000 12202cam a2200409 i 4500
005 20221101232536.0
008 100921s2010 enka b 000 0 eng d
011 _aBIB MATCHES WORLDCAT
020 _a1849962197
_qcased
020 _a9781849962193
_qcased
035 _a(ATU)b11796613
035 _a(OCoLC)619946117
040 _aUKM
_beng
_erda
_cUKM
_dC#P
_dYDXCP
_dATU
042 _aukblsr
050 4 _aTJ211.4
_b.M68 2010
082 0 4 _a629.892
_222
245 0 0 _aMotion planning for humanoid robots /
_cKensuke Harada, Eiichi Yoshida, Kazuhito Yokoi, editors.
264 1 _aLondon :
_bSpringer,
_c2010.
300 _axv, 306 pages :
_billustrations (some colour) ;
_c24 cm
336 _atext
_btxt
_2rdacontent
337 _aunmediated
_bn
_2rdamedia
338 _avolume
_bnc
_2rdacarrier
504 _aIncludes bibliographical references.
505 0 _a1. Navigation and Gait Planning / Joel Chestnutt -- 2. Compliant Control of Whole-body Multi-contact Behaviors in Humanoid Robots / Luis Sentis -- 3. Whole-body Motion Planning - Building Blocks for Intelligent Systems / Michael Gienger, Marc Toussaint and Christian Goerick -- 4. Planning Whole-body Humanoid Locomotion, Reaching, and Manipulation / Eiichi Yoshida, Claudia Esteves, Oussama Kanoun, Mathieu Poirier, Anthony Mallet, Jean-Paul Laumond and Kazuhito Yokoi -- 5. Efficient Motion and Grasp Planning for Humanoid Robots / Nikolaus Vahrenkamp, Tamim Asfour and R¨udiger Dillmann -- 6. Multi-contact Acyclic Motion Planning and Experiments on HRP-2 Humanoid / Adrien Escande and Abderrahmane Kheddar -- 7. Motion Planning for a Humanoid Robot Based on a Biped Walking Pattern Generator / Kensuke Harada -- 8. Autonomous Manipulation of Movable Obstacles / Mike Stilman -- 9. Multi-modal Motion Planning for Precision Pushing on a Humanoid Robot / Kris Hauser and Victor Ng-Thow-Hing -- 10. A Motion Planning Framework for Skill Coordination and Learning / Marcelo Kallmann and Xiaoxi Jiang -- --
505 0 0 _g1.
_tNavigation and Gait Planning /
_rJoel Chestnutt --
_g1.1.
_tIntroduction --
_g1.1.1.
_tNavigation Planning --
_g1.1.2.
_tNavigation and Legs --
_g1.2.
_tDimensionality Reductions --
_g1.3.
_tContact Forces and Hybrid Dynamics --
_g1.4.
_tStance Connectivity --
_g1.5.
_tTerrain Evaluation --
_g1.6.
_tA Simple Example --
_g1.6.1.
_tEnvironment Representation --
_g1.6.2.
_tThe State Space --
_g1.6.3.
_tThe Action Model --
_g1.6.4.
_tThe State-Action Evaluation Function --
_g1.6.5.
_tUsing the Simple Planner --
_g1.7.
_tEstimated Cost Heuristic --
_g1.8.
_tLimited-time and Tiered Planning --
_g1.9.
_tAdaptive Actions --
_g1.9.1.
_tAdaptation Algorithm --
_g1.10.
_tRobot and Environment Dynamics --
_g1.11.
_tSummary -- --
_g2.
_tCompliant Control of Whole-body Multi-contact Behaviors in Humanoid Robots /
_rLuis Sentis --
_g2.1.
_tIntroduction --
_g2.2.
_tModeling Humanoids Under Multi-contact Constraints --
_g2.2.1.
_tKinematic and Dynamic Models --
_g2.2.2.
_tTask Kinematics and Dynamics Under Supporting Constraints --
_g2.2.3.
_tModeling of Contact Centers of Pressure, Internal Forces, and Co MBehavior --
_g2.2.4.
