Mobile Robots Navigation Control And Remote Sensing Pdf

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Haynes ManualsThe Haynes

Mobile Robots: Navigation, Control and Remote Sensing

We introduce a new autonomous path planning algorithm for mobile robots for reaching target locations in an unknown environment where the robot relies on its on-board sensors. In particular, we describe the design and evaluation of a deep reinforcement learning motion planner with continuous linear and angular velocities to navigate to a desired target location based on deep deterministic policy gradient DDPG. Additionally, the algorithm is enhanced by making use of the available knowledge of the environment provided by a grid-based SLAM with Rao-Blackwellized particle filter algorithm in order to shape the reward function in an attempt to improve the convergence rate, escape local optima and reduce the number of collisions with the obstacles. A comparison is made between a reward function shaped based on the map provided by the SLAM algorithm and a reward function when no knowledge of the map is available. The results are validated in a simulated experiment on a skid-steering mobile robot.

This paper proposes a tracking control method for a differential drive wheeled mobile robot with nonholonomic constraints with an inverse optimal neural controller. It is based on two techniques: first, an identifier using a discrete-time recurrent high-order neural network RHONN trained with an extended Kalman filter EKF algorithm is employed; second, an inverse optimal control is used to avoid solving the Hamilton Jacobi Bellman HJB equation. The desired trajectory of the robot is computed during the navigation process using a stereo camera sensor. Keywords: Neural control, tracking control, differential drive steering, identifier, inverse optimal control. Siegwart, R.

Robotic Follower System Using Bearing-Only Tracking with Directional Antennas

Written for a one-semester course in electrical engineering, this book provides comprehensive coverage of mobile robot applications. The book presents the major areas of mobile robot applications—control, navigation, and remote sensing—which are essential to not only detecting desired objects but also providing accurate information on their precise locations. Topics include kinematic models for mobile robots, mobile robot control, robot attitude, and robot navigation. Whether you are transitioning a classroom course to a hybrid model, developing virtual labs, or launching a fully online program, MathWorks can help you foster active learning no matter where it takes place. Select a Web Site.

Robot Intelligence Technology and Applications 2 pp Cite as. This paper presents the development of a robotic follower system with the eventual goal of autonomous convoying to create end-to-end communication. The core of the system is a bearing-only tracking with directional antennas and an obstacle avoidance algorithm with sonar sensors. We also discuss the use of sonar sensors that can detect objects, which could improve our robotic follower system in mobile robot navigation. Through extensive field experiments in different environments, we show feasibilities of our proposed system, allowing a follower robot to track a leader robot effectively in convoying fashion. We expect that our system can be applied in a variety of applications that need autonomous convoying. Unable to display preview.

Mobile Robots: Navigation, Control and Remote Sensing

While we are building a new and improved webshop, please click below to purchase this content via our partner CCC and their Rightfind service. You will need to register with a RightFind account to finalise the purchase. Signal Processing is one of the large specializations in electrical engineering, mechanical engineering and computer sciences. It derives input from physics, mathematics and is an indispensable feature of all natural- and life sciences in research and in application.

By Silas F. Alves, Joao M. Rincon and Rosana A.

Mobile Robots: Navigation, Control and Remote Sensing [1ed.]0470630213, 9780470630211

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These are 1 control, 2 navigation and 3 remote sensing, all with application to mobile robots. Much of the material is readily extended to any type ground vehicle. In the controls area, robot steering is the issue.

A mobile robot , is a robot that is capable of moving in the surrounding locomotion. Mobile robotics is usually considered to be a subfield of robotics and information engineering. Mobile robots have the capability to move around in their environment and are not fixed to one physical location. Mobile robots can be "autonomous" AMR - autonomous mobile robot which means they are capable of navigating an uncontrolled environment without the need for physical or electro-mechanical guidance devices. Alternatively, mobile robots can rely on guidance devices that allow them to travel a pre-defined navigation route in relatively controlled space AGV - autonomous guided vehicle. By contrast, industrial robots are usually more-or-less stationary, consisting of a jointed arm multi-linked manipulator and gripper assembly or end effector , attached to a fixed surface. Mobile robots have become more commonplace in commercial and industrial settings.


These are (1) control, (2) navigation and (3) remote sensing, all with application to mobile robots. Much of the material is readily extended to any type ground.


1. Introduction

Haynes ManualsThe Haynes Author : Gerald Cook Description:An important feature of this book is the particular combination of topics included. These are 1 control, 2 navigation and 3 remote sensing, all with application to mobile robots. Much of the material is readily extended to any type ground vehicle. In the controls area, robot steering is the issue.

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