Proceedings ArticleDOI
Collision avoidance for a low-cost robot using SVM-based monocular vision
Ajay Shankar,Mayank Vatsa,P. B. Sujit +2 more
- pp 277-282
TLDR
An obstacle avoidance algorithm that learns optical flow patterns through an SVM classifier that can be used for indoors and outdoors without modifying the algorithm is proposed.Abstract:
Collision-free navigation is an important problem in autonomous robots. In most of the applications, camera vision techniques using stereo-vision and laser scanners have been used. These techniques are not commercially viable for miniature robots due to size and computational limitations. Optical flow based models using monocular vision have shown promise in biomimetic systems to estimate depth information from a scene. In this paper, we propose an obstacle avoidance algorithm that learns optical flow patterns through an SVM classifier. Experimental results and simulation results are presented to validate our approach. The system can be used for indoors and outdoors without modifying the algorithm.read more
Citations
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Journal ArticleDOI
Image Segmentation-Based Unmanned Aerial Vehicle Safe Navigation
TL;DR: This work proposes a vision-based guidance scheme for an unmanned aerial vehicle navigating through urban environments while seeking a predefined goal point and presents a much improved avoidance performance as compared to existing optical flow-based methods.
Proceedings ArticleDOI
An experimental evaluation of balance strategy based obstacle avoidance
TL;DR: This paper evaluates obstacle avoidance methods based on optical flow in synthetic and real-world scenes using five representative optical flow algorithms and demonstrates the effectiveness of the balance strategy for obstacle avoidance.
Proceedings ArticleDOI
Development of Low-Cost Autonomous Robot
Sanjha Khan,Jawaid Daudpoto +1 more
TL;DR: This type of inexpensive robot finds usefulness in schools for robotic studies where each student can work individually and understand the sensing, actuating and the dynamics of wheeled robot.
An experimental evaluation of balance strategy based obstacle avoidance
TL;DR: In this article, the authors evaluate obstacle avoidance methods based on optical flow in synthetic and real-world scenes, where the balance strategy is chosen and five representative optical flow algorithms are used.
Book ChapterDOI
Obstacle Detection in Drones Using Computer Vision Algorithm
TL;DR: In the proposed method, key point features are extracted from each video frame using Computer vision algorithms like Harris corner detector and Scale Invariant Feature Transform algorithm (SIFT) and by using Brute Force Matching (BFM), key points of consecutive frames are matched.
References
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