A study on obstacle avoidance in autonomous robot system using robotics system toolbox

In this paper, a TurtleBot, which is an open-source personal research robot platform, will be introduced to create an obstacle avoiding system. To control the robot avoid obstacles, the coordinate data from the laser sensor will be received and calculated the distance from all obstacles to robot for finding the direction of the closest obstacle.

HAPPY NEW YEAR 2018 A STUDY ON OBSTACLE AVOIDANCE IN AUTONOMOUS ROBOT SYSTEM USING ROBOTICS SYSTEM TOOLBOX LUU HOANG MINH Faculty of Electrical and Electronic Engineering, Vietnam Maritime University Abstract In robotics, obstacle avoidance is the task of satisfying some control objective subject to non-intersection or non-collision position constraints Normally obstacle avoidance is considered to be distinct from path planning in that one is usually implemented as a reactive control law while the other involves the pre-computation of an obstacle-free path which a controller will then guide a robot along In this paper, a TurtleBot, which is an open-source personal research robot platform, will be introduced to create an obstacle avoiding system To control the robot avoid obstacles, the coordinate data from the laser sensor will be received and calculated the distance from all obstacles to robot for finding the direction of the closest obstacle Based on that, robot direction control command will be decided by using robotics system toolbox and MATLAB program Keywords: TurtleBot, obstacle avoiding, robotics system toolbox, MATLAB Tóm tắt Trong robot học, tránh chướng ngại vật nhiệm vụ phải thỏa mãn số mục tiêu ràng buộc điều khiển tránh vị trí giao cắt với đối tượng di động tránh va chạm với đối tượng cố định Thông thường, phương pháp tránh chướng ngại vật khác biệt với phương pháp bám quỹ đạo, tránh chướng ngại vật thường thực dạng luật điều khiển phản ứng robot, phương pháp bám quỹ đạo liên quan đến việc tính tốn trước đường robot Trong báo này, tác giả giới thiệu phương pháp điều khiển robot tự hành tránh chướng ngại vật sử dụng TurtleBot Để điều khiển robot tránh chướng ngại, liệu tọa độ từ cảm biến laser robot sử dụng để tính khoảng cách từ tất vật cản đến robot xác định hướng vật cản gần Dựa vào đó, ứng dụng tự động điều khiển robot thay đổi hướng tránh vật cản lập trình cách sử dụng MATLAB chương trình robotics system toolbox MATLAB Từ khóa: TurtleBot, tránh chướng ngại vật, robotics system toolbox, MATLAB Introduction The ability to detect and avoid obstacles quickly is an important design requirement for all application of autonomous robot system In the past, a lot of solutions have been proposed for this problem But most of these solutions demand a heavy computational load, which makes them very difficult and cannot use to control a low-cost robot system This paper presents the results of a research aimed to presented a new method for obstacle avoidance relying on low cost robot with laser sensors, and involving a reasonable level of calculations, so that it can be easily used in real time control applications The Cartesian coordinates signal from laser sensor will be used to calculate distance from robot to all obstacle, and the index number of this signal will decide the signal to control the robot Besides this introduction, the structure of the present paper is as follows: Section introduces about TurtleBot and robot system configuration; Section contains a description of the obstacle avoidance solution to control robot by using signal from laser sensor; Section presents the experimental results used for evaluating the system System configuration TurtleBot is a low-cost, personal robot kit with open-source software With TurtleBot, we can build a robot that can drive around our house or our office, and have enough horsepower to create exciting applications [1] Journal of Marine Science and Technology No 53 - January 2018 15 HAPPY NEW YEAR 2018 The Figure shows the TurtleBot of Willow Garage TurtleBot is an open source hardware project as described by the Open Source Hardware Statement of Principles and Definition v1.0 Open source hardware is hardware whose design is made publicly available so that anyone can study, modify, distribute, make, and sell the design or hardware based on that design The hardware's source, the design from which it is made, is available in the preferred format for making modifications to it Ideally, open source hardware uses readily-available components and materials, standard processes, open infrastructure, unrestricted content, and open-source design tools to maximize the ability of individuals to make and use hardware Open source hardware gives people the freedom to control their technology while sharing knowledge and encouraging commerce through the open exchange of designs Hardware of TurtleBot