Implementation of an autonomous mobile robot navigation algorithm using C language

Navigation is a major challenge for autonomous, mobile robots. The problem can basically be divided into positioning and path planning. This report basically discusses the study and also work that has been done from previous of the chosen topic, which is Implementation of an Autonomous Mobile Robot Navigation Algorithm using 'C' language. The objective of the project is to develop navigation algorithm for the autonomous mobile robot. After that, implement the navigation algorithm on the mobile robot and without using the external sensor for navigation of the mobile robot to reach the specified point. From the encoder programming to the motor speed control, this project basically focusing on how to control the motor speed movement such as rotation speed, turning speed, turning angle of the robot by controlling the movement of the motor and distance travel or displacement of the mobile robot from initial point to end point through some path that required turning algorithm and forward movement in controlled speed

Sensor Network Based Collision-Free Navigation and Map Building for Mobile Robots

Safe robot navigation is a fundamental research field for autonomous robots including ground mobile robots and flying robots. The primary objective of a safe robot navigation algorithm is to guide an autonomous robot from its initial position to a target or along a desired path with obstacle avoidance. With the development of information technology and sensor technology, the implementations combining robotics with sensor network are focused on in the recent researches. One of the relevant implementations is the sensor network based robot navigation. Moreover, another important navigation problem of robotics is safe area search and map building. In this report, a global collision-free path planning algorithm for ground mobile robots in dynamic environments is presented firstly. Considering the advantages of sensor network, the presented path planning algorithm is developed to a sensor network based navigation algorithm for ground mobile robots. The 2D range finder sensor network is used in the presented method to detect static and dynamic obstacles. The sensor network can guide each ground mobile robot in the detected safe area to the target. Furthermore, the presented navigation algorithm is extended into 3D environments. With the measurements of the sensor network, any flying robot in the workspace is navigated by the presented algorithm from the initial position to the target. Moreover, in this report, another navigation problem, safe area search and map building for ground mobile robot, is studied and two algorithms are presented. In the first presented method, we consider a ground mobile robot equipped with a 2D range finder sensor searching a bounded 2D area without any collision and building a complete 2D map of the area. Furthermore, the first presented map building algorithm is extended to another algorithm for 3D map building

MAZE ROBOT: APPLYING AUTONOMOUS VEHICLE NAVIGATION ALGORITHM WITH EVENT-DRIVEN PROGRAMMING

Autonomous navigation is an eminent feature in robotics as it provides mobile robot with the ability to traverse from one point to another point while avoiding any obstacles that lie within its path. To navigate through a maze with unpredictable routes would be a great challenge as it requires the assistance of an intelligent algorithm. The main objective of this project is to build and program a mini mobile robot that is able to autonomously navigate through a physical maze. The physical maze will comprise of several different configurations to measure the efficiency of the robot. Hardware and software co-design method is used to construct the mobile robot. The basic navigation algorithm was developed using finite state machine (FSM). Event-driven programming method was applied in producing the maze navigation algorithm for the robot

Design and implementation of a real-time autonomous navigation system applied to lego robots

Teaching theoretical concepts of a real-time autonomous robot system may be a challenging task without real hardware support. The paper discusses the application of the Lego Robot for teaching multi interdisciplinary subjects to Mechatronics students. A real-time mobile robot system with perception using sensors, path planning algorithm, PID controller is used as the case to demonstrate the teaching methodology. The novelties are introduced compared to classical robotic classes: (i) the adoption of a project-based learning approach as teaching methodology; (ii) an effective real-time autonomous navigation approach for the mobile robot. However, the extendibility and applicability of the presented approach are not limited to only the educational purpose

Implementation of an autonomous mobile robot navigation algorithm using C language

Navigation is a major challenge for autonomous, mobile robots. The problem can basically be divided into positioning and path planning. This report basically discusses the study and also work that has been done from previous of the chosen topic, which is Implementation of an Autonomous Mobile Robot Navigation Algorithm using 'C' language. The objective of the project is to develop navigation algorithm for the autonomous mobile robot. After that, implement the navigation algorithm on the mobile robot and without using the external sensor for navigation of the mobile robot to reach the specified point. From the encoder programming to the motor speed control, this project basically focusing on how to control the motor speed movement such as rotation speed, turning speed, turning angle of the robot by controlling the movement of the motor and distance travel or displacement of the mobile robot from initial point to end point through some path that required turning algorithm and forward movement in controlled speed

