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

It can be admitted that multi robot systems have better possibilities of success in accomplishing surveillance and rescue missions. In proposed system, a multi robot system based on swarm intelligence is developed which will help in surveillance with real time data uploading on cloud using IoT and perform rescue missions. The objective of this paper is to develop wireless intercommunication between multiple agents so that they perform the given task in synchronized manner and to develop a control strategy for robots using PID technique and further optimizing it using ant colony optimization (ACO) algorithm. The presented system consists of two robots with temperature sensing, fire sensing and hazardous gas sensing features and a hand held device which receives this information and handheld device is incorporated with the NodeMCU unit that upload the data on BLYN app. These robots also have capability of sending live videos using wireless camera. The paper also consists of development of hardware along with simulation results of the system.

[1]  Vijay Singh,et al.  Tuning of PID Controller for Speed Control of DC Motor Using Soft Computing Techniques – A Review , 2014 .

[2]  Tamotsu Kamigaki,et al.  Object‐Oriented RFID with IoT: A Design Concept of Information Systems in Manufacturing , 2017 .

[3]  Feng WeiXing,et al.  Novel Algorithms for Coordination of Underwater Swarm Robotics , 2006, 2006 International Conference on Mechatronics and Automation.

[4]  Marzuki Khalid,et al.  Tuning of a neuro-fuzzy controller by genetic algorithm , 1999, IEEE Trans. Syst. Man Cybern. Part B.

[5]  Jie Lin,et al.  Ultra-Low-Power Design and Hardware Security Using Emerging Technologies for Internet of Things , 2017 .

[6]  Ritu Soni,et al.  Simulation of Optimal Speed Control for a DC Motor Using Conventional PID Controller and Fuzzy Logic Controller , 2006 .

[7]  Liu Yang,et al.  Research on Ant Colony Neural Network PID Controller and Application , 2007, Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007).

[8]  F. Ratnieks,et al.  Communication in ants , 2006, Current Biology.

[9]  Shashank Sultaniya.  Design of PID Controller using PSO Algorithm for CSTR System , 2014 .

[10]  S. Easter Selvan,et al.  Novel Technique for PID Tuning by Particle Swarm Optimization , 2003 .

[11]  Chris Phillips,et al.  Cooperative Path-Planning for Multi-Vehicle Systems , 2014 .

[12]  Pierre Borne,et al.  Tuning PID Controller Using Multiobjective Ant Colony Optimization , 2012, Appl. Comput. Intell. Soft Comput..

[13]  Zhongyang Zheng,et al.  Research Advance in Swarm Robotics , 2013 .

[14]  Patrick Benavidez,et al.  Multi-domain robotic swarm communication system , 2008, 2008 IEEE International Conference on System of Systems Engineering.

[15]  Yang Liu,et al.  Research on Ant Colony Neural Network PID Controller and Application , 2007, SNPD.

[16]  M. Kushwah,et al.  Tuning PID Controller for Speed Control of DC Motor Using Soft Computing Techniques-A Review , 2014 .

[17]  Konstantin Kondak,et al.  Autonomous transportation and deployment with aerial robots for search and rescue missions , 2011, J. Field Robotics.

[18]  Lisa L. Grant,et al.  Collective robotic search using hybrid techniques: Fuzzy logic and swarm intelligence inspired by nature , 2009, Eng. Appl. Artif. Intell..

[19]  Ying-Tung Hsiao,et al.  Ant colony optimization for designing of PID controllers , 2004, 2004 IEEE International Conference on Robotics and Automation (IEEE Cat. No.04CH37508).

[20]  Semuil Tjiharjadi,et al.  Design and Implementation of a Path Finding Robot Using Flood Fill Algorithm , 2016 .

[21]  M. Higgins,et al.  Analysis of Into-Out Wireless Body Area Network Systems : Towards QoS-Aware Health Internet of Things Applications , 2016 .

[22]  Anant Oonsivilai,et al.  Application of Adaptive Tabu Search for Optimum PID Controller tuning AVR System , 2008 .