Conference Paper

Intelligent Bug Algorithm (IBA): A Novel Strategy to Navigate Mobile Robots Autonomously

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Abstract

This research proposed an intelligent obstacle avoidance algorithm to navigate an autonomous mobile robot. The presented Intelligent Bug Algorithm (IBA) over performs and reaches the goal in relatively less time as compared to existing Bug algorithms. The improved algorithm offers a goal oriented strategy by following smooth and short trajectory. This has been achieved by continuously considering the goal position during obstacle avoidance. The proposed algorithm is computationally inexpensive and easy to tune. The paper also presents the performance comparison of IBA and reported Bug algorithms. Simulation results of robot navigation in an environment with obstacles demonstrate the performance of the improved algorithm.

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... Bug algorithms are efficient, simple and straight forward navigation methods designed for robots to navigate in an unknown environment that is constantly changing [3,[13][14][15] . Bug algorithms are divided into two types (Bug-1 and Bug-2) on the basis of their behavior of obstacle avoidance. ...
... The robot then restarts following the edge till it reaches the calculated leaving point. One of the drawbacks of the Bug-1 algorithm is when the robot is following the edge of obstacle 1, it may collide with a neighboring obstacle 2 if it is in very close proximity to the first obstacle or if the gap between them is less than the width of the robot [15]. In the Bug-2 algorithm the behavior of the robot changes to "obstacle avoidance" when an obstacle is encountered, where the robot starts following edge of the obstacle and continuously calculates the slope of the line from its current position to the destination. ...
... When this slope becomes equal to the slope of the initial path (from source to destination), the behavior of the robot changes to "move to goal". Therefore, the robot follows a non-repeated path [15]. Both Bug-1 and Bug-2 algorithms do not have high memory requirements. ...
Conference Paper
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Autonomous mobile robots are expected to provide a major role in manufacturing, logistics and service industry. The objective of this research is to develop an improved obstacle avoidance and navigation algorithms for navigation in an unknown indoor environment. Ultrasonic sensors are used to detect the obstacles and rotational odometry is used to localize the robot position and reach the target. A Bluetooth interface is used to establish the communication between the laptop and robot and the same is used to program the robot and feed starting and target positions. An improved collision avoidance algorithm based on Bug2 algorithm is developed. An experimental robot is developed by modifying commercially available Kobuki robot base. The proposed improved navigation algorithm is tested experimentally in a typical laboratory room and experimental results are presented. Keywords: Autonomous mobile robot, robots, navigation, ultrasonic sensors, indoor environment, transportation, obstacle detection, obstacle avoidance, differential drive, PWM converter
... It also allows the robot to decide the most suitable way to move toward the goal [12]. The robot can compute the new path [261] from its departure point (x 1 , y 1 ) to the destination point (x 2 , y 2 ) using two equations to find the slope m and y-intercept c. m = arctan ...
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Robots that can move autonomously and can make intelligent decisions by perceiving their environments and surrounding objects are known as autonomous mobile robots. Such robots have rapidly moved from laboratories to automated industries to fill a variety of roles in our lives, homes, offices, hospitals, industries, and even on the streets. The interest in mobile robots is growing rapidly, prompting an enormous amount of research over the last 30 years, on critical factors of mobile robots such as locomotion, perception, localization, mapping, ego-motion tracking, and dynamic navigation. This article surveys these essential factors of autonomous mobile robots in terms of mathematical modeling, control issues, and challenging factors. Brief discussions are provided on the fundamentals of these technologies, popular algorithms in comprehensive mode, future challenges, and promising directions to guide the construction of an autonomous mobile robot with high accuracy and effectiveness. Since it is difficult to find complete coverage of those topics in a single location, this paper provides a guideline for researchers entering the field or for innovators in the mobile robotics sector. The paper also examines open challenges in indoor mobile robots and identifies potential futures for autonomous mobile robots.
... Besides, Bug algorithm has other types for instance the splitting Bug algorithm [21] and so forth. In numerous simple situations the Bug algorithm is facile and convenient to execute, but it is not usually used due to demerits of self-driving vehicle dynamics and not authentic for complicated real environments. ...
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Automation of the obstacle avoidance is observed to be a potential challenges in the growth of self-driving vehicles (SDVs). For obstacle avoidance data is received from high resolution camera and highly precise sensors. Considering the available data, different Obstacle avoidance methods have been implemented to self-driving on complicated surroundings. On the basis of received data the vehicle is instructed to avoid obstacle considering the size of obstacle. This paper reviewed the obstacle avoidance techniques for SDVs. The main motive of this paper is to provide a diversity of all pertinent literature to possess researchers prevalent on the present situation and potential challenges of obstacle avoidance techniques for SDVs. An explanation and outlooks of obstacle avoidance techniques of the SDVs are also outlined. Finally, an outline of future research is discussed.
... The improved algorithm offers a goal oriented strategy by following smooth and short trajectory. This has been achieved by continuously considering the goal position during obstacle avoidance [11]. As noted, most of the aforementioned algorithms use more complex hardware such as several sensor types or use a large number of ultrasound sensors, which makes them more energy-consuming than our algorithm. ...
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The goal of this research is the development of a detection and obstacle avoidance real-time algorithm for autonomous mobile robot (mobot) navigation in unknown environments. The above mobot will be implemented on low cost hardware, open source software and low processing power platform. The algorithm is designed on using the Pythagorean Theorem to describe the obstacle (determining the size, shape and the plurality of potential obstacles in the environment). A basic feature of the specific implementation is simplicity, not only in calculations but also in hardware requirements. Our algorithm requires only one ultrasound sensor for its operation, while provides very small blind zone and limited energy consumption. The particular algorithm could be applied in unmanned vehicles, for exploration of hazardous environments such as wreckages, volcanos, shipwrecks, radioactive areas, space exploration and generally in places that are hard to human existence.
... It also discusses the deadlock problem which occurs due to moving obstacles. The Intelligent Bug Algorithm (IBA) proposed in [10] is a goaloriented algorithm which results in a shorter and smoother trajectory compared to some of the Bug algorithms. The Intelligent Follow the Gap Method (IFGM) presented in [11] on the other hand is aimed at solving the problem that arises when a robot encounters U or H shaped obstacles. ...
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Several algorithms have been developed to help guide mobile robots in unknown environments. Various kinds of Bug algorithms are available and each one these algorithms has an advantage over the others under different circumstances. This paper introduces a new approach, the Diligent-Bug (D-Bug) algorithm, which is developed to enable a collision free navigation of robots in an unknown 2-dimensional environment. Static obstacles of arbitrary shapes have been considered to evaluate the developed algorithm. This algorithm also enables robots to avoid getting stuck in both local and global loops.
... Focusing in real time obstacle avoidance techniques, a wide variety of algorithms has been proposed [4]. For Bugs algorithm [5], the robot moves directly toward the goal unless faced by an obstacle, in which case the obstacle would be contoured until motion to the goal is again possible. In the Potential Field method introduced by Khatib, each obstacle is modeled with a built-in repulsive force that prevents the robot from bumping into the obstacle [6]. ...
... Focusing in real time obstacle avoidance techniques, a wide variety of algorithms has been proposed [10]. For Bugs algorithm [11], the robot moves directly toward the goal unless faced by an obstacle, in which case the obstacle would be contoured until motion to the goal is again possible. In the Potential Field method introduced by Khatib, each obstacle is modeled with a built-in repulsive force that prevents the robot from bumping into the obstacle [12]. ...
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Chapter
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