Overview of Search and Rescue from Robotics to Wireless Sensors and Robots Networks

2016 ◽  
Vol 4 (2) ◽  
pp. 16-33 ◽  
Author(s):  
Sarah Allali ◽  
Mahfoud Benchaïba
Keyword(s):  
Wireless Sensors ◽  
Search And Rescue ◽  
Robotic Systems ◽  
Multiple Robots ◽  
Robot System ◽  
Research Challenges ◽  
Open Research ◽  
Robot Systems ◽  
Rescue System ◽  
Multi Robot

In the recent years, many researchers have shown interest in developing search and rescue system composed of one or multiple robots, which have the mission of finding victims and identifying the potential hazards. To enhance the robotic systems there is a growing trend of integrating wireless sensor networks (WSNs) to robots and multi-robot systems, which gives more awareness of the environments. In the first part of this article, the authors present a review of robotic system and their environments in search and rescue systems. Additionally, they explain challenges related to these systems and tasks that a robot or a multi-robot system should execute to fulfil the search and rescue activities. As a second part, the authors expose the system that integrates WSNs with robots and the advantages that brings this latter. In addition, they cite tasks and missions that are achieved in a better way with a cooperation of WSN and robots. Furthermore, the authors expose and discuss the remarkable research, challenges and the open research challenges that includes this cooperation.

Overview of Search and Rescue From Robotics to Wireless Sensors and Robots Networks

2019 ◽  
pp. 1212-1231
Author(s):  
Sarah Allali ◽  
Mahfoud Benchaïba
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensors ◽  
Search And Rescue ◽  
Wireless Sensor ◽  
Multiple Robots ◽  
Robot System ◽  
Research Challenges ◽  
Robot Systems ◽  
Rescue System ◽  
Multi Robot

In the recent years, many researchers have shown interest in developing search and rescue system composed of one or multiple robots, which have the mission of finding victims and identifying the potential hazards. To enhance the robotic systems there is a growing trend of integrating wireless sensor networks (WSNs) to robots and multi-robot systems, which gives more awareness of the environments. In the first part of this article, the authors present a review of robotic system and their environments in search and rescue systems. Additionally, they explain challenges related to these systems and tasks that a robot or a multi-robot system should execute to fulfil the search and rescue activities. As a second part, the authors expose the system that integrates WSNs with robots and the advantages that brings this latter. In addition, they cite tasks and missions that are achieved in a better way with a cooperation of WSN and robots. Furthermore, the authors expose and discuss the remarkable research, challenges and the open research challenges that includes this cooperation.

A Multi-Robot System Using Mobile Agents with Ant Colony Clustering

2010 ◽  
pp. 174-192
Author(s):  
Yasushi Kambayashi ◽  
Yasuhiro Tsujimura ◽  
Hidemi Yamachi ◽  
Munehiro Takimoto
Keyword(s):  
Communication Networks ◽  
Mobile Agents ◽  
Software Agents ◽  
Ant Colony ◽  
Multiple Robots ◽  
Robot System ◽  
Mobile Software ◽  
Robot Systems ◽  
Ant Colony Clustering ◽  
Multi Robot

This chapter presents a framework using novel methods for controlling mobile multiple robots directed by mobile agents on a communication networks. Instead of physical movement of multiple robots, mobile software agents migrate from one robot to another so that the robots more efficiently complete their task. In some applications, it is desirable that multiple robots draw themselves together automatically. In order to avoid excessive energy consumption, we employ mobile software agents to locate robots scattered in a field, and cause them to autonomously determine their moving behaviors by using a clustering algorithm based on the Ant Colony Optimization (ACO) method. ACO is the swarm-intelligence-based method that exploits artificial stigmergy for the solution of combinatorial optimization problems. Preliminary experiments have provided a favorable result. Even though there is much room to improve the collaboration of multiple agents and ACO, the current results suggest a promising direction for the design of control mechanisms for multi-robot systems. In this chapter, we focus on the implementation of the controlling mechanism of the multi-robot system using mobile agents.