is shown as following table Figure TurtleBot of Willow Garage Table TurtleBot technical specifications MOBILE BASE AND POWER BOARD Platform: Yujin Kobuki Battery: Up to 4400mAh Ni-lon User Power: 5V and 19V at 1A 12V at 1.5A 12V at 5A TURTLEBOT HARDWARE Mechanical: Mounting hardware TurtleBot structure Module Plate with inch spacing hole pattern Electrical: Modified Kinect cable for Kokuki access ON-BOARD 3D SENSING Sensor: ASUS Xtion PRO Specs: 640x480 @ 30 frames/sec Range: 0.8 - 3.5m Gyro: 110 degrees/sec, Factory Calibrated ON-BOARD NETBOOK Processors: Intel Core i3-4010U Memory: 4G HDD: 500GB Connectivity: USB, Wi-Fi, Ethernet,VGA, HDMI, SD card The robotic software of TurtleBot includes Ubuntu OS and Robotic operation system (ROS) ROS is a collection of software frameworks for robot software development There are more than 2,000 packages, going from diverse robotic platforms, and passing from hardware drivers to many computer algorithms ROS is a collection of tools, libraries, and conventions that aim to simplify the task of creating complex and robust robot behavior across a wide variety of robotic platforms Figure showed the hardware diagram In Figure Hardware diagram TurtleBot, the net-book is connected with Kobuki base and Kinect sensors by USB cables Kinect sensor contains a laser sensor, it measures the coordinates of obstacle When battery is low, robot can charge by direct power cable or through docking station To control TurtleBot, a master computer (host) is used The host and TurtleBot must be connected to the same wireless local area network There are two methods to control TurtleBot: 16 Journal of Marine Science and Technology No 53 - January 2018 HAPPY NEW YEAR 2018  The host is installed Ubuntu OS and ROS;  The host uses Window OS and MATLAB program with Robotics system toolbox In this research, the second method is used to build an application of obstacle avoiding system Obstacle avoidance algorithm This part introduces an obstacle avoidance algorithm to control TurtleBot The data from laser sensor [2÷4] is used to control robot for avoiding obstacles The coordinate data from the sensor will be received by net-book of TurtleBot After that, this data will be send to the host to calculate the distance of all obstacles to the robot and obtain the minimum distance and index of minimum and maximum distances If the minimum distance is bigger than a fix distance, which is called threshold distance, the robot will move forward If the minimum distance is smaller than threshold, the robot will turn with spin and back up slight velocities The process will be repeated until the robot has other order Table Laser sensor specification Range 110 degrees with minimum distance is 50 cm Data type Array (Cartesian coordinates of obstacle) Size of data Over 500 scan points (depend on material of obstacle) Table and Figure showed the laser sensor specification Because the laser sensor cannot detect a near distance object, about 20 cm from the robot to object, so in our program, the threshold distance is 30cm, it means that when the robot moves to obstacle with distance from laser sensor to obstacle is 30 cm, the robot will turn to other direction The distance from sensor to obstacle can be calculated as following: distance = √x2 +y2 (1) where, x and y is Cartesian coordinates of obstacle Besides that, the index of laser data increases from right position to left position, so the obstacle avoiding program has three cases as follows: Case 1: The robot approaches to obstacle from the right side (Figure 4) In this case the minimum distance index is smaller than the maximum distance index; the robot will be controlled to turn to the left side Figure Laser data indexes Figure The robot approaches to obstacle from right side Case 2: The robot approaches to obstacle from the left side (Figure 5) In this case the minimum distance index is bigger than the maximum distance index; the robot will be controlled to turn to the right side Case 3: The robot moves to the corner (Figure 6) In this case the maximum distance index is in the middle range of data size; the robot will be controlled to turn to the left side with big angle Figure The robot approaches to obstacle from left side Journal of Marine Science and Technology Figure The robot moves to the corner No 53 - January 2018 17 HAPPY NEW YEAR 2018 An obstacle avoidance program was created with three cases above The Figure shows the flowchart of obstacle avoidance program Begin Begin Enter Enter TurtleBot TurtleBot IP IP address address Define Define parameter parameter for for obstacle obstacle avoiding avoiding (Angular (Angular velocity; velocity; forward forward velocity; velocity; Backward Backward velocity; velocity; Distance Distance threshold) threshold) Initialize Initialize ROS ROS (Connect (Connect to to