Semantic coupling of path planning and a primitive action of a task plan for the simulation of manipulation tasks in a virtual 3D environment. (February 2022)

• Record Type: Journal Article
• Authors: Zhao, Yingshen; Fillatreau, Philippe; Elmhadhbi, Linda; Karray, Mohamed Hedi; Archimede, Bernard
• Is Part Of: Robotics and computer-integrated manufacturing. Volume 73(2022)
• Publication Date: 2022-02
• Subjects: Path planning -- Joint task and path planning -- Ontology -- Task-oriented knowledge -- Knowledge reasoning; Robots, Industrial -- Periodicals; Computer integrated manufacturing systems -- Periodicals; Robotics -- Periodicals; Robots industriels -- Périodiques; Productique -- Périodiques; Robotique -- Périodiques; 670.285
• DOI: 10.1016/j.rcim.2021.102255
• Languages: English
• ISSNs: 0736-5845

Abstract

Highlights: Simulation of complex manipulation tasks under strong geometric constraints. Use ontologies to model the environment, by involving high abstraction level data. Use ontologies reasoning capacities to define task-related geometric constraints on path planning queries. Improvement of motion planning through better semantic control. Abstract: This work deals with the simulation of complex manipulation tasks in virtual environments. Validating such complex tasks, possibly to be performed under strong geometric constraints, requires considering task and path planning jointly. The contribution of this work focuses on using task-related information at the path planning level. We propose an ontology-based approach to a) model the 3D environment where the simulated task is executed, based on an original multi-level environment model involving higher abstraction level data than the purely geometric models traditionally used, and b) automatically define path planning queries for the primitive actions of a task plan, together with task-related geometric constraints on these queries. This approach allows the improvement of the state of the art from two points of view. First, our joint task and path planning approach allows the improvement of path planning through better semantic control of the path planning process. Second, if compared to hard-coded geometric constraints, the proposed ontology-based approach introduces a more flexible way of defining geometric constraints through an inference process, and can be adapted to different applications of manipulation tasks.