Format:
1 Online-Ressource (164 Seiten)
Edition:
Also available in print
ISBN:
1598291270
,
9781598291278
Series Statement:
Synthesis Lectures on Artificial Intelligence and Machine Learning #1
Content:
Robotics technology has recently advanced to the point of being widely accessible for relatively low-budget research, as well as for graduate, undergraduate, and even secondary and primary school education. This lecture provides an example of how to productively use a cutting-edge advanced robotics platform for education and research by providing a detailed case study with the Sony AIBO robot, a vision-based legged robot. The case study used for this lecture is the UT Austin Villa RoboCup Four-Legged Team. This lecture describes both the development process and the technical details of its end result. The main contributions of this lecture are (i) a roadmap for new classes and research groups interested in intelligent autonomous robotics who are starting from scratch with a new robot, and (ii) documentation of the algorithms behind our own approach on the AIBOs with the goal of making them accessible for use on other vision-based and/or legged robot platforms
Content:
Robotics technology has recently advanced to the point of being widely accessible for relatively low-budget research, as well as for graduate, undergraduate, and even secondary and primary school education. This lecture provides an example of how to productively use a cutting-edge advanced robotics platform for education and research by providing a detailed case study with the Sony AIBO robot, a vision-based legged robot. The case study used for this lecture is the UT Austin Villa RoboCup Four-Legged Team. This lecture describes both the development process and the technical details of its end result. The main contributions of this lecture are (i) a roadmap for new classes and research groups interested in intelligent autonomous robotics who are starting from scratch with a new robot, and (ii) documentation of the algorithms behind our own approach on the AIBOs with the goal of making them accessible for use on other vision-based and/or legged robot platforms
Content:
Introduction -- The class -- Initial behaviors -- Vision -- Movement -- Fall detection -- Kicking -- Localization -- Communication -- General architecture -- Global map -- Behaviors -- Coordination -- Simulator -- UT assist --Conclusion -- Heuristics for the vision module -- Kicks -- TCP Gateway -- Extension to world state in 2004 -- Simulator message grammar -- Competition results -- References -- Biography
Note:
Description based upon print version of record
,
Introduction; The Class; Initial Behaviors; Vision; Camera Settings; Color Segmentation; Region Building and Merging; Object Recognition with Bounding Boxes; Position and Bearing of Objects; Visual Opponent Modeling; Movement; Walking; Basics; Forward Kinematics; Inverse Kinematics; General Walking Structure; Omnidirectional Control; Tilting the Body Forward; Tuning the Parameters; Odometry Calibration; GENERAL MOVEMENT; Movement Module; Movement Interface; High-Level Control; Learning Movement Tasks; Forward Gait; Ball Acquisition; Fall Detection; Kicking; Creating the Critical Action
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Integrating the Critical Action into the WalkLocalization; Background; Basic Monte Carlo Localization; MCL for Vision-Based Legged Robots; Enhancements to the Basic Approach; Landmark Histories; Distance-Based Updates; Extended Motion Model; Experimental Setup and Results; Simulator; Experimental Methodology; Test for Accuracy and Time; Test for Stability; Extended Motion Model; Recovery; Localization Summary; Communication; Initial Robot-to-Robot Communication; Message Types; Knowing Which Robots Are Communicating; Determining When A Teammate Is ``Dead''; Practical Results
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General ArchitectureGlobal Map; Maintaining Location Data; Information from Teammates; Providing a High-Level Interface; Behaviors; Goal Scoring; Initial Solution; Incorporating Localization; A Finite State Machine; Goalie; Coordination; Dibs; Relevant Data; Thrashing; Stabilization; Taking the Average; Aging; Calling the Ball; Support Distance; Phasing out Dibs; Final Strategy; Roles; Supporter Behavior; Defender Behavior; Dynamic Role Assignment; Simulator; Basic Architecture; Server Messages; Sensor Model; Motion Model; Graphical Interface; UT Assist; General Architecture; Debugging Data
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Visual OutputLocalization Output; Miscellaneous Output; Vision Calibration; Conclusion; Region Merging and Pruning Parameters; Initial Kick; Extension to World State in 2004; Client Action Messages; American Open 2003; Tilt-Angle Test; Head Kick; Client Info Messages; RoboCup 2003; Circle Method; Chest-Push Kick; Simulated Sensation Messages; Challenge Events 2003; Beacon Parameters; Arms Together Kick; Simulated Observation Messages; U.S. Open 2004; Goal Parameters; Fall-Forward Kick; RoboCup 2004; Ball Parameters; Opponent Detection Parameters; Back Kick; U.S. Open 2005; RoboCup 2005
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Opponent Blob Likelihood CalculationCoordinate Transforms; Walking Parameters
,
Also available in print.
,
System requirements: Adobe Acrobat Reader.
,
Mode of access: World Wide Web.
Additional Edition:
ISBN 1598291262
Additional Edition:
ISBN 9781598291261
Additional Edition:
Erscheint auch als Druck-Ausgabe Intelligent Autonomous Robotics A Robot Soccer Case Study
Language:
English
Keywords:
Electronic books
