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Chiara Fulgenzi
Researcher at French Institute for Research in Computer Science and Automation
Publications - 9
Citations - 528
Chiara Fulgenzi is an academic researcher from French Institute for Research in Computer Science and Automation. The author has contributed to research in topics: Probabilistic logic & Motion planning. The author has an hindex of 7, co-authored 9 publications receiving 485 citations.
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Proceedings ArticleDOI
Dynamic Obstacle Avoidance in uncertain environment combining PVOs and Occupancy Grid
TL;DR: The paper presents a method to estimate the probability of collision where uncertainty in position, shape and velocity of the obstacles, occlusions and limited sensor range contribute directly to the computation.
Proceedings ArticleDOI
Probabilistic navigation in dynamic environment using Rapidly-exploring Random Trees and Gaussian processes
TL;DR: The paper describes a navigation algorithm for dynamic, uncertain environment 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.
Proceedings ArticleDOI
Probabilistic motion planning among moving obstacles following typical motion patterns
TL;DR: The paper presents a navigation algorithm for dynamic probabilistic environments based on an extension of the Rapidly-exploring Random Tree algorithm, where the likelihood of the obstacles future trajectory and the probability of collision is explicitly taken into account.
Risk based motion planning and navigation in uncertain dynamic environment
TL;DR: A new concept to integrate a probabilist collision risk function linking planning and navigation methods with the perception and the prediction of the dynamic environments, and shows the performance for a robotic wheelchair in a simulated environment among multiple dynamic obstacles.
Journal ArticleDOI
Experimental validation of FastSLAM algorithm integrated with a linear features based map
TL;DR: The proposed approach results in a computationally efficient solution to the SLAM problem and the high quality sensor measurements allow to maintain a good localization of the mobile base and a compact representation of the environment.