Robot simulation physics validation
PerMIS '07 Proceedings of the 2007 Workshop on Performance Metrics for Intelligent Systems
Extending open dynamics engine for robotics simulation
SIMPAR'10 Proceedings of the Second international conference on Simulation, modeling, and programming for autonomous robots
Evaluation and enhancement of common simulation methods for robotic range sensors
SIMPAR'10 Proceedings of the Second international conference on Simulation, modeling, and programming for autonomous robots
Simulation and evaluation of mixed-mode environments: towards higher quality of simulations
SIMPAR'10 Proceedings of the Second international conference on Simulation, modeling, and programming for autonomous robots
Binocular stereo vision system for a humanoid robot
International Journal of Computer Applications in Technology
Petri-net-based implementations for FIRA weightlifting and sprint games with a humanoid robot
Robotics and Autonomous Systems
Hi-index | 0.00 |
In this paper a humanoid robot simulator based on the multi-robot simulation framework (MuRoSimF) is presented. Among the unique features of this simulator is the scalability in the level of physical detail in both the robot's motion and sensing systems. It facilitates the development of control software for humanoid robots which is demonstrated for several scenarios from the RoboCup Humanoid Robot League. Different requirements exist for a humanoid robot simulator. E.g., testing of algorithms for motion control and postural stability require high fidelity of physical motion properties whereas testing of behavior control and role distribution for a robot team requires only a moderate level of detail for real-time simulation of multiple robots. To meet such very different requirements often different simulators are used which makes it necessary to model a robot multiple times and to integrate different simulations with high-level robot control software. MuRoSimF provides the capability of exchanging the simulation algorithms used for each robot transparently, thus allowing a trade-off between computational performance and fidelity of the simulation. It is therefore possible to choose different simulation algorithms which are adequate for the needs of a given simulation experiment, for example, motion simulation of humanoid robots based on kinematical, simplified dynamics or full multi-body system dynamics algorithms. In this paper also the sensor simulation capabilities of MuRoSimF are revised. The methods for motion simulation and collision detection and handling are presented in detail including an algorithm which allows the real-time simulation of the full dynamics of a 21 DOF humanoid robot. Merits and drawbacks of the different algorithms are discussed in the light of different simulation purposes. The simulator performance is measured and illustrated in various examples, including comparison with experiments of a physical humanoid robot.