Sonar Sensor Model for Safe Landing and Obstacle Detection

Author(s):  
Umberto Papa
2012 ◽  
Vol 152-154 ◽  
pp. 1195-1201
Author(s):  
Kuan Meng Tan ◽  
Tien Fu Lu ◽  
Amir Anvar

One of the key aspects in designing an Autonomous Underwater Vehicle (AUV) simulation framework is sensor modeling. This paper presents specifically the underwater sonar sensor modeling structure used in the proposed AUV simulation framework. This sensor model covers the mathematical aspects from the field of acoustics which mimics real world sensors. Simplified sonar signal models are widely used however rarely discussed in the literature. Based on this designed simulation framework, simple scenario using different sonar configuration is shown and discussed. This paper shows the formulation of a typical side-scan sonar with emphasis on the assumptions which leads to the simplification of the sonar model. The sonar sensor model is built based on a developed AUV test-bed which was done previously in the University of Adelaide.


Author(s):  
John J. Leonard ◽  
Hugh F. Durrant-Whyte
Keyword(s):  

2016 ◽  
Vol 31 (6) ◽  
pp. 34-40 ◽  
Author(s):  
Umberto Papa ◽  
Giuseppe Del Core ◽  
Francesco Picariello

2019 ◽  
Vol 7 (1) ◽  
pp. 2-18 ◽  
Author(s):  
Ravinder Singh ◽  
Kuldeep Singh Nagla

Purpose An efficient perception of the complex environment is the foremost requirement in mobile robotics. At present, the utilization of glass as a glass wall and automated transparent door in the modern building has become a highlight feature for interior decoration, which has resulted in the wrong perception of the environment by various range sensors. The perception generated by multi-data sensor fusion (MDSF) of sonar and laser is fairly consistent to detect glass but is still affected by the issues such as sensor inaccuracies, sensor reliability, scan mismatching due to glass, sensor model, probabilistic approaches for sensor fusion, sensor registration, etc. The paper aims to discuss these issues. Design/methodology/approach This paper presents a modified framework – Advanced Laser and Sonar Framework (ALSF) – to fuse the sensory information of a laser scanner and sonar to reduce the uncertainty caused by glass in an environment by selecting the optimal range information corresponding to a selected threshold value. In the proposed approach, the conventional sonar sensor model is also modified to reduce the wrong perception in sonar as an outcome of the diverse range measurement. The laser scan matching algorithm is also modified by taking out the small cluster of laser point (w.r.t. range information) to get efficient perception. Findings The probability of the occupied cells w.r.t. the modified sonar sensor model becomes consistent corresponding to diverse sonar range measurement. The scan matching technique is also modified to reduce the uncertainty caused by glass and high computational load for the efficient and fast pose estimation of the laser sensor/mobile robot to generate robust mapping. These stated modifications are linked with the proposed ALSF technique to reduce the uncertainty caused by glass, inconsistent probabilities and high load computation during the generation of occupancy grid mapping with MDSF. Various real-world experiments are performed with the implementation of the proposed approach on a mobile robot fitted with laser and sonar, and the obtained results are qualitatively and quantitatively compared with conventional approaches. Originality/value The proposed ASIF approach generates efficient perception of the complex environment contains glass and can be implemented for various robotics applications.


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