Human-robot collaboration while sharing production activities in dynamic environment: SPADER system

- A safe trajectory generation in dynamic environments.
- The evaluation of human motion.
- A strategy adapted for industrial robot already installed in the production line.
- The system is based on neural network in order to create the waypoints required for dynamic obstacles avoidance.
- Finally, a quintic polynomial function is used in order to smooth motion and least-square is computed for an optimal trajectory.

Interactive robot doing collaborative work in hybrid work cell need adaptive trajectory planning strategy. Indeed, systems must be able to generate their own trajectories without colliding with dynamic obstacles like humans and assembly components moving inside the robot workspace. The aim of this paper is to improve collision-free motion planning in dynamic environment in order to insure human safety during collaborative tasks such as sharing production activities between human and robot. Our system proposes a trajectory generating method for an industrial manipulator in a shared workspace. A neural network using a supervised learning is applied to create the waypoints required for dynamic obstacles avoidance. These points are linked with a quintic polynomial function for smooth motion which is optimized using least-square to compute an optimal trajectory. Moreover, the evaluation of human motion forms has been taken into consideration in the proposed strategy. According to the results, the proposed approach is an effective solution for trajectories generation in a dynamic environment like a hybrid workspace.