Tailored real-time simulation for teams of humanoid robots

Developing and testing the key modules of autonomous humanoid robots (e.g., for vision, localization, and behavior control) in software-in-the-loop (SIL) experiments, requires real-time simulation of the main motion and sensing properties. These include humanoid robot kinematics and dynamics, the interaction with the environment, and sensor simulation. To deal with an increasing number of robots per team the simulation algorithms must be very efficient. In this paper, the simulator framework MuRoSimF (Multi-Robot-Simulation-Framework) is presented which allows the flexible and transparent integration of different, simulation algorithms with the same robot model. These include several algorithms for simulation of humanoid robot motion kinematics and dynamics (with O(n) runtime complexity), collision handling, and camera simulation including lens distortion. A simulator for teams of humanoid robots based on MuRoS:imF is presented. A unique feature of this simulator is the scalability of the level of detail and complexity which can be chosen individually for each simulated robot and tailored to the requirements of a specific SIL test. Performance measurements are given for real-time simulation on a moderate laptop computer of up to six humanoid robots with 21 degrees of freedom, each equipped with an articulated camera.