scholarly journals A Visual Navigation Strategy Based on Inverse Perspective Transformation

Robot Vision ◽  
10.5772/9309 ◽  
2010 ◽  
Author(s):  
Francisco Bonin-Font ◽  
Alberto Ortiz ◽  
Gabriel Oliver

2012 ◽  
Vol 48 (5) ◽  
pp. 264 ◽  
Author(s):  
F. Bonin-Font ◽  
A. Burguera ◽  
A. Ortiz ◽  
G. Oliver


2021 ◽  
Vol 55 (4) ◽  
pp. 24-32
Author(s):  
Nare Karapetyan ◽  
James V. Johnson ◽  
Ioannis Rekleitis

Abstract This work proposes vision-only navigation strategies for an autonomous underwater robot. This approach is a step towards solving the coverage path planning problem in a 3-D environment for surveying underwater structures. Given the challenging conditions of the underwater domain, it is very complicated to obtain accurate state estimates reliably. Consequently, it is a great challenge to extend known path planning or coverage techniques developed for aerial or ground robot controls. In this work, we are investigating a navigation strategy utilizing only vision to assist in covering a complex underwater structure. We propose to use a navigation strategy akin to what a human diver will execute when circumnavigating around a region of interest, in particular when collecting data from a shipwreck. The focus of this article is a step towards enabling the autonomous operation of lightweight robots near underwater wrecks in order to collect data for creating photo-realistic maps and volumetric 3-D models while at the same time avoiding collisions. The proposed method uses convolutional neural networks to learn the control commands based on the visual input. We have demonstrated the feasibility of using a system based only on vision to learn specific strategies of navigation with 80% accuracy on the prediction of control command changes. Experimental results and a detailed overview of the proposed method are discussed.



2014 ◽  
Author(s):  
Chi Ngo ◽  
Nora Newcombe ◽  
Ingrid Olson ◽  
Steven Weisberg


ROBOT ◽  
2011 ◽  
Vol 33 (4) ◽  
pp. 490-501 ◽  
Author(s):  
Xinde LI ◽  
Xuejian WU ◽  
Bo ZHU ◽  
Xianzhong DAI


2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Abdallah Daddi-Moussa-Ider ◽  
Hartmut Löwen ◽  
Benno Liebchen

AbstractAs compared to the well explored problem of how to steer a macroscopic agent, like an airplane or a moon lander, to optimally reach a target, optimal navigation strategies for microswimmers experiencing hydrodynamic interactions with walls and obstacles are far-less understood. Here, we systematically explore this problem and show that the characteristic microswimmer-flow-field crucially influences the navigation strategy required to reach a target in the fastest way. The resulting optimal trajectories can have remarkable and non-intuitive shapes, which qualitatively differ from those of dry active particles or motile macroagents. Our results provide insights into the role of hydrodynamics and fluctuations on optimal navigation at the microscale, and suggest that microorganisms might have survival advantages when strategically controlling their distance to remote walls.



Author(s):  
Zhenhuan Rao ◽  
Yuechen Wu ◽  
Zifei Yang ◽  
Wei Zhang ◽  
Shijian Lu ◽  
...  


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