Overview of Wireless Sensor Network, Robotics, IoT, and Social Media in Search and Rescue Activities

2018 ◽  
pp. 188-216
Author(s):  
Sarah Allali ◽  
Mahfoud Benchaïba
Keyword(s):  
Social Media ◽  
Search And Rescue ◽  
Decision Makers ◽  
Wireless Sensor ◽  
Multiple Robots ◽  
Robot System ◽  
The Public ◽  
Emergency Situations ◽  
Research Challenges ◽  
Insight Into

In recent years, many researchers have shown interest in developing search and rescue systems composed of one or multiple robots. To enhance the robotic systems, wireless sensor networks and internet of things (IoT) were integrated to give more awareness of the environments. Additionally, data exchanged in social media during emergency situations can help rescuers, decision makers, and the public to gain insight into the situation as it unfolds. In the first part of this chapter, the authors present a review of robotic system and their environments in search and rescue systems. Additionally, they explain the challenges related to these systems and the tasks that a robot or a multi-robot system should execute to fulfil the search and rescue activities. As a second part, the authors expose the systems that integrates WSNs and IoT with robots and the advantages that brings those. Furthermore, they expose and discuss the remarkable research, the challenges, and the open research challenges that include this cooperation.

scholarly journals Robot Swarm Navigation and Victim Detection Using Rendezvous Consensus in Search and Rescue Operations

2019 ◽  
Vol 9 (8) ◽  
pp. 1702 ◽  
Author(s):  
Gustavo A. Cardona ◽  
Juan M. Calderon
Keyword(s):  
Formation Control ◽  
Target Location ◽  
Research Work ◽  
Search And Rescue ◽  
Consensus Algorithm ◽  
Robot System ◽  
Robot Swarm ◽  
Robot Systems ◽  
Swarm Theory ◽  
Multi Robot

Cooperative behaviors in multi-robot systems emerge as an excellent alternative for collaboration in search and rescue tasks to accelerate the finding survivors process and avoid risking additional lives. Although there are still several challenges to be solved, such as communication between agents, power autonomy, navigation strategies, and detection and classification of survivors, among others. The research work presented by this paper focuses on the navigation of the robot swarm and the consensus of the agents applied to the victims detection. The navigation strategy is based on the application of particle swarm theory, where the robots are the agents of the swarm. The attraction and repulsion forces that are typical in swarm particle systems are used by the multi-robot system to avoid obstacles, keep group compact and navigate to a target location. The victims are detected by each agent separately, however, once the agents agree on the existence of a possible victim, these agents separate from the general swarm by creating a sub-swarm. The sub-swarm agents use a modified rendezvous consensus algorithm to perform a formation control around the possible victims and then carry out a consensus of the information acquired by the sensors with the aim to determine the victim existence. Several experiments were conducted to test navigation, obstacle avoidance, and search for victims. Additionally, different situations were simulated with the consensus algorithm. The results show how swarm theory allows the multi-robot system navigates avoiding obstacles, finding possible victims, and settling down their possible use in search and rescue operations.

scholarly journals Research Progress on Synergistic Technologies of Agricultural Multi-Robots

2021 ◽  
Vol 11 (4) ◽  
pp. 1448
Author(s):  
Wenju Mao ◽  
Zhijie Liu ◽  
Heng Liu ◽  
Fuzeng Yang ◽  
Meirong Wang
Keyword(s):  
Path Planning ◽  
Formation Control ◽  
Research Progress ◽  
Hybrid Architecture ◽  
Labor Costs ◽  
Robot System ◽  
System Architectures ◽  
Research Results ◽  
Robot Systems ◽  
Multi Robot

Multi-robots have shown good application prospects in agricultural production. Studying the synergistic technologies of agricultural multi-robots can not only improve the efficiency of the overall robot system and meet the needs of precision farming but also solve the problems of decreasing effective labor supply and increasing labor costs in agriculture. Therefore, starting from the point of view of an agricultural multiple robot system architectures, this paper reviews the representative research results of five synergistic technologies of agricultural multi-robots in recent years, namely, environment perception, task allocation, path planning, formation control, and communication, and summarizes the technological progress and development characteristics of these five technologies. Finally, because of these development characteristics, it is shown that the trends and research focus for agricultural multi-robots are to optimize the existing technologies and apply them to a variety of agricultural multi-robots, such as building a hybrid architecture of multi-robot systems, SLAM (simultaneous localization and mapping), cooperation learning of robots, hybrid path planning and formation reconstruction. While synergistic technologies of agricultural multi-robots are extremely challenging in production, in combination with previous research results for real agricultural multi-robots and social development demand, we conclude that it is realistic to expect automated multi-robot systems in the future.

