Abstract
Abstract Common control systems for mobile robots include the use of deterministic control laws together with state estimation approaches and the consideration of the certainty equivalence principle. Recent approaches consider the use of partially observable Markov decision process strategies together with Bayesian estimators. In order to reduce the required processing power and yet allow for multimodal or non-Gaussian distributions, a scheme based on a particle filter and a corresponding cloud of input signals is proposed in this paper. Results are presented and compared to a scheme with extended Kalman filter and the assumption that the certainty equivalence holds.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
