Where Am I? Autonomous Navigation System of a Mobile Robot in an Unknown Environment (original) (raw)

Implementation of Autonomous Navigation Algorithms on Two-Wheeled Ground Mobile Robot

American Journal of Engineering and Applied Sciences, 2014

This study presents an effective navigation architecture that combines 'go-to-goal', 'avoid-obstacle' and 'follow-wall' controllers into a full navigation system. A MATLAB robot simulator is used to implement this navigation control algorithm. The robot in the simulator moves to a goal in the presence of convex and non-convex obstacles. Experiments are carried out using a ground mobile robot, Dr Robot X80SV, in a typical office environment to verify successful implementation of the navigation architecture algorithm programmed in MATLAB. The research paper also demonstrates algorithms to achieve tasks such as 'move to a point', 'move to a pose', 'follow a line', 'move in a circle' and 'avoid obstacles'. These control algorithms are simulated using Simulink models.

Simulation of a mobile robot navigation system

2011

Mobile robots are used in various application areas including manufacturing, mining, military operations, search and rescue missions and so on. As such there is a need to model robot mobility that tracks robot system modules such as navigation system and vision based object recognition. For the navigation system it is important to locate the position of the robot in surrounding environment. Then it has to plan a path towards desired destination. The navigation system of a robot has to identify all potential obstacles in order to find a suitable path. The objective of this research is to develop a simulation system to identify difficulties facing mobile robot navigation in industrial environments, and then tackle these problems effectively. The simulation makes use of information provided by various sensors including vision, range, and force sensors. With the help of battery operated mobile robots it is possible to move objects around in any industry/manufacturing plant and thus minimize environmental impact due to carbon emissions and pollution. The use of such robots in industry also makes it safe to deal with hazardous materials. In industry, a mobile robot deals with many tools and equipment and therefore it has to detect and recognize these objects and then track them. In this paper, the object detection and recognition is based on vision sensors and then image processing techniques. Techniques covered include Speeded Up Robust Features (SURF), template matching, and colour segmentation. If the robot detects the target in its view, it will track the target and then grasp it. However, if the object is not in the current view, the robot continues its search to find it. To make the mobile robot move in its environment, a number of basic path planning strategies have been used. In the navigation system, the robot navigates to the nearest wall (or similar obstacle) and then moves along that obstacle. If an obstacle is detected by the robot using the built-in ultrasonic range sensor, the robot will navigate around that obstacle and then continue moving along it. While the robot is self-navigating in its environment, it continues to look for the target. The robot used in this work robot is scalable for industrial applications in mining, search and rescue missions, and so on. This robot is environmentally friendly and does not produce carbon emissions. In this paper the simulation of path planning algorithm for an autonomous robot is presented. Results of modelling the robot in a real-world industrial environment for testing the robot's navigation are also discussed.

AN INTEGRATED APPROACH FOR AUTONOMOUS NAVIGATION OF A DIFFERENTIAL-DRIVE MOBILE ROBOT

This paper concerns with the problem of autonomous navigation in indoor environments of a differential-drive mobile robot using information for its localization obtained from onboard sensors. First, the robot architecture is presented and a kinematic model appropriate for control applications is derived. An integrated approach using combined information from encoders and ultrasonic sensors is presented in order to perform indoor navigation (corridor following and wall following). A minimum-time optimal control law is designed to stabilize the motion of the robot along the reference path. Simulation and experimental results are presented in order to evaluate the proposed control scheme.

Intelligent Autonomous Navigation System for the Wheeled Mobile Robot

Advanced Materials Research, 2011

An intelligent behavior control system for an autonomous mobile robot operating in an unstructured environment with sensor uncertainties is proposed. This study focuses on implementing and improving the methodology from Motlagh et al. [7] on a two-wheeled P3DX mobile robot. Motlagh et al. verified their design with computer simulation. When applying it on a real robot platform, we noticed some problems and improved the design using sensor selection strategy, safe rule and target switching strategy. The proposed sensor fusion architecture introduces two additional sensors, a laser range finder on the robot and an omnidirectional CCD camera on the ceiling, to improve the reliability of the sensing capability of P3DX mobile robot. The target switching strategy is used to guide the robot out of a dead zone and reach the target by creating a virtual target. Results of the experiments with the U-shaped and subspace dead zones are presented. These results proved that the target switching s...

