Assembly-Oriented Task Sequence Planning for a Dual-Arm Robot

One of the goals for the deployment of dual-arm robots is to imitate and replace human workers to complete manufacturing tasks. Moreover, especially in scenarios where workpieces are randomly scattered on the workbench, endowing a robotic system with a capacity of scheduling task sequences will undoubtedly expand its application prospects and improve the autonomy. For that purpose, this paper proposes a dual-arm robot task sequence planning approach based on environmental constraints and causal reasoning among tasks. In this work, the Monte Carlo method, the Gaussian Mixture Model and the binary functions are adopted to evaluate the constraints from the robots. Meanwhile, constraints from workpieces are addressed with a geometric method combined with its semantic relations. In addition to the environmental constraints, which consist of constraints from the robot and workpieces, the causal relations among tasks are considered. Finally, all the above information is exploited to construct a graphical structure for task sequence planning, where workpieces are regarded as vertices and their semantic relations are edges with attributes. The effectiveness of the approach is demonstrated using various simulation experiments within different scene layouts rather than using several specified tasks.