GBS: Guidance by Semantics-Using High-Level Visual Inference to Improve Vision-Based Mobile Robot Localization

Abstract

The overall objective in guidance by semantics is to improve the sensing and actuation of unmanned and optionally manned platforms by incorporating high-level visual inference into the robot loop. Our specific goal in this project is to perform mapping and localization on a mobile platform using semantically meaningful sensor data. In our case, we have used a camera image co-registered with a laser scan to filter in scan points that fall on buildings in the scene or an RGBD sensor. This enables the robotic platform to only make use of readings that are known to be good, static landmarks, such as buildings as we have done in previous years. However, buildings are just one small type of semantic inference we can and plan to use.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Aug 28, 2015
Accession Number
ADA625865

Entities

People

  • Jason J. Corso

Organizations

  • University at Buffalo

Tags

Communities of Interest

  • Autonomy
  • Biomedical
  • Sensors

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Artificial Intelligence Software
  • Autonomous Navigation
  • Autonomous Systems
  • Computer Vision
  • Data Mining
  • Guidance
  • Information Processing
  • Information Science
  • Machine Learning
  • Monte Carlo Method
  • Pattern Recognition
  • Robot Mapping
  • Robot Navigation
  • Robots
  • Simultaneous Localization And Mapping
  • Supervised Machine Learning

Fields of Study

  • Computer science
  • Engineering

Readers

  • Computational Linguistics
  • Computer Vision.
  • Robotics and Automation.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • Autonomy
  • Directed Energy