Features of the Construction and Control of the Navigation System of a Mobile Robot

The use of robots is one of the promising areas for development in various industries, human activities. Mobile robots are of particular importance. These robots are able to replace humans in difficult and dangerous situations. Mobile robots are able to perform any tasks that have different levels of difficulty. An important element of mobile robots is the navigation system and the management of such a system. The navigation control system of a mobile robot determines the possibilities of using such a robot. This necessitated the importance of considering the features of the construction and control of the navigation system of a mobile robot. The paper highlights the key features of this consideration.

A REVIEW ON WHEELED MOBILE ROBOT USING DIFFERENT NAVIGATION TECHNIQUES

2024

Mobile robots are autonomous agents capable of intelligent navigation anywhere Using sensor actuator control technology. Autonomous application Mobile robots that are active in many fields such as industry, space, defense, transportation, etc., and other social sectors are growing day by day. Mobile robots do many things rescue operations, patrols, disaster relief, and planetary exploration, That's why we need intelligent mobile robots. It can move autonomously in various static and dynamic environments. Several techniques have been applied to mobile robots by various researchers. Navigation and obstacle avoidance. In this article, Intelligent navigation technology can navigate mobile robots Autonomously in static and dynamic environments. Navigating robots in obstacle-filled environments remains a challenge. This work describes the navigational difficulties of WMRs (wheeled mobile robots). WMR navigation mechanisms and strategies to address sub-problems are mappings, localization, and path planning. Planning can be used in all aspects of robot navigation. We will discuss some existing approaches. Accurate robot navigation is very important in agriculture applications. You have to deal with many activities in a complex agricultural environment. Focusing on the complexity of specific agricultural environments, this study anticipates the use of answers to WMR navigation problems in agricultural engineering and demonstrates that this project aims to address the challenges of precise navigation in agricultural areas. This paper presents a rigorous survey of mobile robot navigation techniques used so far. Here, a stepwise investigation of classical and reactive approaches is undertaken to understand the development of pathway planning strategies under different environmental conditions and to identify research gaps. Classical approaches such as cell decomposition (CD), roadmap approach (RA) and artificial potential field (APF). Genetic Algorithm (GA), Fuzzy Logic (FL), Neural Network (NN), Firefly Algorithm (FA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Bacteria Search Optimization (BFO), Artificial Reactive approaches such as Bee Colony (ABC), Cuckoo Search (CS), Shuffled Frog Leap Algorithm (SFLA), and other miscellaneous algorithms (OMA) are under study.

Design and implementation of a navigation system for autonomous mobile robots

International Journal of Ad Hoc and Ubiquitous Computing, 2010

The robotic navigation system is one of the most important and fundamental components of the successful robots. A navigation system of a robot is the key to the excellent motion of the robot. In this thesis, a navigation system for autonomous mobile robot is proposed. Our navigation system is a hybrid of behavior-based and model-based navigation systems. In our system, behavior-based subsystem is in charge of low-level reactive actions, and model-based subsystem is responsible for high-level planned actions. Besides, our system can communicate with wireless sensor network and utilize the localization technology of wireless sensor network to calibrate the estimated position of the robot. When the robot is going to leave for a destination, our system will utilize model-based subsystem to compute a path from the robot to the destination. Then, it divides this path into many virtual points, and the behavior-based subsystem is going to approach each virtual point in turn. If there are some obstacles in the way, the navigation system will use our obstacle avoidance algorithm to avoid these obstacles and keep the robot toward the destination. Therefore, our robot will arrive at the destination correctly. Furthermore, we use multi-thread technology to establish our navigation system. Thus, our system can run important modules concurrently and can utilize the multi-core processor more efficiently. Based on our experimental results, our navigation system can navigate the robot in the passages with obstacles effectively and would be applied extensively.

Mobile robot navigation with distance control

2012 International Conference of Robotics and Artificial Intelligence, 2012

Intelligent systems to increase the road safety have been widely applied in the automotive sector; similarly, they have critical importance in the robotics to navigate the robot safely. Automatic distance control system helps to avoid collision between vehicles. In this paper, we present an algorithm to maintain a distance between the robot and the object. It keeps the autonomous mobile robot at a safe distance from the object. It is implemented in a wheeled mobile robot to track the moving object. The surrounding information is obtained through the range sensors that are mounted at the front side of the robot. The central sensor gives instructions for the forward and backward motion, and the other sensors help for the left and right motion. To avoid collision, safety distance, which makes the movement easy in the out of range, stop, and forward and backward modes, is predefined in the mobile robot. Each time the range data is compared with the predefined distance measurements, and the respected function is activated. The robot is characterized due to low cost and simple control architecture. Different experiments were carried out in the indoor and outdoor environments with different objects. The results have shown that the robot tracks the object correctly by maintaining a constant distance from the followed object.