the the TurtleBot) TurtleBot) Create Create aa publisher publisher for for the the robot's robot's velocity velocity and and create create aa message message for for velocity velocity robot robot == rospublisher('/mobile_base/commands/velocity'); rospublisher('/mobile_base/commands/velocity'); velmsg velmsg == rosmessage(robot); rosmessage(robot); Subscribe Subscribe to to the the topic topic /scan /scan laser laser == rossubscriber('/scan'); rossubscriber('/scan'); Receive Receive scan scan data data scan scan == receive(laser) receive(laser) Receive Receive coordinates coordinates from from all all obstacle obstacle data data == readCartesian(scan) readCartesian(scan) Compute Compute distances distances from from Robot Robot to to all all obstacles obstacles (dist) (dist) Compute Compute size size of of distances distances data data (n) (n) Compute Compute distance distance of of the the closest closest (MinDist) (MinDist) and and farest farest (MaxDist) (MaxDist) obstacles obstacles and and data data indexes indexes (Minindex, (Minindex, Maxindex) Maxindex) of of thore thore distances distances Closest Closest distance distance MinIndex MaxIndex>MinIndex (Robot (Robot moves moves to to obst obst from from right right side) side) Control Control robot robot back back up up slightly slightly and and left left spin spin with with Angular Angular velocity velocity Control Control robot robot back back up up slightly slightly and and right right spin spin with with negative negative Angular Angular velocity velocity Stop? Stop? End End Figure The flowchart of obstacle avoidance algorithm The control signal is created by using MATLAB program and tranfer to robot base on wifi network After communication between robot and the host succeeded, the TurtleBot can be controlled by publishing a message For example, the linear velocity is controlled by typing following commands [5]: 18 Journal of Marine Science and Technology No 53 - January 2018 HAPPY NEW YEAR 2018 robot = rospublisher('/mobile_base/commands/velocity') velmsg = rosmessage(robot) velmsg.Linear.X = 0.1; % meters per second send(robot,velmsg); Experimental result (a) The robot moves to the obstacle (b) The robot turn to other direction (c) Image from robot’s camera Figure TurtleBot avoids the wall Figure shows the way the robot escapes the corner When the distance between laser sensor and the door is 30 cm and the maximum distance index is in the middle range of data index, the robot will automatic change its direction following the red line The second obstacle is the wall The robot also avoids the wall perfect with the direction is the red line in Figure (a) The robot moves to corner (b) The robot finds the way to escape (c) Image from robot’s camera Figure 8.TurtleBot escapes the corner Journal of Marine Science and Technology No 53 - January 2018 19 HAPPY NEW YEAR 2018 Conclusion This paper presented the obstacle avoidance method using signal of laser sensor From above results these following conclusion are given: (1) The method demands very low computational load, and can be implemented on low-cost autonomous robot and can be easily adapted for other sensors, like sonar sensors, infrared sensors; (2) The robot could avoid any kind of static obstacles, and even some moving obstacles with low velocity; (3) The robot performs very well on narrow zone (Figure 8); (4) The method can be combined with some control theory such as fuzzy logic control or neural networks, etc., to control robot more smoothly and exactly REFERENCES [1] Willow Garage, “TurtleBot”, URL: http://turtlebot.com [2] MediaWiki, "OpenKinect", URL: http://www.openkinect.org, 2013 [3] Ayrton Oliver, Steven Kang, Burkhard C Wünsche, Bruce MacDonald, "Using the Kinect as a Navigation Sensor for Mobile Robotics", IVCNZ ’12, Dunedin, New Zealand, November 2012 [4] K Khoshelham “Accuracy Analysis of Kinect Depth Data” In ISPRS Workshop Laser Scanning, volume 38, 2011 [5] Luu Hoang-minh, Park Young_san “A study on TurtleBot Controll using Matlab Program”, The Korean Society of Marine Engineering, 10/2015 Received: Revised: Accepted: 20 10 January 2018 22 January 2018 28 January 2018 Journal of Marine Science and Technology No 53 - January 2018 ... rossubscriber('/scan'); Receive Receive scan scan data data scan scan == receive(laser) receive(laser) Receive Receive coordinates coordinates from from all all obstacle obstacle data data == readCartesian(scan)... distance distance of of the the closest closest (MinDist) (MinDist) and and farest farest (MaxDist) (MaxDist) obstacles obstacles and and data data indexes indexes (Minindex, (Minindex, Maxindex)... obstacle avoiding system Obstacle avoidance algorithm This part introduces an obstacle avoidance algorithm to control TurtleBot The data from laser sensor [2÷4] is used to control robot for avoiding