Physically Based Simulation Model for Acoustic Sensor Robot Navigation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Spatial Sampling Criterion for Sonar Obstacle Detection
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
Spatial planning: a configuration space approach
Autonomous robot vehicles
A physically based navigation strategy for sonar-guided vehicles
International Journal of Robotics Research
Introduction to Robotics: Mechanics and Control
Introduction to Robotics: Mechanics and Control
Digital Principles and Applications
Digital Principles and Applications
Sensor and Navigation System for a Mobile Robot
Intelligent Autonomous Systems, An International Conference
Mobile Robot Relocation from Echolocation Constraints
IEEE Transactions on Pattern Analysis and Machine Intelligence
Journal of Intelligent and Robotic Systems
A Physical Model-Based Analysis of Heterogeneous Environments Using Sonar-ENDURA Method
IEEE Transactions on Pattern Analysis and Machine Intelligence
Localization using combining sensors and dead-reckoning
Focus on computational neurobiology
Cooperative Indoor Radio Environment Mapping in Ad-hoc Wireless Cognitive Networks
Wireless Personal Communications: An International Journal
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The physical properties of acoustic sensors are exploited to obtain information about the environment for sonar map building. A theoretical formulation for interpreting the sensor databases on the physical principles of acoustic propagation and reflection is presented. A characterization of the sonar scan that allows the differentiation of planes, corners, and edges in a specular environment is described. A single sensor mounted on an autonomous vehicle in a laboratory verifies the technique. The implications for sonar map building and the limitations of differentiating elements with one sensor are discussed.