Smart Animal Detection and Counting Framework for Monitoring Livestock in an Autonomous Unmanned Ground Vehicle Using Restricted Supervised Learning and Image Fusion

2021 ◽  
Vol 53 (2) ◽  
pp. 1253-1285
Author(s):  
S. Divya Meena ◽  
L. Agilandeeswari
Keyword(s):  
Image Fusion ◽  
Supervised Learning ◽  
Unmanned Ground Vehicle ◽  
Ground Vehicle ◽  
Detection And Counting ◽  
Animal Detection

Self-supervised free space estimation in outdoor terrain

Robotica ◽  
2018 ◽  
Vol 36 (9) ◽  
pp. 1278-1300
Author(s):  
Ali Harakeh ◽  
Daniel Asmar ◽  
Elie Shammas
Keyword(s):  
Supervised Learning ◽  
Long Range ◽  
Free Space ◽  
Robot Navigation ◽  
Unmanned Ground Vehicle ◽  
Essential Requirement ◽  
Ground Vehicle ◽  
Second Stage ◽  
Stochastic Framework ◽  
Close Range

SUMMARYThe ability to reliably estimate free space is an essential requirement for efficient and safe robot navigation. This paper presents a novel system, built upon a stochastic framework, which estimates free space quickly from stereo data, using self-supervised learning. The system relies on geometric data in the close range of the robot to train a second-stage appearance-based classifier for long range areas in a scene. Experiments are conducted on board an unmanned ground vehicle, and the results demonstrate the advantages of the proposed technique over other self-supervised systems.

Familiarity and Expertise in the Recognition of Vehicles from an Unmanned Ground Vehicle

2006 ◽  
Author(s):  
Thomas D. Fincannon ◽  
Michael Curtis ◽  
Florian Jentsch
Keyword(s):  
Unmanned Ground Vehicle ◽  
Ground Vehicle

Design and Realization of an All-terrain Unmanned Ground Vehicle

ROBOT ◽  
2013 ◽  
Vol 35 (6) ◽  
pp. 657 ◽  
Author(s):  
Taoyi ZHANG ◽  
Tianmiao WANG ◽  
Yao WU ◽  
Qiteng ZHAO
Keyword(s):  
Unmanned Ground Vehicle ◽  
Ground Vehicle

Testing of Unmanned Ground Vehicle (UGV) Systems

2009 ◽  
Author(s):  
ABERDEEN TEST CENTER MD
Keyword(s):  
Unmanned Ground Vehicle ◽  
Ground Vehicle

Unmanned Ground Vehicle for Security and Surveillance

2020 ◽  
Author(s):  
Prajot P. Kulkarni ◽  
Shubham R. Kutre ◽  
Shravan S. Muchandi ◽  
Pournima Patil ◽  
Shankargoud Patil
Keyword(s):  
Unmanned Ground Vehicle ◽  
Ground Vehicle

scholarly journals Collaborative Pursuit-Evasion Strategy of UAV/UGV Heterogeneous System in Complex Three-Dimensional Polygonal Environment

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Xiao Liang ◽  
Honglun Wang ◽  
Haitao Luo
Keyword(s):  
Visual Field ◽  
Heterogeneous System ◽  
Three Dimensional ◽  
Unmanned Ground Vehicle ◽  
Worst Case ◽  
Ground Vehicle ◽  
Pursuit Evasion ◽  
Evasion Game ◽  
Evasion Strategy ◽  
Aerial Vehicle

The UAV/UGV heterogeneous system combines the air superiority of UAV (unmanned aerial vehicle) and the ground superiority of UGV (unmanned ground vehicle). The system can complete a series of complex tasks and one of them is pursuit-evasion decision, so a collaborative strategy of UAV/UGV heterogeneous system is proposed to derive a pursuit-evasion game in complex three-dimensional (3D) polygonal environment, which is large enough but with boundary. Firstly, the system and task hypothesis are introduced. Then, an improved boundary value problem (BVP) is used to unify the terrain data of decision and path planning. Under the condition that the evader knows the position of collaborative pursuers at any time but pursuers just have a line-of-sight view, a worst case is analyzed and the strategy between the evader and pursuers is studied. According to the state of evader, the strategy of collaborative pursuers is discussed in three situations: evader is in the visual field of pursuers, evader just disappears from the visual field of pursuers, and the position of evader is completely unknown to pursuers. The simulation results show that the strategy does not guarantee that the pursuers will win the game in complex 3D polygonal environment, but it is optimal in the worst case.

Water Hazard Detection Based on 3D LIDAR

2014 ◽  
Vol 668-669 ◽  
pp. 1174-1177 ◽  
Author(s):  
Hai Yan Shao ◽  
Zhen Hai Zhang ◽  
Ke Jie Li ◽  
Jian Wang ◽  
Tao Xu ◽  
...  
Keyword(s):  
Unmanned Ground Vehicle ◽  
Data Format ◽  
Ground Vehicle ◽  
Air Water Interface ◽  
Water Hazard ◽  
Outdoor Environments ◽  
Bodies Of Water ◽  
3D Lidar ◽  
Water Hazards ◽  
Complicated Task

Autonomous off-road navigation is a highly complicated task for a robot or unmanned ground vehicle (UGV) owing to the different kinds of obstacles it could encounter. In-particular, water hazards such as puddles and ponds are very common in outdoor environments and are hard to detect even with ranging devices due to the specular nature of reflection at the air water interface. In recent years, many researches to detect the water bodies have been done. But there still has been very little work on detecting bodies of water that could be navigation hazards, especially at night. In this paper, we used Velodyne HDL-64ES2 3D LIDAR to detect water hazard. The approach first analyzes the data format and transformation of 3D LIDAR, and then writes the data acquisition and visualizations algorithm, integrated data based on ICP algorithm. Finally according the intensity distribution identifies the water hazard. Experiments are carried out on the experimental car in campus, and results show the promising performance.

Analysis of electric machines and drive systems for unmanned ground vehicle applications

2000 ◽  
Author(s):  
Richard W. Wies ◽  
Jerias Mitchell ◽  
Stephen Daniels ◽  
Joseph G. Hawkins
Keyword(s):  
Electric Machines ◽  
Unmanned Ground Vehicle ◽  
Ground Vehicle ◽  
Drive Systems
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