scholarly journals Design and simulation of disaster mitigation robot using machine vision

2021 ◽  
Vol 2115 (1) ◽  
pp. 012009
Author(s):  
M Avinaash ◽  
D Andrew ◽  
S Visnu ◽  
M Abrar ◽  
N Seenu
Keyword(s):  
Artificial Intelligence ◽  
Path Planning ◽  
Mobile Robot ◽  
Search And Rescue ◽  
Disaster Mitigation ◽  
High Definition ◽  
Life And Death ◽  
Autonomous Operation ◽  
Remote Operation ◽  
The Difference

Abstract The goal is to provide a robust mobile robot to assist recures in their operation by providing real time surveillance, remote operation as well autonomous operation. The mobile robot is capable of mapping using a LIDAR, this provides a map of the disaster zone which is then used to assess and provide a path planning for the most efficient rescue for the Mobile robot as well as the Rescuers. The built-in gas sensor reads the concentration of gases in the area, providing data on the environment in the disaster zone. The use of high definition cameras combined with Artificial Intelligence based image classification provides an edge in autonomous traversing and search and rescue. Disaster mitigation is an extremely dangerous task for the rescuers, a mobile robot such as LV-01 can be the difference between life and death.

scholarly journals Robots to the Rescue

2019 ◽  
Vol 141 (03) ◽  
pp. 30-35 ◽  
Author(s):  
Lina Zeldovich
Keyword(s):  
Search And Rescue ◽  
Life And Death ◽  
The Difference ◽  
New Generation

Robots are becoming increasingly important responders, joining search and rescue teams in their missions. Besides being able to traverse contaminated and dangerous areas, these robots bring a different set of skills to disaster recover site. A new generation of robots is being developed that could quite literally be the difference between life and death in search and rescue operations. This article discusses land, aerial, and aquatic robots in different stages of their training to assist humans in various calamities.

scholarly journals Toward safe and stable time-delayed mobile robot teleoperation through sampling-based path planning

Robotica ◽  
2011 ◽  
Vol 30 (3) ◽  
pp. 351-361 ◽  
Author(s):  
Jorge Nieto ◽  
Emanuel Slawiñski ◽  
Vicente Mut ◽  
Bernardo Wagner
Keyword(s):  
Artificial Intelligence ◽  
Time Delay ◽  
Path Planning ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Indoor Environments ◽  
Variable Time Delay ◽  
Variable Time ◽  
Prediction Module ◽  
Path Planner

SUMMARYThis work proposes a teleoperation architecture for mobile robots in partially unknown environments under the presence of variable time delay. The system is provided with artificial intelligence represented by a probabilistic path planner that, in combination with a prediction module, assists the operator while guaranteeing a collision-free motion. For this purpose, a certain level of autonomy is given to the system. The structure was tested in indoor environments for different kinds of operators. A maximum time delay of 2s was successfully coped with.

Path Planning for Mobile Robot Search and Rescue Based on Improved Ant Colony Optimization Algorithm

2011 ◽  
Vol 66-68 ◽  
pp. 1039-1044 ◽  
Author(s):  
Yu Feng Ding ◽  
Qian Pan
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Optimization Algorithm ◽  
Ant Colony Algorithm ◽  
Grid Method ◽  
Search And Rescue ◽  
Ant Colony ◽  
Complex Environment ◽  
Ant Colony Optimization Algorithm ◽  
Search Path

Aiming at disasters such as fire, earthquake etc. city disaster complex environment, a robot search path algorithm based on ant colony algorithm is put forward in this paper. Suppose environmental was known, we use grid method to divide and model the whole environment space and put forward some improvement in dead circulation, optimizing parameters, stimulating factors for the basic ant colony algorithm, which improved the ant colony algorithm’s robustness effectively. Finally, we obtain search path through numeric experiments in the simulation rescue scenario and make a comparison with original results. Experiment results show the effectiveness of the proposed algorithm and the improved rationality. It will be a good basis for later path planning research in unknown environment.

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