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Enabling Autonomous Navigation for Affordable Scooters

Computer Engineering, San Jose State University, San Jose, CA 95123, USA
Author to whom correspondence should be addressed.
Sensors 2018, 18(6), 1829;
Received: 1 April 2018 / Revised: 19 May 2018 / Accepted: 21 May 2018 / Published: 5 June 2018
(This article belongs to the Section Physical Sensors)
Despite the technical success of existing assistive technologies, for example, electric wheelchairs and scooters, they are still far from effective enough in helping those in need navigate to their destinations in a hassle-free manner. In this paper, we propose to improve the safety and autonomy of navigation by designing a cutting-edge autonomous scooter, thus allowing people with mobility challenges to ambulate independently and safely in possibly unfamiliar surroundings. We focus on indoor navigation scenarios for the autonomous scooter where the current location, maps, and nearby obstacles are unknown. To achieve semi-LiDAR functionality, we leverage the gyros-based pose data to compensate the laser motion in real time and create synthetic mapping of simple environments with regular shapes and deep hallways. Laser range finders are suitable for long ranges with limited resolution. Stereo vision, on the other hand, provides 3D structural data of nearby complex objects. To achieve simultaneous fine-grained resolution and long range coverage in the mapping of cluttered and complex environments, we dynamically fuse the measurements from the stereo vision camera system, the synthetic laser scanner, and the LiDAR. We propose solutions to self-correct errors in data fusion and create a hybrid map to assist the scooter in achieving collision-free navigation in an indoor environment. View Full-Text
Keywords: autonomous system; sensor fusion; scooter; object detection; navigation; SLAM autonomous system; sensor fusion; scooter; object detection; navigation; SLAM
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MDPI and ACS Style

Liu, K.; Mulky, R. Enabling Autonomous Navigation for Affordable Scooters. Sensors 2018, 18, 1829.

AMA Style

Liu K, Mulky R. Enabling Autonomous Navigation for Affordable Scooters. Sensors. 2018; 18(6):1829.

Chicago/Turabian Style

Liu, Kaikai, and Rajathswaroop Mulky. 2018. "Enabling Autonomous Navigation for Affordable Scooters" Sensors 18, no. 6: 1829.

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