Literature DB >> 33501292

Visual Odometry Using Pixel Processor Arrays for Unmanned Aerial Systems in GPS Denied Environments.

Alexander McConville1, Laurie Bose2, Robert Clarke1, Walterio Mayol-Cuevas2, Jianing Chen3, Colin Greatwood4, Stephen Carey3, Piotr Dudek3, Tom Richardson1.   

Abstract

Environments in which Global Positioning Systems (GPS), or more generally Global Navigation Satellite System (GNSS), signals are denied or degraded pose problems for the guidance, navigation, and control of autonomous systems. This can make operating in hostile GNSS-Impaired environments, such as indoors, or in urban and natural canyons, impossible or extremely difficult. Pixel Processor Array (PPA) cameras-in conjunction with other on-board sensors-can be used to address this problem, aiding in tracking, localization, and control. In this paper we demonstrate the use of a PPA device-the SCAMP vision chip-combining perception and compute capabilities on the same device for aiding in real-time navigation and control of aerial robots. A PPA consists of an array of Processing Elements (PEs), each of which features light capture, processing, and storage capabilities. This allows various image processing tasks to be efficiently performed directly on the sensor itself. Within this paper we demonstrate visual odometry and target identification running concurrently on-board a single PPA vision chip at a combined frequency in the region of 400 Hz. Results from outdoor multirotor test flights are given along with comparisons against baseline GPS results. The SCAMP PPA's High Dynamic Range (HDR) and ability to run multiple algorithms at adaptive rates makes the sensor well suited for addressing outdoor flight of small UAS in GNSS challenging or denied environments. HDR allows operation to continue during the transition from indoor to outdoor environments, and in other situations where there are significant variations in light levels. Additionally, the PPA only needs to output specific information such as the optic flow and target position, rather than having to output entire images. This significantly reduces the bandwidth required for communication between the sensor and on-board flight computer, enabling high frame rate, low power operation.
Copyright © 2020 McConville, Bose, Clarke, Mayol-Cuevas, Chen, Greatwood, Carey, Dudek and Richardson.

Entities:  

Keywords:  GPS denied; Parallel Processing; SIND; UAS; navigation; pixel processor array; visual odometry

Year:  2020        PMID: 33501292      PMCID: PMC7805748          DOI: 10.3389/frobt.2020.00126

Source DB:  PubMed          Journal:  Front Robot AI        ISSN: 2296-9144


  1 in total

1.  Configural processing enables discrimination and categorization of face-like stimuli in honeybees.

Authors:  A Avarguès-Weber; G Portelli; J Benard; A Dyer; M Giurfa
Journal:  J Exp Biol       Date:  2010-02-15       Impact factor: 3.312

  1 in total
  2 in total

1.  On-sensor binarized CNN inference with dynamic model swapping in pixel processor arrays.

Authors:  Yanan Liu; Laurie Bose; Rui Fan; Piotr Dudek; Walterio Mayol-Cuevas
Journal:  Front Neurosci       Date:  2022-08-15       Impact factor: 5.152

2.  Visual Collaboration Leader-Follower UAV-Formation for Indoor Exploration.

Authors:  Nikolaos Evangeliou; Dimitris Chaikalis; Athanasios Tsoukalas; Anthony Tzes
Journal:  Front Robot AI       Date:  2022-01-04
  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.