Mobile Robot Path Planning Optimization Based on Integration of Firefly Algorithm and Cubic Polynomial Equation

Mobile Robot is an extremely essential technology in the industrial world. Optimal path planning is essential for the navigation of mobile robots. The firefly algorithm is a very promising tool of Swarm Intelligence, which is used in various optimization areas. This study used the firefly algorithm to solve the mobile robot path-planning problem and achieve optimal trajectory planning. The objective of the proposed method is to find the free-collision-free points in the mobile robot environment and then generate the optimal path based on the firefly algorithm. It uses the A∗ algorithm to find the shortest path. The essential function of use the firefly algorithm is applied to specify the optimal control points for the corresponding shortest smooth trajectory of the mobile robot. Cubic Polynomial equation is applied to generate a smooth path from the initial point to the goal point during a specified period. The results of computer simulation demonstrate the efficiency of the firefly algorithm in generating optimal trajectory of mobile robot in a variable degree of mobile robot environment complexity

Design, Construction, Energy Modeling, and Navigation of a Six-Wheeled Differential Drive Robot to Deliver Medical Supplies inside Hospitals

Differential drive mobile robots have been the most ubiquitous kind of robots for the last few decades. As each of the wheels of a differential drive mobile robot can be controlled, it provides additional flexibility to the end-users in creating new applications. These applications include personal assistance, security, warehouse and distribution applications, ocean and space exploration, etc. In a clinic or hospital, the delivery of medicines and patients’ records are frequently needed activities. Medical personnel often find these activities repetitive and time-consuming. Our research was to design, construct, produce an energy model, and develop a navigation control method for a six-wheeled differential drive robot designed to deliver medical supplies inside the hospital. Such a robot is expected to lessen the workload of medical staff. Therefore, the design and implementation of a six-wheeled differential drive robot with a password-protected medicine carrier were presented. This password-protected medicine carrier ensures that only the authorized medical personnel can receive medical supplies. The low-cost robot base and the medicine carrier were built in real life. Besides the actual robot design and fabrication, a kinematic model for the robot was developed, and a navigation control algorithm to avoid obstacles was implemented using MATLAB/Simulink. The kinematic modeling is helpful for the robot to achieve better energy optimization. To develop the object avoidance algorithm, we investigated the use of the Robot Operating System (ROS) and the Simultaneous Localization and Mapping (SLAM) algorithm for the implementation of the mapping and navigation of a robotic platform named TurtleBot 2. Finally, using the Webot robot simulator, the navigation of the six-wheeled mobile robot was demonstrated in a hospital-like simulation environment

Autonomous navigation framework for a car-like robot

This technical report describes the work done to develop a new navigation scheme for an autonomous car-like robot available at the Mobile Robotics Laboratory at IRI. To plan the general path the robot should follow (i.e. the global planner), a search based planner algorithm, with motion primitives which take into account the kinematic constraints of the robot, is used. To actually execute the path and avoid dynamic obstacles (i.e the local planner) a modification of the DWA algorithm is used, which takes into account the kinematic constraints of the ackermann configuration to generate and evaluate possible trajectories for the robot. The whole navigation scheme has been integrated into the ROS middleware navigation framework and tested on the real robot and also in a simulator.Peer reviewe

High accuracy mobile robot positioning using external large volume metrology instruments

A method of accurately controlling the position of a mobile robot using an external large volume metrology (LVM) instrument is presented in this article. By utilising an LVM instrument such as a laser tracker or indoor GPS (iGPS) in mobile robot navigation, many of the most difficult problems in mobile robot navigation can be simplified or avoided. Using the real-time position information from the laser tracker, a very simple navigation algorithm, and a low cost robot, 5mm repeatability was achieved over a volume of 30m radius. A surface digitisation scan of a wind turbine blade section was also demonstrated, illustrating possible applications of the method for manufacturing processes. Further, iGPS guidance of a small KUKA omni-directional robot has been demonstrated, and a full scale prototype system is being developed in cooperation with KUKA Robotics, UK. © 2011 Taylor & Francis