_tFriction Boundaries for Planning Co Mand Internal Force Behaviors --
_g2.3.
_tPrioritized Whole-body Torque Control --
_g2.3.1.
_tRepresentation of Whole-body Skills --
_g2.3.2.
_tPrioritized Torque Control --
_g2.3.3.
_tReal-time Handling of Dynamic Constraints --
_g2.3.4.
_tTask Feasibility --
_g2.3.5.
_tControl of Contact Centers of Pressure and Internal Tensions/Moments --
_g2.4.
_tSimulation Results --
_g2.4.1.
_tMulti-contact Behavior --
_g2.4.2.
_tReal-time Response to Dynamic Constraints --
_g2.4.3.
_tDual Arm Manipulation --
_g2.5.
_tConclusion and Discussion -- --
_g3.
_tWhole-body Motion Planning - Building Blocks for Intelligent Systems /
_rMichael Gienger, Marc Toussaint and Christian Goerick --
_g3.1.
_tIntroduction --
_g3.2.
_tModels for Movement Control and Planning --
_g3.2.1.
_tControl System --
_g3.2.2.
_tTrajectory Generation --
_g3.2.3.
_tTask Relaxation: Displacement Intervals --
_g3.3.
_tStance Point Planning --
_g3.4.
_tPrediction and Action Selection --
_g3.4.1.
_tVisual Perception --
_g3.4.2.
_tBehavior System --
_g3.4.3.
_tExperiments --
_g3.5.
_tTrajectory Optimization --
_g3.6.
_tPlanning Reaching and Grasping --
_g3.6.1.
_tAcquisition of Task Maps for Grasping --
_g3.6.2.
_tIntegration into Optimization Procedure --
_g3.6.3.
_tExperiments --
_g3.7.
_tConclusion -- --
_g4.
_tPlanning Whole-body Humanoid Locomotion, Reaching, and Manipulation /
_rEiichi Yoshida, Claudia Esteves, Oussama Kanoun, Mathieu Poirier, Anthony Mallet, Jean-Paul Laumond and Kazuhito Yokoi --
_g4.1.
_tIntroduction --
_g4.1.1.
_tBasic Motion Planning Methods --
_g4.1.2.
_tHardware and Software Platform --
_g4.2.
_tCollision-free Locomotion: Iterative Two-stage Approach --
_g4.2.1.
_tTwo-stage Planning Framework --
_g4.2.2.
_tSecond Stage: Smooth Path Reshaping --
_g4.3.
_tReaching: Generalized Inverse Kinematic Approach --
_g4.3.1.
_tMethod Overview --
_g4.3.2.
_tGeneralized Inverse Kinematics for Whole-body Motion --
_g4.3.3.
_tResults --
_g4.4.
_tManipulation: Pivoting a Large Object --
_g4.4.1.
_tPivoting and Small-time Controllability --
_g4.4.2.
_tCollision-free pivoting sequence planning --
_g4.4.3.
_tWhole-body Motion Generation and Experiments --
_g4.4.4.
_tRegrasp Planning --
_g4.5.
_tMotion in Real World: Integratingwith Perception --
_g4.5.1.
_tObject Recognition and Localization --
_g4.5.2.
_tCoupling the Motion Plannerwith Perception --
_g4.5.3.
_tExperiments --
_g4.6.
_tConclusion -- --
_g5.
_tEfficient Motion and Grasp Planning for Humanoid Robots /
_rNikolaus Vahrenkamp, Tamim Asfour and R¨udiger Dillmann --
_g5.1.
_tIntroduction --
_g5.1.1.
_tRRT-based Planning --
_g5.1.2.
_tThe Motion Planning Framework --
_g5.2.
_tCollision Checks and Distance Calculations --
_g5.3.
_tWeighted Sampling --
_g5.4.
_tPlanning Grasping Motions --
_g5.4.1.
_tPredefined Grasps --
_g5.4.2.
_tRandomized IK-solver --
_g5.4.3.
_tRRT-based Planning of Grasping Motions with a Set of Grasps --
_g5.5.
