Next Article in Journal
Paper-Based Sensors: Emerging Themes and Applications
Next Article in Special Issue
Automatic Calibration of an Around View Monitor System Exploiting Lane Markings
Previous Article in Journal
Star Centroiding Based on Fast Gaussian Fitting for Star Sensors
Previous Article in Special Issue
Handshape Recognition Using Skeletal Data
Open AccessArticle

Lightweight Visual Odometry for Autonomous Mobile Robots

College of Engineering and Computer Science, University of Michigan-Dearborn, Dearborn, MI 48128, USA
*
Author to whom correspondence should be addressed.
Sensors 2018, 18(9), 2837; https://doi.org/10.3390/s18092837
Received: 19 July 2018 / Revised: 23 August 2018 / Accepted: 25 August 2018 / Published: 28 August 2018
(This article belongs to the Special Issue Visual Sensors)
Vision-based motion estimation is an effective means for mobile robot localization and is often used in conjunction with other sensors for navigation and path planning. This paper presents a low-overhead real-time ego-motion estimation (visual odometry) system based on either a stereo or RGB-D sensor. The algorithm’s accuracy outperforms typical frame-to-frame approaches by maintaining a limited local map, while requiring significantly less memory and computational power in contrast to using global maps common in full visual SLAM methods. The algorithm is evaluated on common publicly available datasets that span different use-cases and performance is compared to other comparable open-source systems in terms of accuracy, frame rate and memory requirements. This paper accompanies the release of the source code as a modular software package for the robotics community compatible with the Robot Operating System (ROS). View Full-Text
Keywords: visual odometry; ego-motion estimation; stereo; RGB-D; mobile robots visual odometry; ego-motion estimation; stereo; RGB-D; mobile robots
Show Figures

Figure 1

MDPI and ACS Style

Aladem, M.; Rawashdeh, S.A. Lightweight Visual Odometry for Autonomous Mobile Robots. Sensors 2018, 18, 2837.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop