Simulating complex industrial manipulation tasks (e.g., assembly, disassembly and maintenance tasks) under strong geometric constraints in a virtual environment, requires the joint usage of task and path planning, not only to compute a sequence of primitive actions (i.e., a task plan) at task planning level to identify the order to manipulate different objects (e.g., assembly order), but also to generate and validate motions for each of these primitive actions in a virtual environment by computing valid collision-free paths for these actions at path planning level. Although task and path planning have been respectively welly discussed by artificial intelligence and robotic domain, the link between them still remains an open issue, in particular because path planning for a primitive action often uses purely geometric data. This purely geometric path planning suffers from the classical failures (i.e., high-possibility of failure, high processing time and low path relevance) of automated path planning techniques when dealing with complex geometric models. Thus, it can possibly lead to high computational time of the joint task and path planning process and can probably produce a poor implementation of a task plan. Instead of geometric data, involving higher abstraction level information related to a task to be performed in the path planning of a primitive action could lead to a better relevance of simulations. In this work, we propose an ontology-based approach to generate a specific path planning query for a primitive action, using a well-structured task-oriented knowledge model. This specific path planning query aims at obtaining an increased control on the path planning process of the targeted primitive action.

This work considers Virtual Reality (VR) applications dealing with objects manipulation (such as industrial product assembly, disassembly or maintenance simulation). For such applications, the operator performing the simulation can be assisted by path planning techniques from the robotics research field. A novel automatic path planner involving geometrical, topological and semantic information of the environment is proposed for the guidance of the user through a haptic device. The interaction allows on one hand, the automatic path planner providing assistance to the human operator, and on the other hand, the human operator to reset the whole planning process suggesting a better suited path. Control sharing techniques are used to improve the assisted manipulation ergonomics by dynamically balancing the automatic path planner authority according to the operator involvement in the task, and by predicting user's intent to integrate it as early as possible in the planning process.

International audience