Title :
Probabilistic modeling and analysis of high-speed rough-terrain mobile robots
Author :
Golda, Dariusz ; Iagnemma, Karl ; Dubowsky, Steven
Author_Institution :
Massachusetts Inst. of Technol., Cambridge, MA, USA
fDate :
26 April-1 May 2004
Abstract :
Mobile robots have important applications in high speed, rough-terrain scenarios. It would be desirable to construct accurate models of these systems. However, due to the system complexity, accurate modeling is difficult. In This work a high-speed rough-terrain robot model is presented. Experiments show that this model can accurately predict robot performance in simple, well-known terrain. However in unstructured, rough terrain, performance prediction is less accurate. A stochastic method for analyzing system performance in spite of model parameter uncertainty is presented. A method for studying model sensitivity to parameter uncertainty is also presented. It is shown that stochastic analysis can be used effectively for model-based analysis of real-world rough-terrain robotic systems.
Keywords :
mobile robots; probability; sensitivity analysis; stochastic processes; high-speed rough-terrain mobile robots; model parameter uncertainty; model sensitivity; model-based analysis; probabilistic modeling; stochastic analysis; system complexity; Damping; Mobile robots; Performance analysis; Predictive models; Robot sensing systems; Stochastic systems; System performance; Tires; Uncertain systems; Wheels;
Conference_Titel :
Robotics and Automation, 2004. Proceedings. ICRA '04. 2004 IEEE International Conference on
Print_ISBN :
0-7803-8232-3
DOI :
10.1109/ROBOT.2004.1307266