_tDual Arm Motion Planning for Re-grasping --
_g5.5.1.
_tDual Arm IK-solver --
_g5.5.2.
_tReachability Space --
_g5.5.3.
_tGradient Descent in Reachability Space --
_g5.5.4.
_tDual Arm J+-RRT --
_g5.5.5.
_tDual Arm IK-RRT --
_g5.5.6.
_tPlanning Hand-off Motions for Two Robots --
_g5.5.7.
_tExperiment on ARMAR-III --
_g5.6.
_tAdaptive Planning --
_g5.6.1.
_tAdaptively Changing the Complexity for Planning --
_g5.6.2.
_tA 3D Example --
_g5.6.3.
_tAdaptive Planning for ARMAR-III --
_g5.6.4.
_tExtensions to Improve the Planning Performance --
_g5.6.5.
_tExperiments --
_g5.7.
_tConclusion -- --
_g6.
_tMulti-contact Acyclic Motion Planning and Experiments on HRP-2 Humanoid /
_rAdrien Escande and Abderrahmane Kheddar --
_g6.1.
_tIntroduction --
_g6.2.
_tOverview of the Planner --
_g6.3.
_tPosture Generator --
_g6.4.
_tContact Planning --
_g6.4.1.
_tSet of Contacts Generation --
_g6.4.2.
_tRough Trajectory --
_g6.4.3.
_tUsing Global Potential Field as Local Optimization Criterion --
_g6.5.
_tSimulation Scenarios --
_g6.6.
_tExperimentation on HRP-2 --
_g6.7.
_tConclusion -- --
_g7.
_tMotion Planning for a Humanoid Robot Based on a Biped Walking Pattern Generator /
_rKensuke Harada --
_g7.1.
_tIntroduction --
_g7.2.
_tGait Generation Method --
_g7.2.1.
_tAnalytical-solution-based Approach --
_g7.2.2.
_tOnline Gait Generation --
_g7.2.3.
_tExperiment --
_g7.3.
_tWhole-body Motion Planning --
_g7.3.1.
_tDefinitions --
_g7.3.2.
_tWalking Pattern Generation --
_g7.3.3.
_tCollision-free Motion Planner --
_g7.3.4.
_tResults --
_g7.4.
_tSimultaneous Foot-place/Whole-body Motion Planning --
_g7.4.1.
_tDefinitions --
_g7.4.2.
_tGait Pattern Generation --
_g7.4.3.
_tOverall Algorithm --
_g7.4.4.
_tExperiment --
_g7.5.
_tWhole-body Manipulation --
_g7.5.1.
_tMotion Modification --
_g7.5.2.
_tForce-controlled Pushing Manipulation --
_g7.6.
_tConclusion -- --
_g8.
_tAutonomous Manipulation of Movable Obstacles /
_rMike Stilman --
_g8.1.
_tIntroduction --
_g8.1.1.
_tPlanning Challenges --
_g8.1.2.
_tOperators --
_g8.1.3.
_tAction Spaces --
_g8.1.4.
_tComplexity of Search --
_g8.2.
_tNAMO Planning --
_g8.2.1.
_tOverview --
_g8.2.2.
_tConfiguration Space --
_g8.2.3.
_tGoals for Navigation --
_g8.2.4.
_tGoals for Manipulation --
_g8.2.5.
_tPlanning as Graph Search --
_g8.2.6.
_tPlanner Prototype --
_g8.2.7.
_tSummary --
_g8.3.
_tHumanoid Manipulation --
_g8.3.1.
_tBackground --
_g8.3.2.
_tBiped Controlwith External Forces --
_g8.3.3.
_tModeling Object Dynamics --
_g8.3.4.
_tExperiments and Results --
_g8.3.5.
_tSummary --
_g8.4.
_tSystem Integration --
_g8.4.1.
_tFrom Planning to Execution --
_g8.4.2.
_tMeasurement --
_g8.4.3.
_tPlanning --
_g8.4.4.
_tUncertainty --
_g8.4.5.
