Reachable Space Generation of A Humanoid Robot Using The Monte Carlo Method

In view of the importance of workspace to robotic motion planning and control, we study the reachable space of a humanoid robot in standing postures. Since it would be very difficult or impractical to use conventional analytical method to analyze and obtain the workspace of a humanoid robot, we present a numerical approach in this paper using the Monte Carlo method. As a random sampling numerical method, the Monte Carlo method is relatively simple and flexible to apply, and hence is suitable for the workspace generation of a humanoid robot. After formulating the basic constraints that a humanoid robot must satisfy in a manipulation task to enable the Monte Carlo method in generation of the reachable space, we present the algorithm and a method to build a database for utilization of the numerical results in application. We illustrate this method by an example conducted on the humanoid platform HRP-2. The results show that this method is feasible and practical for the generation and visualization of workspace of a humanoid robot