Multi-Robot Motion Planning with Communication A thesis submitted to the Graduate School of University of Cincinnati In the partial fulfillment of the requirements for the degree of Master of Science In the Department of Electrical and Computer Engineering Of the College of Engineering and Applied Science By Harmandeep Kaur Buttar Thesis Advisor and Committee Chair: Dr. Raj Bhatnagar Abstract A successful motion planning algorithm was designed and implemented on multiple high performance KheperaIII robots. 2 KheperaIII robots finds a dynamic path from the specified source to the targeted destination avoiding collisions in an unpredictable environment processing real-time data exchanged within robots by distributed communication on a well-spaced grid where boundaries are used as landmarks ascertained by the infrared sensors. Distributed communication was implemented by implementing server and client on every robot in the system with the help of multi-threads. This algorithm hence, is successful implementation in the field of motion planning and coordination with autonomous robots. Also in this thesis, is explained the centralized and decoupled behavior of the motion planning algorithms on the multi robots. The implementation of the algorithm over KheperaIII robots aimed at representing the successfulness of this technique in practical cases, as the work in this field is still relatively new. i ii Acknowledgements I would like to take this opportunity to express my gratitude to my thesis advisor, Dr. Raj Bhatnagar, whose guidance, encouragement and patience, inspired me to work on this project. I am extremely grateful to him for his support and co-operation which helped me in successfully completing my Master’s degree. I would also like to thank Dr. Carla Purdy and Dr. Manish Kumar for their presence on my thesis committee. I would also like to thank Robert Montjoy for his technical support in the research lab. Most importantly, I would like to thank my family and friends for their love and support. I would like to dedicate this work to them. iii Table of Contents Abstract…..…………………………………………………………….………….....…….i Acknowledgements……….………………….…………………..…………….………...iii Table of Contents……...………...………………………………….….........…...............iv List of figures…….………………………….…………………........………...………….vi Chapter 1. Introduction …………………………..……………………………………....1 1.1 Introduction…………………………………………………………….…………1 Chapter 2. Literature Review……………………………………………………………...6 2.1 Background…………………………………………..……………………............6 2.2 Introduction to Multi-Robot Motion Planning………………………………….....7 2.3 Technical Specifications for KheperaIII Robot…………………………………...8 Chapter 3. Algorithm……………………..……………………………………..….……10 3.1 Terminology Used..………….……..………………….……………………...…10 3.2 Assumptions made…………………………….………………….…...………....11 3.3 Motion Logic for the Robots……………………………………………………..12 3.4 Real-Time Distributed Communication………………………………………….13 3.5 Implementation of Real Time Communication………………………………….14 3.6 Pseudo-Code of the Algorithm…………………………………………………..15 Chapter 4. Results and Analysis…………………………………………………………22 Chapter 5. Conclusions and Future Work………………………………………………..26 5.1 Comparing Approaches……………………………………………………………...26 iv Bibliography ………………………………………………………………….……………30 v List of Figures Figure 1. Representation of the directions assigned in workspace………………………………12 Figure 2. Communication among robots sharing their real time position information………….14 Figure 3.The simple path taken by the robot from the specified source to the specified destination in workspace free of obstacles…………………………………………………………………...22 Figure 4. Movement of the multi-robot on the workspace with dynamic obstacles……………..24 Figure 5. Movements of multi-robot on the workspace with dynamic obstacles…………….28 vi Chapter 1: Introduction 1.1. Introduction This thesis addresses the problem of adjusting paths of robots in response to non-stationary obstacles encountered when the robots are following their paths towards their goal locations. We solve this problem in the context of distributed decision making, that is, when there is no central agent making plans for each of the robots. Also, some centralized agent does not inform the robots of their current locations, but each robot keeps track of its current location by counting the grid marks as it travels on a marked terrain. This situation is a simplified model for situations in which the robots determine their locations based only on local landmarks. We show in this thesis that our algorithm can achieve this goal in the context of two Khepera robots traversing a terrain marked by grid lines. The main problem that we address is of two robots starting from their starting cells on the grid and seeking to trade places by moving to each other’s location. On the way they seek to avoid running into each other. The collision avoidance is done only when the two robots are about to move into the same grid cell at the same time. Our focus is on developing a generalizable algorithm that can easily be adapted to many other similar situations. The path planning and collision avoidance algorithms defined in this thesis are executed in a distributed manner. We can state the difference between Centralized and Decentralized approaches by defining basic differences between these approaches as follows: 1. Centralized Approach: This approach, as name suggests, has a centralized approach to decision making. Every entity performs work based on decisions made by the central entity. The centralized approach has an advantage of completeness and global optimization, but a major disadvantage lies in high dimensional configuration spaces becoming computationally intensive [12]. 1 2. Decentralized Approach: This approach unlike centralized, is distributed in nature where decision-making is distributed among all the entities present in the system. They perform better in high dimensional configuration space systems. This algorithm implementation involves planning a trajectory from the source to the destination on a 2-dimensional grid, for two Khepera-III robots, and appropriately updating it based on the communication among the robots about their current locations and plans for movement in the immediate future. Robots use decentralized approach to path planning and collision avoidance by making their own decisions to reach from their source to destination locations avoiding the dynamic obstacles encountered along the way. The algorithm is tested for only two robots in this thesis but the approach is generalizable for more robots trying to achieve similar goals. Distributed artificial intelligence is an attractive field of research which deals with making machines perform intelligent tasks based on cooperative exchange of required information. Making multiple machines learn and imitate human intelligence and cooperative behavior while performing tasks is a challenging research topic and this thesis addresses a small problem in this direction. The field of artificial intelligence is characterized as :“The central problems of AI include such traits as reasoning, knowledge, planning, learning, communication, perception and the ability to move and manipulate objects” [1]. All these problems lead to the task of integrating artificial intelligence algorithms with the machines, to make the machines think and perform in the same manner as humans would perform under the given circumstances. The field of Distributed Artificial Intelligence aims to make groups of cooperative machines intelligent by sharing minimum requisite information among them about a specific task and then performing in a similar or superior fashion as compared to a group of cooperating humans. Such 2 intelligent groups of robots or autonomous agents are very useful in various applications such as industrial plants, space exploration, defense situations, and domestic chores. Recent commercial and research popularity of the autonomous and humanoid robots has directly hinted on the emphasis being placed upon the improvement of overall functionality of intelligent robots and their cooperative groups. One important area for autonomous robots is trajectory planning algorithms and obstacle avoidance during navigation, which is also an important research problem [13]. Navigation is an integral part of the autonomous robots for making coordinated movements of the robots possible. Path planning algorithms are designed to navigate the robots efficiently along the shortest possible paths in an unknown or known environment. One of the extensively studied problems in this area is the real time path planning of the robots with collision avoidance. This thesis addresses the path planning problems as real time problems to be solved, with our algorithm designed to keep the two robots from colliding while navigating along their paths. The path planning algorithms are designed based on a number of different types of criteria. The cost of the path taken to move from the source to the destination is one of the important criteria in path planning algorithms. Some of the real world applications which require and need to employ these algorithms include: Manufacturing floor: Manufacturing floor control is one such system where several "intelligent" entities work together to achieve a global manufacturing work instead of a central controller assigning jobs to these individual entities to achieve the respective result. The overall system links various machine tools/entities by different makers. Computers are embedded in this system to help