Principles of robot motion : theory, algorithms, and implementation

By:

Choset, Howie M

Material type: Text

9780262033275

DDC classification:

629.892 CHO

Contents:

1 Introduction 2 Bug Algorithms 3 Configuration Space 4 Potential Functions 5 Roadmaps 6 Cell Decompositions 7 Sampling-Based Algorithms 8 Kalman Filtering 9 Bayesian Methods 10 Robot Dynamics 11 Trajectory Planning 12 Nonholonomic and Underactuated Systems A Mathematical Notation B Basic Set Definitions C Topology and Metric Spaces D Curve Tracing E Representations of Orientation F Polyhedral Robots in Polyhedral Worlds G Analysis of Algorithms and Complexity Classes H Graph Representation and Basic Search I Statistics Primer J Linear Systems and Control Bibliography Index

Summary: This text reflects the great advances in the field that have taken place in the last ten years, including sensor-based planning, probabilistic planning, localization and mapping, and motion planning for dynamic and nonholonomic systems. Its presentation makes the mathematical underpinnings of robot motion accessible to students of computer science and engineering, relating low-level implementation details to high-level algorithmic concepts

List(s) this item appears in: New Arrivals November - December 2022

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Holdings ( 5 )
Title notes ( 2 )
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Holdings
Item type	Current library	Collection	Call number	Status	Notes	Barcode
Reference	IIITDM Kurnool Reference	Reference	629.892 CHO (Browse shelf(Opens below))	Not for loan	Costly Book	0005112
Books	IIITDM Kurnool General Stacks	Non-fiction	629.892 CHO (Browse shelf(Opens below))	Available	Costly Book	0005110
Books	IIITDM Kurnool General Stacks	Non-fiction	629.892 CHO (Browse shelf(Opens below))	Available	Costly Book	0005111
Books	IIITDM Kurnool General Stacks	Non-fiction	629.892 CHO (Browse shelf(Opens below))	Available		0004959
Books	IIITDM Kurnool General Stacks	Non-fiction	629.892 CHO (Browse shelf(Opens below))	Available		0004960

1 Introduction
2 Bug Algorithms
3 Configuration Space
4 Potential Functions
5 Roadmaps
6 Cell Decompositions
7 Sampling-Based Algorithms
8 Kalman Filtering
9 Bayesian Methods
10 Robot Dynamics
11 Trajectory Planning
12 Nonholonomic and Underactuated Systems
A Mathematical Notation
B Basic Set Definitions
C Topology and Metric Spaces
D Curve Tracing
E Representations of Orientation
F Polyhedral Robots in Polyhedral Worlds
G Analysis of Algorithms and Complexity Classes
H Graph Representation and Basic Search
I Statistics Primer
J Linear Systems and Control
Bibliography
Index

This text reflects the great advances in the field that have taken place in the last ten years, including sensor-based planning, probabilistic planning, localization and mapping, and motion planning for dynamic and nonholonomic systems. Its presentation makes the mathematical underpinnings of robot motion accessible to students of computer science and engineering, relating low-level implementation details to high-level algorithmic concepts

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