Building, registrating, and fusing noisy visual maps
International Journal of Robotics Research - Special Issue on Sensor Data Fusion
Robot Motion Planning and Control
Robot Motion Planning and Control
Recursive Estimation of Motion, Structure, and Focal Length
IEEE Transactions on Pattern Analysis and Machine Intelligence
Planning Algorithms
A penalized nonparametric method for nonlinear constrained optimization based on noisy data
Computational Optimization and Applications
Feedback Systems: An Introduction for Scientists and Engineers
Feedback Systems: An Introduction for Scientists and Engineers
Accurate road following and reconstruction by computer vision
IEEE Transactions on Intelligent Transportation Systems
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This paper describes an efficient algorithm to find a smooth trajectory joining two points A and B with minimum length constrained to avoid fixed subsets. The basic assumption is that the locations of the obstacles are measured several times through a mechanism that corrects the sensors at each reading using the previous observation. The proposed algorithm is based on the penalized nonparametric method previously introduced that uses confidence ellipses as a fattening of the avoidance set. In this paper we obtain consistent estimates of the best trajectory using Monte Carlo construction of the confidence ellipse.