Multimodal Perception System for Real Open Environment

Yuyang Sha, Jiasong Xiao, Kefeng Li

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper presents a novel multimodal perception system for a real open environment. The proposed system includes an embedded computation platform, cameras, ultrasonic sensors, GPS, and IMU devices. Unlike the traditional frameworks, our system integrates multiple sensors with advanced computer vision algorithms to help users walk outside reliably. The system can efficiently complete various tasks, including navigating to specific locations, passing through obstacle regions, and crossing intersections. Specifically, we also use ultrasonic sensors and depth cameras to enhance obstacle avoidance performance. The path planning module is designed to find the locally optimal route based on various feedback and the user's current state. To evaluate the performance of the proposed system, we design several experiments under different scenarios. The results show that the system can help users walk efficiently and independently in complex situations.

Original languageEnglish
Title of host publicationSixteenth International Conference on Signal Processing Systems, ICSPS 2024
EditorsRobert Minasian, Li Chai
PublisherSPIE
ISBN (Electronic)9781510689251
DOIs
Publication statusPublished - 2025
Event16th International Conference on Signal Processing Systems, ICSPS 2024 - Kunming, China
Duration: 15 Nov 202417 Nov 2024

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume13559
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference16th International Conference on Signal Processing Systems, ICSPS 2024
Country/TerritoryChina
CityKunming
Period15/11/2417/11/24

Keywords

  • computer vision
  • deep learning
  • object detection
  • perception system
  • semantic segmentation

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