Mobile robots : navigation, control and remote sensing
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書誌事項
Mobile robots : navigation, control and remote sensing
IEEE Press , Wiley, c2011
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内容説明・目次
内容説明
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. Both linear and nonlinear models are treated. Various control schemes are utilized, and through these applications the reader is introduced to methods such as: (1) Linearization and use of linear control design methods for control about a reference trajectory, (2) Use of Lyapunov stability theory for nonlinear control design, (3) Derivation of optimal control strategies via Pontryagin s maximum principle, (4) Derivation of a local coordinate system which is fundamental for the steering of vehicles along a path never before traversed. This local coordinate system has application regardless of the control design methods utilized. In the navigation area, various coordinate systems are introduced, and the transformations among them are derived. (1) The Global Positioning System (GPS) is introduced and described in significant detail.
(2) Also introduced and discussed are inertial navigation systems (INS). These two methods are treated in terms of their ability to provide vehicle position as well as attitude. A preceding chapter is devoted to coordinate rotations and transformations since they play an important role in the understanding of this body of theory.
目次
Preface xi Introduction xiii 1 Kinematic Models for Mobile Robots 1 1.0 Introduction, 1 1.1 Vehicles with Front-Wheel Steering, 1 1.2 Vehicles with Differential-Drive Steering, 5 Exercises, 8 References, 9 2 Mobile Robot Control 11 2.0 Introduction, 11 2.1 Front-Wheel Steered Vehicle, Heading Control, 11 2.2 Front-Wheel Steered Vehicle, Speed Control, 22 2.3 Heading and Speed Control for the Differential-Drive Robot, 23 2.4 Reference Trajectory and Incremental Control, Front-Wheel Steered Robot, 26 2.5 Heading Control of Front-Wheel Steered Robot Using the Nonlinear Model, 32 2.6 Computed Control for Heading and Velocity, Front-Wheel Steered Robot, 36 2.7 Heading Control of Differential Drive Robot Using the Nonlinear Model, 38 2.8 Computed Control for Heading and Velocity, Differential-Drive Robot, 39 2.9 Steering Control Along a Path Using a Local Coordinate Frame, 41 2.10 Optimal Steering of Front-Wheel Steered Vehicle, 54 2.11 Optimal Steering of Front-Wheel Steered Vehicle, Free Final Heading Angle, 75 Exercises, 77 References, 78 3 Robot Attitude 79 3.0 Introduction, 79 3.1 Defi nition of Yaw, Pitch and Roll, 79 3.2 Rotation Matrix for Yaw, 80 3.3 Rotation Matrix for Pitch, 82 3.4 Rotation Matrix for Roll, 84 3.5 General Rotation Matrix, 86 3.6 Homogeneous Transformation, 88 3.7 Rotating a Vector, 92 Exercises, 93 References, 94 4 Robot Navigation 95 4.0 Introduction, 95 4.1 Coordinate Systems, 95 4.2 Earth-Centered Earth-Fixed Coordinate System, 96 4.3 Associated Coordinate Systems, 98 4.4 Universal Transverse Mercator (UTM) Coordinate System, 102 4.5 Global Positioning System, 104 4.6 Computing Receiver Location Using GPS, Numerical Methods, 108 4.6.1 Computing Receiver Location Using GPS via Newton s Method, 108 4.6.2 Computing Receiver Location Using GPS via Minimization of a Performance Index, 116 4.7 Array of GPS Antennas, 123 4.8 Gimbaled Inertial Navigation Systems, 126 4.9 Strap-Down Inertial Navigation Systems, 131 4.10 Dead Reckoning or Deduced Reckoning, 137 4.11 Inclinometer/Compass, 138 Exercises, 142 References, 147 5 Application of Kalman Filtering 149 5.0 Introduction, 149 5.1 Estimating a Fixed Quantity Using Batch Processing, 149 5.2 Estimating a Fixed Quantity Using Recursive Processing, 151 5.3 Estimating the State of a Dynamic System Recursively, 156 5.4 Estimating the State of a Nonlinear System via the Extended Kalman Filter, 169 Exercises, 185 References, 189 6 Remote Sensing 191 6.0 Introduction, 191 6.1 Camera Type Sensors, 191 6.2 Stereo Vision, 202 6.3 Radar Sensing: Synthetic Aperture Radar (SAR), 206 6.4 Pointing of Range Sensor at Detected Object, 212 6.5 Detection Sensor in Scanning Mode, 217 Exercises, 222 References, 223 7 Target Tracking Including Multiple Targets with Multiple Sensors 225 7.0 Introduction, 225 7.1 Regions of Confidence for Sensors, 225 7.2 Model of Target Location, 232 7.3 Inventory of Detected Targets, 239 Exercises, 244 References, 245 8 Obstacle Mapping and its Application to Robot Navigation 247 8.0 Introduction, 247 8.1 Sensors for Obstacle Detection and Geo-Registration, 248 8.2 Dead Reckoning Navigation, 249 8.3 Use of Previously Detected Obstacles for Navigation, 252 8.4 Simultaneous Corrections of Coordinates of Detected Obstacles and of the Robot, 258 Exercises, 262 References, 263 9 Operating a Robotic Manipulator 265 9.0 Introduction, 265 9.1 Forward Kinematic Equations, 265 9.2 Path Specifi cation in Joint Space, 269 9.3 Inverse Kinematic Equations, 271 9.4 Path Specifi cation in Cartesian Space, 276 9.5 Velocity Relationships, 284 9.6 Forces and Torques, 289 Exercises, 292 References, 293 10 Remote Sensing via UAVS 295 10.0 Introduction, 295 10.1 Mounting of Sensors, 295 10.2 Resolution of Sensors, 296 10.3 Precision of Vehicle Instrumentation, 297 10.4 Overall Geo-Registration Precision, 298 Exercises, 300 References, 300 Appendix A Demonstrations of Undergraduate Student Robotic Projects 301 A.0 Introduction, 301 A.1 Demonstration of the GEONAVOD Robot, 301 A.2 Demonstration of the Automatic Balancing Robotic Bicycle (ABRB), 302 See demonstration videos at http://www.wiley.com/WileyCDA/WileyTitle/productCd-0470630213.html Index 305
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