemented with perception, recognition, reasoning, decision-making, and action. Without using any traditional safety cages, a vision-based detection system is implemented for robots to monitor the environment and to detect humans. Subsequently, reasoning and decision making enables robots to evaluate the current safety-related situation for humans and provide corresponding safety signals. The decision making is based on maximizing the productivity of the robot in the manipulation process and keep the safety of humans in the environment. The system is implemented with a Baxter humanoid robot and a PowerBot mobile robot. Practical experiments and simulation experiments are carried out to validate our design.