Path Planner for Objects, Robots and Mannequins by Multi-Agents Systems or Motion Captures

TL;DR

This paper introduces two methods for path planning of virtual humans and robots: one using multi-agent systems with ergonomic constraints, and another based on motion capture data for precise trajectory generation.

Contribution

It presents a novel multi-agent system approach for path planning considering ergonomic constraints and integrates motion capture data for virtual human trajectory evolution.

Findings

Multi-agent system effectively plans paths with ergonomic considerations.

Motion capture data enhances virtual human trajectory accuracy.

Real-time operator collaboration improves environment perception.

Abstract

In order to optimise the costs and time of design of the new products while improving their quality, concurrent engineering is based on the digital model of these products. However, in order to be able to avoid definitively physical model without loss of information, new tools must be available. Especially, a tool making it possible to check simply and quickly the maintainability of complex mechanical sets using the numerical model is necessary. Since one decade, the MCM team of IRCCyN works on the creation of tools for the generation and the analysis of trajectories of virtual mannequins. The simulation of human tasks can be carried out either by robot-like simulation or by simulation by motion capture. This paper presents some results on the both two methods. The first method is based on a multi-agent system and on a digital mock-up technology, to assess an efficient path planner for a manikin or a robot for access and visibility task taking into account ergonomic constraints or joint limits. The human operator is integrated in the process optimisation to contribute to a global perception of the environment. This operator cooperates, in real-time, with several automatic local elementary agents. In the second method, we worked with the CEA and EADS/CCR to solve the constraints related to the evolution of human virtual in its environment on the basis of data resulting from motion capture system. An approach using of the virtual guides was developed to allow to the user the realization of precise trajectory in absence of force feedback.