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Long range LiDAR characterisation for obstacle detection for use by the visually impaired and blind
O'Keeffe, Rosemary; O'Murchu, Cian; Mathewson, Alan; Gnecchi, Salvatore; Buckley, Steve
Obstacle detection has become a very important area of interest for the automotive industry due to the move towards autonomous vehicles. Since the environment the vehicle has to navigate is ever changing the current best system for obstacle detection is to combine a number of sensors. This means that for the varying weather and lighting conditions the best sensor can be used to provided obstacle detection and avoidance information. The INSPEX H2020 project goal is to use a similar system of multiple sensors to provide personal obstacle detection for visually impaired and blind (VIB) people. Figure 1 shows the INSPEX ambition. Power, weight and size reduction will be key to achieving this goal. In this paper the initial prototype is characterised and improvements beyond typical reduction of key parameters is considered. The INSPEX system will integrate a short range LiDAR (distances up to 5m), an ultrawide band (UWB) RADAR (distances up to 5m), ultrasound (distances up to 2m) and a long range LiDAR (distances up to 10m). The sensors will be miniaturised and the power consumption reduced so that they can be incorporated into a white cane. In this paper the first prototype for the long range LiDAR sensor is characterised for various lighting conditions and distances. The results show that for distances of 3m and 5m consistence obstacle detection can be achieved even in bright lighting conditions but for distances beyond this the detection can be inconsistence and is highly dependent on the lighting conditions.
Keyword(s): Collision avoidance; Handicapped aids; Mobile robots; Optical radar; Ultrasonic devices; Range LiDAR characterisation,; Obstacle detection,; Autonomous vehicles,; Vehicles surroundings,; Range sensors,; Smart white cane,; Visually impaired and blind people,; Size 10.0 m; LiDAR; Characterisation; Embedded; Integrated system; Low-power
Publication Date:
Type: Conference item
Peer-Reviewed: Yes
Language(s): English
Institution: University College Cork
Citation(s): O'Keefe, R., O'Murchu, C., Mathewson, A., Gnecchi, S. and Buckley, S. (2018) 'Long range LiDAR characterisation for obstacle detection for use by the visually impaired and blind', Smart Systems Integration 2018, Dresden, Germany, 11-12 April.
File Format(s): application/pdf
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First Indexed: 2018-09-25 06:31:05 Last Updated: 2018-09-25 06:31:05