Detection and Tracking of Moving Objects for Indoor Mobile Robots with a Low-Cost Laser Scanner

2018 ◽  
pp. 243-250
Author(s):  
Tianyu Liu ◽  
Ye Gu ◽  
Weihua Sheng ◽  
Yongqiang Li ◽  
Yongsheng Ou
Keyword(s):  
Mobile Robots ◽  
Moving Objects ◽  
Low Cost ◽  
Laser Scanner ◽  
Detection And Tracking

Construction and calibration of a low-cost 3D laser scanner with 360° field of view for mobile robots

2015 ◽  
Author(s):  
Jorge L. Martinez ◽  
Jesus Morales ◽  
Antonio J. Reina ◽  
Anthony Mandow ◽  
Alejandro Pequeno-Boter ◽  
...  
Keyword(s):  
Mobile Robots ◽  
Low Cost ◽  
Laser Scanner ◽  
Field Of View

scholarly journals Performance Analysis of Low-Cost Tracking System for Mobile Robots

Machines ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 29
Author(s):  
Andrea Botta ◽  
Giuseppe Quaglia
Keyword(s):  
Performance Analysis ◽  
Mobile Robots ◽  
Moving Objects ◽  
Tracking System ◽  
Low Cost ◽  
Simple Extension ◽  
Preliminary Study ◽  
Indoor Tracking ◽  
User Friendly ◽  
Straightforward Approach

This paper proposes a reliable and straightforward approach to mobile robots (or moving objects in general) indoor tracking, in order to perform a preliminary study on their dynamics. The main features of this approach are its minimal and low-cost setup and a user-friendly interpretation of the data generated by the ArUco library. By using a commonly available camera, such as a smartphone one or a webcam, and at least one marker for each object that has to be tracked, it is possible to estimate the pose of these markers, with respect to a reference conveniently placed in the environment, in order to produce results that are easily interpretable by a user. This paper presents a simple extension to the ArUco library to generate such user-friendly data, and it provides a performance analysis of this application with static and moving objects, using a smartphone camera to highlight the most notable feature of this solution, but also its limitations.

Accurate 3D Localization Using RGB-TOF Camera and IMU for Industrial Mobile Robots

Robotica ◽  
2021 ◽  
pp. 1-18
Author(s):  
Majid Yekkehfallah ◽  
Ming Yang ◽  
Zhiao Cai ◽  
Liang Li ◽  
Chuanxiang Wang
Keyword(s):  
Mobile Robots ◽  
Inertial Measurement Unit ◽  
Indoor Environment ◽  
State Of The Art ◽  
Low Cost ◽  
Estimation Algorithm ◽  
Measurement Unit ◽  
3D Localization ◽  
Fast Motion ◽  
Tof Camera

SUMMARY Localization based on visual natural landmarks is one of the state-of-the-art localization methods for automated vehicles that is, however, limited in fast motion and low-texture environments, which can lead to failure. This paper proposes an approach to solve these limitations with an extended Kalman filter (EKF) based on a state estimation algorithm that fuses information from a low-cost MEMS Inertial Measurement Unit and a Time-of-Flight camera. We demonstrate our results in an indoor environment. We show that the proposed approach does not require any global reflective landmark for localization and is fast, accurate, and easy to use with mobile robots.

Multi Object Detection and Tracking from Video File

2014 ◽  
Vol 533 ◽  
pp. 218-225 ◽  
Author(s):  
Rapee Krerngkamjornkit ◽  
Milan Simic
Keyword(s):  
Computer Vision ◽  
Background Subtraction ◽  
Moving Objects ◽  
Gaussian Mixture Models ◽  
Gaussian Mixture ◽  
Video Tracking ◽  
Partial Occlusion ◽  
Video File ◽  
Detection And Tracking ◽  
Over Time

This paper describes computer vision algorithms for detection, identification, and tracking of moving objects in a video file. The problem of multiple object tracking can be divided into two parts; detecting moving objects in each frame and associating the detections corresponding to the same object over time. The detection of moving objects uses a background subtraction algorithm based on Gaussian mixture models. The motion of each track is estimated by a Kalman filter. The video tracking algorithm was successfully tested using the BIWI walking pedestrians datasets [. The experimental results show that system can operate in real time and successfully detect, track and identify multiple targets in the presence of partial occlusion.

The Research of Moving Target Detection and Tracking System Based on DM6437

2015 ◽  
Vol 734 ◽  
pp. 203-206
Author(s):  
En Zeng Dong ◽  
Sheng Xu Yan ◽  
Kui Xiang Wei
Keyword(s):  
Target Detection ◽  
Digital Signal Processor ◽  
Moving Objects ◽  
Tracking System ◽  
Digital Signal ◽  
Gaussian Mixture ◽  
Background Model ◽  
Moving Target ◽  
Moving Target Detection ◽  
Detection And Tracking

In order to enhance the rapidity and the accuracy of moving target detection and tracking, and improve the speed of the algorithm on the DSP (digital signal processor), an active visual tracking system was designed based on the gaussian mixture background model and Meanshift algorithm on DM6437. The system use the VLIB library developed by TI, and through the method of gaussian mixture background model to detect the moving objects and use the Meanshift tracking algorithm based on color features to track the target in RGB space. Finally, the system is tested on the hardware platform, and the system is verified to be quickness and accuracy.

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