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Open AccessJournal ArticleDOI

A Review of some Pure-Pursuit based Path Tracking Techniques for Control of Autonomous Vehicle

Moveh Samuel, +2 more
- 17 Feb 2016 - 
- Vol. 135, Iss: 1, pp 35-38
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TLDR
A brief review of few common path tracking techniques used in the design of autonomous vehicles and proposes an area where feature research can be done such as tracking of both implicit and explicit path for a non-holonomic mobile robot.
Abstract
paper gives a brief review of few common path tracking techniques used in the design of autonomous vehicles. Technique such as pure-pursuit, vector pursuit as well as CF- pursuit which are all based on the pure-pursuit techniques were discussed and a detailed comparism was made between these geometric techniques. Also this review work discusses areas were little research has been done. Areas such as tracking of an implicit part of a mobile robot and proposes an area where feature research can be done such as tracking of both implicit and explicit path for a non-holonomic mobile robot.

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Design, Analysis, and Experiments of Preview Path Tracking Control for Autonomous Vehicles

TL;DR: The experimental and simulation results are presented to demonstrate the improved performance in tracking accuracy, steering smoothness, and computational efficiency compared to the MPC and the full-state feedback control.
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Path Following Control of Autonomous Ground Vehicle Based on Nonsingular Terminal Sliding Mode and Active Disturbance Rejection Control

TL;DR: A robust AGV path following control strategy that is based on nonsingular terminal sliding mode (NTSM) and active disturbance rejection control (ADRC) and the nonlinear error feedback control law is designed by combining the NTSM and exponential approximation law.
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Simulation of an Autonomous Mobile Robot for LiDAR-Based In-Field Phenotyping and Navigation

TL;DR: A Robotic Operating System (ROS)-based mobile field robot that simultaneously navigates through occluded crop rows and performs various phenotyping tasks, such as measuring plant volume and canopy height using a 2D LiDAR in a nodding configuration is presented.
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Preview Path Tracking Control With Delay Compensation for Autonomous Vehicles

TL;DR: This paper presents a preview steering control design considering both communication delay and steering lag to achieve accurate, smooth, and computationally efficient path tracking for highly automated vehicles.
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Double-DQN based path smoothing and tracking control method for robotic vehicle navigation

TL;DR: This article presents a novel path smoothing and tracking control method based on Double Deep Q-Network (Double DQN) for an automated robotic vehicle that dramatically reduced the settling time and the overshoot at the corner at higher forward speeds at a minor expense of slightly increased rise time and steady state error.
References
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Book ChapterDOI

I and J

Book

An Behavior-based Robotics

TL;DR: Following a discussion of the relevant biological and psychological models of behavior, the author covers the use of knowledge and learning in autonomous robots, behavior-based and hybrid robot architectures, modular perception, robot colonies, and future trends in robot intelligence.
Book

Behavior-Based Robotics

TL;DR: Whence behaviour? animal behaviour robot behaviour behaviour based architectures representational issues for behavioural systems hybrid deliberative/rective architectures perceptual basis for behaviour-based control adaptive behaviour social behaviour fringe robotics - beyond behaviour.

Implementation of the Pure Pursuit Path Tracking Algorithm

R. C. Coulter
TL;DR: The implementation of the pure pursuit path tracking algorithm is described in detail, and some insights into the performance of the algorithm as a function of its parameters are presented.
Proceedings ArticleDOI

Natural person-following behavior for social robots

TL;DR: In this paper, the authors investigated the social perceptions of a robot's movement as it follows behind a person and proposed that the ideal person-following behavior may be a hybrid approach, with the robot automatically selecting which method to use.
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