Probabilistic navigation in dynamic environment using Rapidly-exploring Random Trees and Gaussian processes Export

@inproceedings{citeulike:3722170, abstract = {The paper describes a navigation algorithm for dynamic, uncertain environment. Moving obstacles are supposed to move on typical patterns which are pre-learned and are represented by Gaussian processes. The planning algorithm is based on an extension of the Rapidly-exploring Random Tree algorithm, where the likelihood of the obstacles trajectory and the probability of collision is explicitly taken into account. The algorithm is used in a partial motion planner, and the probability of collision is updated in real-time according to the most recent estimation. Results show the performance of the navigation algorithm for a car-like robot moving among dynamic obstacles with probabilistic trajectory prediction.}, author = {Fulgenzi, Chiara and Tay, Christopher and Spalanzani, Anne and Laugier, Christian}, booktitle = {Intelligent Robots and Systems, 2008. IROS 2008. IEEE/RSJ International Conference on}, citeulike-article-id = {3722170}, citeulike-linkout-0 = {http://dx.doi.org/10.1109/IROS.2008.4650959}, citeulike-linkout-1 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4650959}, doi = {10.1109/IROS.2008.4650959}, journal = {Intelligent Robots and Systems, 2008. IROS 2008. IEEE/RSJ International Conference on}, keywords = {crowd-control, robotics}, pages = {1056--1062}, posted-at = {2009-08-06 09:46:04}, priority = {2}, title = {Probabilistic navigation in dynamic environment using Rapidly-exploring Random Trees and Gaussian processes}, url = {http://dx.doi.org/10.1109/IROS.2008.4650959}, year = {2008} }

TY - CONF ID - citeulike:3722170 L3 - citeulike-article-id:3722170 N2 - The paper describes a navigation algorithm for dynamic, uncertain environment. Moving obstacles are supposed to move on typical patterns which are pre-learned and are represented by Gaussian processes. The planning algorithm is based on an extension of the Rapidly-exploring Random Tree algorithm, where the likelihood of the obstacles trajectory and the probability of collision is explicitly taken into account. The algorithm is used in a partial motion planner, and the probability of collision is updated in real-time according to the most recent estimation. Results show the performance of the navigation algorithm for a car-like robot moving among dynamic obstacles with probabilistic trajectory prediction. JF - Intelligent Robots and Systems, 2008. IROS 2008. IEEE/RSJ International Conference on EP - 1062 TI - Probabilistic navigation in dynamic environment using Rapidly-exploring Random Trees and Gaussian processes T2 - Intelligent Robots and Systems, 2008. IROS 2008. IEEE/RSJ International Conference on SP - 1056 KW - crowd-control KW - robotics AU - Fulgenzi, Chiara AU - Tay, Christopher AU - Spalanzani, Anne AU - Laugier, Christian PY - 2008/// UR - http://dx.doi.org/10.1109/IROS.2008.4650959 ER -