_tResults -- --
_g9.
_tMulti-modal Motion Planning for Precision Pushing on a Humanoid Robot /
_rKris Hauser and Victor Ng-Thow-Hing --
_g9.1.
_tIntroduction --
_g9.2.
_tBackground --
_g9.2.1.
_tPushing --
_g9.2.2.
_tMulti-modal Planning --
_g9.2.3.
_tComplexity and Completeness --
_g9.3.
_tProblem Definition --
_g9.3.1.
_tConfiguration Space --
_g9.3.2.
_tModes --
_g9.3.3.
_tTransitions --
_g9.4.
_tSingle-mode Motion Planning --
_g9.4.1.
_tCollision Checking --
_g9.4.2.
_tWalk Planning --
_g9.4.3.
_tReach Planning --
_g9.4.4.
_tPush Planning --
_g9.5.
_tMulti-modal Planning with Random-MMP --
_g9.5.1.
_tEffects of the Expansion Strategy --
_g9.5.2.
_tBlind Expansion --
_g9.5.3.
_tUtility computation --
_g9.5.4.
_tUtility-centered Expansion --
_g9.5.5.
_tExperimental Comparison of Expansion Strategies --
_g9.6.
_tPostprocessing and System Integration --
_g9.6.1.
_tVisual Sensing --
_g9.6.2.
_tExecution of Walking Trajectories --
_g9.6.3.
_tSmooth Execution of Reach Trajectories --
_g9.7.
_tExperiments --
_g9.7.1.
_tSimulation Experiments --
_g9.7.2.
_tExperiments on ASIMO --
_g9.8.
_tConclusion -- --
_g10.
_tA Motion Planning Framework for Skill Coordination and Learning /
_rMarcelo Kallmann and Xiaoxi Jiang --
_g10.1.
_tIntroduction --
_g10.1.1.
_tRelated Work --
_g10.1.2.
_tFramework Overview --
_g10.2.
_tMotion Skills --
_g10.2.1.
_tReaching Skill --
_g10.2.2.
_tStepping Skill --
_g10.2.3.
_tBalance Skill --
_g10.2.4.
_tOther Skills and Extensions --
_g10.3.
_tMulti-skill Planning --
_g10.3.1.
_tAlgorithm Details --
_g10.3.2.
_tResults and Discussion --
_g10.4.
_tLearning --
_g10.4.1.
_tA Similarity Metric for Reaching Tasks --
_g10.4.2.
_tLearning Reaching Strategies --
_g10.4.3.
_tLearning Constraints from Imitation --
_g10.4.4.
_tResults and Discussion --
_g10.5.
_tConclusion.
520 _a"Research on humanoid robots has been mostly with the aim of developing robots that can replace humans in the performance of certain tasks. Motion planning for these robots can be quite difficult, due to their complex kinematics, dynamics and environment. It is consequently one of the key research topics in humanoid robotics research and the last few years have witnessed considerable progress in the field. Motion Planning for Humanoid Robots surveys the remarkable recent advancement in both the theoretical and the practical aspects of humanoid motion planning. Various motion planning frameworks are presented in Motion Planning for Humanoid Robots, including one for skill coordination and learning, and one for manipulating and grasping tasks. The problem of planning sequences of contacts that support acyclic motion in a highly constrained environment is addressed and a motion planner that enables a humanoid robot to push an object to a desired location on a cluttered table is described. The main areas of interest include: whole body motion planning, task planning, biped gait planning, and sensor feedback for motion planning. Torque-level control of multi-contact behavior, autonomous manipulation of moving obstacles, and movement control and planning architecture are also covered. Motion Planning for Humanoid Robots will help readers to understand the current research on humanoid motion planning. It is written for industrial engineers, advanced undergraduate and postgraduate students."--Publisher's website.
588 _aMachine converted from AACR2 source record.
650 0 _aAndroids.
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650 0 _aRobots
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700 1 _aHarada, Kensuke.
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700 1 _aYoshida, Eiichi,
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700 1 _aYokoi, Kazuhito.
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