Passivity-Based Model Predictive Control for Mobile Vehicle Motion Planning (Record no. 57583)

000 -LEADER
fixed length control field 03510nam a22005535i 4500
001 - CONTROL NUMBER
control field 978-1-4471-5049-7
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20200421112224.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 130419s2013 xxk| s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781447150497
-- 978-1-4471-5049-7
082 04 - CLASSIFICATION NUMBER
Call Number 629.8
100 1# - AUTHOR NAME
Author Tahirovic, Adnan.
245 10 - TITLE STATEMENT
Title Passivity-Based Model Predictive Control for Mobile Vehicle Motion Planning
300 ## - PHYSICAL DESCRIPTION
Number of Pages XI, 56 p. 20 illus., 17 illus. in color.
490 1# - SERIES STATEMENT
Series statement SpringerBriefs in Electrical and Computer Engineering,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Introduction -- PB/MPC Navigation Planner -- PB/MPC-RT Planner For Rough Terrains -- Conclusion.
520 ## - SUMMARY, ETC.
Summary, etc Passivity-based Model Predictive Control for Mobile Vehicle Navigation represents a complete theoretical approach to the adoption of passivity-based model predictive control (MPC) for autonomous vehicle navigation in both indoor and outdoor environments. The brief also introduces analysis of the worst-case scenario that might occur during the task execution. Some of the questions answered in the text include: • how to use an MPC optimization framework for the mobile vehicle navigation approach; • how to guarantee safe task completion even in complex environments including obstacle avoidance and sideslip and rollover avoidance; and  • what to expect in the worst-case scenario in which the roughness of the terrain leads the algorithm to generate the longest possible path to the goal. The passivity-based MPC approach provides a framework in which a wide range of complex vehicles can be accommodated to obtain a safer and more realizable tool during the path-planning stage. During task execution, the optimization step is continuously repeated to take into account new local sensor measurements. These ongoing changes make the path generated rather robust in comparison with techniques that fix the entire path prior to task execution. In addition to researchers working in MPC, engineers interested in vehicle path planning for a number of purposes: rescued mission in hazardous environments; humanitarian demining; agriculture; and even planetary exploration, will find this SpringerBrief to be instructive and helpful.
700 1# - AUTHOR 2
Author 2 Magnani, Gianantonio.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-1-4471-5049-7
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- London :
-- Springer London :
-- Imprint: Springer,
-- 2013.
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-- text
-- txt
-- rdacontent
337 ## -
-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Automotive engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Aerospace engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Astronautics.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Control engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Robotics.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Automation.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Engineering.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Control.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Robotics and Automation.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Automotive Engineering.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Aerospace Technology and Astronautics.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 2191-8112
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-- ZDB-2-ENG

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