Mobile Robot Localization Using Sonar
IEEE Transactions on Pattern Analysis and Machine Intelligence
Physically Based Simulation Model for Acoustic Sensor Robot Navigation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Differentiating Sonar Reflections from Corners and Planes by Employing an Intelligent Sensor
IEEE Transactions on Pattern Analysis and Machine Intelligence
Sensors for mobile robots: theory and application
Sensors for mobile robots: theory and application
Mobile robot sonar for target localization and classification
International Journal of Robotics Research
A fuzzy approach to build sonar maps for mobile robots
Computers in Industry
Quantitative evaluation of the exploration strategies of a mobile robot
International Journal of Robotics Research
Navigating Mobile Robots: Systems and Techniques
Navigating Mobile Robots: Systems and Techniques
Directed Sonar Sensing for Mobile Robot Navigation
Directed Sonar Sensing for Mobile Robot Navigation
Environment Mapping with a Mobile Robot Using Sonar
AI '88 Proceedings of the 2nd Australian Joint Artificial Intelligence Conference
Image Analysis and Mathematical Morphology
Image Analysis and Mathematical Morphology
Constructing maps for mobile robot navigation based on ultrasonic range data
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Effective maximum likelihood grid map withconflict evaluation filter using sonar sensors
IEEE Transactions on Robotics
Biomimetic Sonar: Binaural 3D Localization using Artificial Bat Pinnae
International Journal of Robotics Research
Hi-index | 0.00 |
A new technique for processing ultrasonic arc maps is proposed and compared to six existing techniques for map-building purposes. These techniques are simple point marking along the line-of-sight, voting and thresholding, morphological processing, Bayesian update scheme for occupancy grids, arc-transversal median algorithm, and triangulation-based fusion. The directional maximum technique, newly proposed in this paper, employs directional processing to extract the map of the environment from ultrasonic arc maps. It aims at overcoming the intrinsic angular uncertainty of ultrasonic sensors in map building, as well as eliminating noise and cross-talk related misreadings. The compared techniques are implemented with a wall-following motion-planning scheme for ground coverage. The comparison is based on experimental data and three complementary error criteria: mean absolute error, correct detection rate for full and empty regions, and computational cost in terms of CPU time. The directional maximum technique offers a very good compromise between mean absolute error and correct detection rate, with a processing time less than one-tenth of a second. Compared to the existing techniques, the directional maximum method is also superior in range accuracy and in eliminating artifacts, resulting in the best overall performance. The results indicate several trade-offs in the choice of ultrasonic arc-map processing techniques.