International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 07 Issue: 03 | Mar 2020 www.irjet.net p-ISSN: 2395-0072 © 2020, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 21 Autonomous Eviscerating BOT using ANT Colony Optimization Adnan Mukhtar 1 , Farhan Mukhtar 2 1 Electrical and Electronics Engineering Department, Amity University Uttar Pradesh, Noida, 201303, India 2 Automobile Engineering Department, Manav Rachna International Institute of Research and Studies Faridabad, Haryana, 121004, India -------------------------------------------------------------------------***------------------------------------------------------------------------ Abstract-Autonomous grid/ obstacle solving robot counters a number of problems related to tracking and planning of path that consumes the least time and energy in real-world phenomena. Ant colony optimization (ACO) is used to track and optimize the shortest path used by various robots like ASIMO (Advanced Step in Innovation and Mobility) which is made by Honda for reducing human efforts. ACO and Artificial Intelligence (AI) is used to attain the best results. In this paper, a system is proposed which uses ACO and reduces human efforts by finding energy and time-efficient solution. The aim is to try to counter one such kind of problem that is not to follow the same path. In this paper, a BOT is proposed that works on two autonomous systems that are used for cleaning purposes in the industry and other public places like malls, etc. These two BOTs will be using their separate path with the help of the ACO algorithm and will be in touch with each other through a communication medium. Key Words: Ant Colony Optimization (ACO), Artificial Intelligence (AI), Communication, Robotics 1. INTRODUCTION A system is proposed that uses ACO and reduces time and energy efficiently and gives us an optimal solution for real- world problems in the field of robotics and Artificial Intelligence [3], [4]. A small prototype proposed on edge/ obstacle avoiding BOT that will learn from its previous experiences (the previous path followed) as well from its surrounding robots that will simplify many human efforts example: People go to a mall and they have 4-5 people at least for cleaning the floors. To reduce human interference in such kind of a system and this cleaning task can be done by simply installing two BOTs on a floor, these BOTs will clean the floor as well as the sensors installed on that will avoid the obstacles as well as edges [4],[7]. These two BOTs will be communicating and interchanging the information (optimal path) and reduce time and energy efficiently [1]. This paper consists of five sections. Section 2 describes Methodology and Working, Section 3 explains the Algorithm and Approach, Section 4 explains the Shortest Path Iteration Technique and Section 5 discusses the Conclusion. 2. METHODOLOGY AND WORKING 2.1 ANT Colony Optimization Algorithm (ACO) ACO is a technique in robotics to optimize the shortest path between two paths A and B, build from a combination of several paths, this algorithm is derived from watching the behavior of ants in the real world to find food [6]. In this technique, ants secrete a special kind of liquid called “pheromone” which is used to track the path for finding food. Once an optimal path is being found by avoiding all kinds of obstacles and other constraints, the maximum No. of ants follows the same path, so the pheromone level gets thicker. This results in attaining an optimal solution to a real-world problem by ants. 2.2 Working In this proposed system, ACO is applied for making a robot that will be used for cleaning purposes in commercial buildings [8]. There will be two BOTs that ar e interconnected wirelessly for efficient cleaning of the floor. The two BOT’s will intercommunicate with each other for getting time and energy-efficient cleaning system. Suppose BOT A has followed a path and has cleaned it then it will avoid that path and will be cleaning a different path. Here both the BOT’s will be avoiding obstacles like humans, walls, staircases, etc. which are commonly present in our day-to-day workplaces [2], [9], [10]. 2.3 Block Diagram The block diagram shown in Fig. 1 and Fig. 2 represents two sides where each side is a separate autonomous unit. Each side has a sensor unit, controller unit, motors and a transceiver. These units will be helping us to clean the floors of our workplace. Each unit has its importance, coming to the first unit as a sensor unit. Here I will be using mainly two types of sensors; a color sensor for detection of the area and three ultrasonic sensors for the detection of obstacles. Before the installation of this system different colors need to be used to distinguish between the area defined which will be acting as a pheromone for the BOTs. An ultrasonic sensor senses the obstacle and the edges to avoid any sort of collision. The controller unit will be used for all sorts of computation and other controlling