A Novel Approach With Bayesian Networks to Multi-Robot Task Allocation in Dynamic Environments

2021 ◽  
Author(s):  
Ching-Wei Chuang ◽  
Harry H. Cheng
Keyword(s):  
Bayesian Networks ◽  
Task Allocation ◽  
Low Cost ◽  
Dynamic Environments ◽  
Modern World ◽  
Robot System ◽  
Novel Approach ◽  
Robot Systems ◽  
Robot Task ◽  
Multi Robot

Abstract In the modern world, building an autonomous multi-robot system is essential to coordinate and control robots to help humans because using several low-cost robots becomes more robust and efficient than using one expensive, powerful robot to execute tasks to achieve the overall goal of a mission. One research area, multi-robot task allocation (MRTA), becomes substantial in a multi-robot system. Assigning suitable tasks to suitable robots is crucial in coordination, which may directly influence the result of a mission. In the past few decades, although numerous researchers have addressed various algorithms or approaches to solve MRTA problems in different multi-robot systems, it is still difficult to overcome certain challenges, such as dynamic environments, changeable task information, miscellaneous robot abilities, the dynamic condition of a robot, or uncertainties from sensors or actuators. In this paper, we propose a novel approach to handle MRTA problems with Bayesian Networks (BNs) under these challenging circumstances. Our experiments exhibit that the proposed approach may effectively solve real problems in a search-and-rescue mission in centralized, decentralized, and distributed multi-robot systems with real, low-cost robots in dynamic environments. In the future, we will demonstrate that our approach is trainable and can be utilized in a large-scale, complicated environment. Researchers might be able to apply our approach to other applications to explore its extensibility.

scholarly journals Design and Development of IoT enabled Multi Robot System for Search and Rescue Mission

2018 ◽  
Vol 10 (2) ◽  
pp. 51 ◽  
Author(s):  
Rajesh Singh ◽  
Rohit Samkaria ◽  
Anita Gehlot ◽  
Sushabhan Choudhary
Keyword(s):  
Search And Rescue ◽  
Design And Development ◽  
Robot System ◽  
Rescue Mission ◽  
Multi Robot

Distributed Coordination Architecture for Cooperative Task Planning and Execution of Intelligent Multi-Robot Systems

2015 ◽  
pp. 407-426 ◽  
Author(s):  
Gen'ichi Yasuda
Keyword(s):  
Large Scale ◽  
Discrete Event ◽  
Robotic Systems ◽  
Task Planning ◽  
Distributed Coordination ◽  
Robot Systems ◽  
Concurrent Processes ◽  
Manufacturing Applications ◽  
Robot Cooperation ◽  
Multi Robot

This chapter provides a practical and intuitive way of cooperative task planning and execution for complex robotic systems using multiple robots in automated manufacturing applications. In large-scale complex robotic systems, because individual robots can autonomously execute their tasks, robotic activities are viewed as discrete event-driven asynchronous, concurrent processes. Further, since robotic activities are hierarchically defined, place/transition Petri nets can be properly used as specification tools on different levels of control abstraction. Net models representing inter-robot cooperation with synchronized interaction are presented to achieve distributed autonomous coordinated activities. An implementation of control software on hierarchical and distributed architecture is presented in an example multi-robot cell, where the higher level controller executes an activity-based global net model of task plan representing cooperative behaviors performed by the robots, and the parallel activities of the associated robots are synchronized without the coordinator through the transmission of requests and the reception of status.

Dynamic model based formation control and obstacle avoidance of multi-robot systems

Robotica ◽  
2008 ◽  
Vol 26 (3) ◽  
pp. 345-356 ◽  
Author(s):  
Celso De La Cruz ◽  
Ricardo Carelli
Keyword(s):  
Dynamic Model ◽  
Obstacle Avoidance ◽  
Formation Control ◽  
Inverse Dynamics ◽  
Single Equation ◽  
Model Parameters ◽  
Robot System ◽  
System A ◽  
Robot Systems ◽  
Multi Robot

SUMMARYThis work presents, first, a complete dynamic model of a unicycle-like mobile robot that takes part in a multi-robot formation. A linear parameterization of this model is performed in order to identify the model parameters. Then, the robot model is input-output feedback linearized. On a second stage, for the multi-robot system, a model is obtained by arranging into a single equation all the feedback linearized robot models. This multi-robot model is expressed in terms of formation states by applying a coordinate transformation. The inverse dynamics technique is then applied to design a formation control. The controller can be applied both to positioning and to tracking desired robot formations. The formation control can be centralized or decentralized and scalable to any number of robots. A strategy for rigid formation obstacle avoidance is also proposed. Experimental results validate the control system design.

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