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--- en:research [2012/02/20 23:38] – bonnif
+++ en:research [2022/05/19 14:55] (current) – bonnif
@@ Line 1: / Line 1: @@
-====== Research interests ======
+===== Intelligent Vehicles Navigation =====
-Intelligent Vehicles are robotic systems that perceive the driving environment to assist the driver in safe vehicle operation by providing pertinent information or by controlling directly the vehicle. In this perception process, global localization is useful to retrieve contextual information often stored in a geographical database.
-Global Navigation Satellite Systems (GNSS) - like GPS, which is an affordable technology currently - provide global localization on the scale of the planet. A natural GNSS receiver uses only pseudo-ranges and Doppler measurements to compute an estimate of its location in ECEF coordinates, whatever the mobile: a pedestrian, plane, boat, car, etc. For ground localization, satellite outages and multi-path can occur frequently, particularly in urban areas. The quality of the positioning service therefore changes a lot depending on the local context.
+Intelligent vehicles operate in open and uncontrolled environments. They may assist the driver or have control of some driving tasks. \\
+For autonomous navigation, localization is still an open problem. Global Navigation Satellite Systems (GNSS) provide global localization and need to be assisted by exteroceptive and proprioceptive sensors and map information to increase the performance particularly in terms of accuracy and integrity. I study methods and algorithms able to merge these sources of information and able to provide reliable confidence indicators. \\
+Perception systems that use on-board exteroceptive sensors (e.g. cameras or lidars) and information shared by cooperative agents need also deep improvements to enable drivable space characterization and scene understanding. I consider frameworks and methodologies able to handle uncertainties and partial knowledge in highly dynamic open conditions.\\
+I am also interested in the definition and elaboration of enhanced digital maps able to support these different processes, being convinced that they will play a key role in this field.
 ===== Key words =====
-  * Mobile Robotics, Intelligent Vehicles
+  * Robotics
-  * Advanced Driver Assistance System,
+  * Intelligent Vehicles
-  * Robotic Perception, Obstacle Detection, Drivable Space
+  * Autonomous Navigation
-  * Data and Multisensor Fusion
+  * Localization and Maps
-  * Road Vehicles Localization
+  * Integrity Monitoring (FDE and confidence domains computation)
-  - GNSS (GPS, Galileo)
+  * Multisensor Data Fusion (Kalman filtering, bounded error methods)
-  - GIS and Navigable Maps
+  * Perception (Road users detection, drivable space characterization)
-  - Map-matching
+  * Cooperative systems
-  - Natural landmarks
-  - Integrity monitoring, Fault Detection, Identification, Adaptation
-  * State Observers for handling uncertainties
-  - Bayesian (EKF, UKF, PF, IMM, etc.)
-  - Set-membership (Set Inversion, Interval Analysis, CSP, BPF)
-  - Belief Theory

UMR CNRS 7253

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