In the present paper, we introduce a new control architecture aimed at driving virtual humans in interaction with virtual environments, by motion capture. It brings decoupling of functionalities, and also of stability thanks to passivity. We show projections can break passivity, and thus must be used carefully. Our control scheme enables task space and internal control, contact, and joint limits management. Thanks to passivity, it can be easily extended. Besides, we introduce a new tool as for manikin's control, which makes it able to build passive projections, so as to guide the virtual manikin when sharp movements are needed.

We propose to explore the problem of mechanism synthesis with an approach using genetic algorithms. We intend to study the case where there exist geometric constraints (as avoiding obstacles). More precisely, we are interested in the choice of robots (morphology and position) which has to follow a given trajectory among obstacles.

In complex mechanical systems, the important features to be considered in the earliest phases of assembly design are: the operators accessibility for assembly operations and maintenance checking. We present in this paper a new approach for solving this problem by considering the human operator as a manipulator, taking into account the geometrical and biomechanical constraints. They are integrated by penalizing a global criterion. The solution of the associated optimization problem is obtained with simulated annealing algorithm.

The authors describe a general method of designing and positioning a robot in an environment in order to solve geometrical problems related to the accessibility of given zones. The approach is characterized by the use of two different types of representation of the solids and of the spaces: a CSG (constructive solid geometry) and an octree representation. Each is well adapted to solve two different problems: collision detection and description of the attained space. In addition, an automatic algorithm is used to design any robot related to any set of Denavit-Hartenberg parameters. The use of an optimal approach makes it possible to define the parameters of the robot and its position and orientation in the environment that satisfy the specified task.>