Real-time obstacle avoidance for manipulators and mobile robots
International Journal of Robotics Research
IEEE Transactions on Pattern Analysis and Machine Intelligence
Performance of optical flow techniques
International Journal of Computer Vision
Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Vision for Mobile Robot Navigation: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Dominant plane detection from optical flow for robot navigation
Pattern Recognition Letters
Omnidirectional Vision and Invariant Theory for Robot Navigation Using Conformal Geometric Algebra
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
Efficient Monocular 3D Reconstruction from Segments for Visual Navigation in Structured Environments
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
Robot Navigation by Panoramic Vision and Attention Guided Fetaures
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
Corridor Navigation and Obstacle Avoidance using Visual Potential for Mobile Robot
CRV '07 Proceedings of the Fourth Canadian Conference on Computer and Robot Vision
An iterative image registration technique with an application to stereo vision
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2
Illumination-robust variational optical flow with photometric invariants
Proceedings of the 29th DAGM conference on Pattern recognition
A self-organizing approach to detection of moving patterns for real-time applications
BVAI'07 Proceedings of the 2nd international conference on Advances in brain, vision and artificial intelligence
Mobile robot navigation in 2-D dynamic environments using an electrostatic potential field
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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In this paper, we develop a novel algorithm for navigating a mobile robot using the visual potential. The visual potential is computed from an image sequence and optical flow computed from successive images captured by the camera mounted on the robot. We assume that the direction to the destination is provided at the initial position of the robot. Using the direction to the destination, the robot dynamically selects a local pathway to the destination without collision with obstacles. The proposed algorithm does no require any knowledge or environmental maps of the robot workspace. Furthermore, this algorithm uses only a monocular uncalibrated camera for detecting a feasible region of navigation, since we apply the dominant plane detection to detect the feasible region. We present the experimental results of navigation in synthetic and real environments. Additionally, we present the robustness evaluation of optical flow computation against lighting effects and various kinds of textures.