To the Bookstore! Autonomous Wheelchair Navigation in an Urban Environment

Montella, Corey; Perkins, Timothy; Spletzer, John; Sands, Michael

doi:10.1007/978-3-642-40686-7_17

Cited by 11 publications

(7 citation statements)

References 10 publications

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“…Our localization median error of 0.97 m is quite high compared to that of outdoor LRF‐based systems such as that of Montella et al. (), which reports error near 10 cm. This is because proximity data are much more discriminating when there is a sufficient amount of valid laser readings, which is not always the case outdoors.…”

Section: Discussioncontrasting

confidence: 47%

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Autonomous Mobile Robot Localization and Navigation Using a Hierarchical Map Representation Primarily Guided by Vision

2014

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While impressive progress has recently been made with autonomous vehicles, both indoors and on streets, autonomous localization and navigation in less constrained and more dynamic environments, such as outdoor pedestrian and bicycle-friendly sites, remains a challenging problem. We describe a new approach that utilizes several visual perception modules-place recognition, landmark recognition, and road lane detectionsupplemented by proximity cues from a planar laser range finder for obstacle avoidance. At the core of our system is a new hybrid topological/grid-occupancy map that integrates the outputs from all perceptual modules, despite different latencies and time scales. Our approach allows for real-time performance through a combination of fast but shallow processing modules that update the map's state while slower but more discriminating modules are still computing. We validated our system using a ground vehicle that autonomously traversed three outdoor routes several times, each 400 m or longer, on a university campus. The routes featured different road types, environmental hazards, moving pedestrians, and service vehicles. In total, the robot logged over 10 km of successful recorded experiments, driving within a median of 1.37 m laterally of the center of the road, and localizing within 0.97 m (median) longitudinally of its true location along the route. C 2014 Wiley Periodicals, Inc.

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Section: Discussioncontrasting

confidence: 47%

“…Systems such as that of Trulls et al. () and Montella, Perkins, Spletzer, and Sands () do so by solving localization, road heading estimation, and obstacle avoidance, all by using only an LRF. The key is being able to take advantage of various detectable and distinguishable environment features within the LRF range.…”

Section: Related Workmentioning

confidence: 99%

Autonomous Mobile Robot Localization and Navigation Using a Hierarchical Map Representation Primarily Guided by Vision

2014

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“…Different types of smart devices, able to exchange information with the deployed infrastructure, have been proposed in the surveyed papers. They include smart wheelchairs [1,66,105,135], smart canes enhanced with RFID (Radiofrequency identification) readers [52], and haptic sensors to detect obstacles above the waistline [67,112].…”

Section: Smart Devicesmentioning

confidence: 99%

“…Among them, [11] presents an ambient assisted route planner for intelligent wheelchairs. The work by Montella et al [105] describes the Smart Wheelchair System, which is able to autonomously navigate in outdoor environments thanks to 3D perception sensors for detecting ground planes, obstacles, and landmarks. Recently, a similar approach has been investigated in [135], where an intelligent wheelchair, endowed with a variety of sensors and motion controllers for path planning and object grabbing, is presented.…”

Section: Users With Mobility Impairmentsmentioning

confidence: 99%

Accessible wayfinding and navigation: a systematic mapping study

Prandi

Mirri

Fogli

2021

Univ Access Inf Soc

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Urban environments, university campuses, and public and private buildings often present architectural barriers that prevent people with disabilities and special needs to move freely and independently. This paper presents a systematic mapping study of the scientific literature proposing devices, and software applications aimed at fostering accessible wayfinding and navigation in indoor and outdoor environments. We selected 111 out of 806 papers published in the period 2009–2020, and we analyzed them according to different dimensions: at first, we surveyed which solutions have been proposed to address the considered problem; then, we analyzed the selected papers according to five dimensions: context of use, target users, hardware/software technologies, type of data sources, and user role in system design and evaluation. Our findings highlight trends and gaps related to these dimensions. The paper finally presents a reflection on challenges and open issues that must be taken into consideration for the design of future accessible places and of related technologies and applications aimed at facilitating wayfinding and navigation.

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“…The Smart Wheelchair System developed at Lehigh University [12] focused on navigation in structured outdoor environments and urban pedestrian areas such as side walks and university campuses. Their approach employed a map-based localization approach.…”

Section: Related Workmentioning

confidence: 99%

Autonomous personal mobility scooter for multi-class mobility-on-demand service

Andersen

Eng

Leong

et al. 2016

2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC)

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Abstract-In this paper, we describe the design and development of an autonomous personal mobility scooter that was used in public trials during the 2016 MIT Open House, for the purpose of raising public awareness and interest about autonomous vehicles. The scooter is intended to work cooperatively with other classes of autonomous vehicles such as road cars and golf cars to improve the efficacy of Mobilityon-Demand transportation solutions. The scooter is designed to be robust, reliable, and safe, while operating under prolonged durations. The flexibility in fleet expansion is shown by replicating the system architecture and sensor package that has been previously implemented in the road car and golf cars. We show that the vehicle performed robustly with small localization variance. A survey of the users shows that the public is very receptive to the concept of the autonomous personal mobility device.

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To the Bookstore! Autonomous Wheelchair Navigation in an Urban Environment

Cited by 11 publications

References 10 publications

Autonomous Mobile Robot Localization and Navigation Using a Hierarchical Map Representation Primarily Guided by Vision

Autonomous Mobile Robot Localization and Navigation Using a Hierarchical Map Representation Primarily Guided by Vision

Accessible wayfinding and navigation: a systematic mapping study

Autonomous personal mobility scooter for multi-class mobility-on-demand service

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