Obstacle Avoidance Strategy and Implementation for Unmanned Ground Vehicle Using LIDAR

Wang, Yang; Goila, Ankit; Shetty, Rahul; Heydari, Mahdi; Desai, Ambarish; Yang, Hanlong

doi:10.4271/2017-01-0118

Cited by 19 publications

(12 citation statements)

References 5 publications

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“…To begin with, most of the approaches including conventional methods discussed used cameras and sensors to collect data from the environment to determine the execution of the respective path planning algorithms [55,[91][92][93]. Unfortunately, readings from cameras and sensors are interfered with noise due to changes in pressure, lightening system, temperature and others.…”

Section: Challenges Of Conventional Path Planning Methodsmentioning

confidence: 99%

An Overview of Nature-Inspired, Conventional, and Hybrid Methods of Autonomous Vehicle Path Planning

Ayawli

Chellali

Appiah

et al. 2018

Journal of Advanced Transportation

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Safe and smooth mobile robot navigation through cluttered environment from the initial position to goal with optimal path is required to achieve intelligent autonomous ground vehicles. There are countless research contributions from researchers aiming at finding solution to autonomous mobile robot path planning problems. This paper presents an overview of nature-inspired, conventional, and hybrid path planning strategies employed by researchers over the years for mobile robot path planning problem. The main strengths and challenges of path planning methods employed by researchers were identified and discussed. Future directions for path planning research is given. The results of this paper can significantly enhance how effective path planning methods could be employed and implemented to achieve real-time intelligent autonomous ground vehicles.

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Section: Challenges Of Conventional Path Planning Methodsmentioning

confidence: 99%

An Overview of Nature-Inspired, Conventional, and Hybrid Methods of Autonomous Vehicle Path Planning

Ayawli

Chellali

Appiah

et al. 2018

Journal of Advanced Transportation

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“…In the last thirty years, the use of mobile robots has gained great attention because of their broad potential in practical applications oriented toward the solution of important engineering problems [31][32][33][34][35][36]. For this purpose, several control approaches were developed for obtaining the stabilization and the trajectory tracking control of mobile robots [37][38][39][40][41][42][43]. In particular, in the field of robotics, the advantage of using wheeled mobile robots instead of legged mobile robots is widely accepted.…”

Section: Formulation Of the Problem Of Interest For This Studymentioning

confidence: 99%

“…Therefore, the pure rolling condition is a nonholonomic constraint equation. The Udwadia-Kalaba Equations, on the other hand, were used for obtaining in a concise form the generalized force vector Q r starting from the analytical definition of the pure rolling nonholonomic constraint equation given by Equation (40). To achieve this goal, one can effectively employ the following step-by-step derivation.…”

Section: Unicycle-like Mobile Robot Modelmentioning

confidence: 99%

Forward and Inverse Dynamics of a Unicycle-Like Mobile Robot

Pappalardo

Guida

2019

Machines

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In this research work, a new method for solving forward and inverse dynamic problems of mechanical systems having an underactuated structure and subjected to holonomic and/or nonholonomic constraints is developed. The method devised in this paper is based on the combination of the Udwadia-Kalaba Equations with the Underactuation Equivalence Principle. First, an analytical method based on the Udwadia-Kalaba Equations is employed in the paper for handling dynamic and control problems of nonlinear nonholonomic mechanical systems in the same computational framework. Subsequently, the Underactuation Equivalence Principle is used for extending the capabilities of the Udwadia-Kalaba Equations from fully actuated mechanical systems to underactuated mechanical systems. The Underactuation Equivalence Principle represents an efficient method recently developed in the field of classical mechanics. The Underactuation Equivalence Principle is used in this paper for mathematically formalizing the underactuation property of a mechanical system considering a particular set of nonholonomic algebraic constraints defined at the acceleration level. On the other hand, in this study, the Udwadia-Kalaba Equations are analytically reformulated in a mathematical form suitable for treating inverse dynamic problems. By doing so, the Udwadia-Kalaba Equations are employed in conjunction with the Underactuation Equivalence Principle for developing a nonlinear control method based on an inverse dynamic approach. As shown in detail in this investigation, the proposed method can be used for analytically solving in an explicit manner the forward and inverse dynamic problems of several nonholonomic mechanical systems. In particular, the tracking control of the unicycle-like mobile robot is considered in this investigation as a benchmark example. Numerical experiments on the dynamic model of the unicycle-like mobile robot confirm the effectiveness of the nonlinear dynamic and control approaches developed in this work.

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“…The authors formulated the tracking controller as a Multiconstrained Model Predictive Control (MMPC) problem in order to follow the planned path for maneuvering in order to avoid obstacles by evaluating the proper steering angle to avoid collisions [3]. Wang et al (2017), instead, underlined the safety issues regarding obstacle avoidance, being important features for any kind of vehicle. A LiDAR sensor was used to detect the obstacles along the route and to optimize the path automatically by using the information about the vehicle position, the location of the obstacle, the operational capabilities of the vehicle and environmental restrictions [4].…”

Section: Introductionmentioning

confidence: 99%

“…Wang et al (2017), instead, underlined the safety issues regarding obstacle avoidance, being important features for any kind of vehicle. A LiDAR sensor was used to detect the obstacles along the route and to optimize the path automatically by using the information about the vehicle position, the location of the obstacle, the operational capabilities of the vehicle and environmental restrictions [4]. Lee et al (2017) presented a method for identifying objects in a dynamic environment by using a 3D light detection and ranging sensor, for high speed object detection [5].…”

Section: Introductionmentioning

confidence: 99%

Obstacle Avoidance System for Unmanned Ground Vehicles by Using Ultrasonic Sensors

2018

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Artificial intelligence is the ability of a computer to perform the functions and reasoning typical of the human mind. In its purely informatic aspect, it includes the theory and techniques for the development of algorithms that allow machines to show an intelligent ability and/or perform an intelligent activity, at least in specific areas. In particular, there are automatic learning algorithms based on the same mechanisms that are thought to be the basis of all the cognitive processes developed by the human brain. Such a powerful tool has already started to produce a new class of self-driving vehicles. With the projections of population growth that will increase until the year 2100 up to 11.2 billion, research on innovating agricultural techniques must be continued. In order to improve the efficiency regarding precision agriculture, the use of autonomous agricultural machines must become an important issue. For this reason, it was decided to test the use of the "Neural Network Toolbox" tool already present in MATLAB to design an artificial neural network with supervised learning suitable for classification and pattern recognition by using data collected by an ultrasonic sensor. The idea is to use such a protocol to retrofit kits for agricultural machines already present on the market.

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Obstacle Avoidance Strategy and Implementation for Unmanned Ground Vehicle Using LIDAR

Cited by 19 publications

References 5 publications

An Overview of Nature-Inspired, Conventional, and Hybrid Methods of Autonomous Vehicle Path Planning

An Overview of Nature-Inspired, Conventional, and Hybrid Methods of Autonomous Vehicle Path Planning

Forward and Inverse Dynamics of a Unicycle-Like Mobile Robot

Obstacle Avoidance System for Unmanned Ground Vehicles by Using Ultrasonic Sensors

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