Kooperativer Bibliotheksverbund

UID:

Format: 1 Online-Ressource (X, 123 p. 36 illus., 27 illus. in color)

Edition: 1st ed. 2021

ISBN: 9783030408862

Series Statement: Studies in Computational Intelligence 888

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-40885-5

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-40887-9

Language: English

Keywords: Konferenzschrift

DOI: 10.1007/978-3-030-40886-2

URL: Volltext  (URL des Erstveröffentlichers)

UID:

Format: 1 online resource (671 pages) : , color illustrations

ISBN: 0-12-803774-1 , 0-12-803766-0

Note: Front Cover -- Bioinspired Legged Locomotion -- Copyright -- Contents -- List of Contributors -- About the Editors -- 1 Introduction -- 1.1 What Is Bio-Inspired Legged Locomotion? -- 1.2 Organization of the Book -- References -- Part I Concepts -- 2 Fundamental Subfunctions of Locomotion -- Preamble-Things to Consider "Before Walking -- 2.1 Stance -- 2.1.1 Effects of Gait -- 2.1.2 Effects of Size -- 2.1.3 Summary -- References -- 2.2 Leg Swinging -- 2.2.1 Characterizing Features of Leg Swinging -- 2.2.2 Leg Swinging Effects in Locomotion -- 2.2.2.1 Contributing to Stance Phase Dynamics -- 2.2.2.2 Trade-off Between Versatility, Robustness, and Ef ciency -- 2.2.2.3 Distribution of Energies in Forward, Lateral, and Vertical Directions -- 2.2.2.4 Recovery from Perturbations -- 2.2.3 Swing Leg Modeling and Control -- 2.2.3.1 Massless Swing Leg -- 2.2.3.2 Mass in the Swing Leg -- References -- 2.3 Balancing -- 2.3.1 The Neural Control of Balance: Standing vs. Walking -- Sensory feedback control -- References -- 3 Conceptual Models of Legged Locomotion -- A Role for Simple Conceptual Models -- 3.1 Conceptual Models Based on Empirical Observations -- 3.1.1 Observing, Imagining, and Gaining Insights into Locomotion -- 3.1.2 Locomotion as a Complex System Behavior -- 3.1.3 Some Characteristics of Whole-Body Locomotion -- 3.1.3.1 The Trunk: Bouncing Along -- 3.1.3.2 The Stance Leg: Acting Like a Spring -- 3.1.3.3 The Swing Leg: Recirculating for Touchdown -- 3.1.4 Whole-Body Conceptual Models as an Integration of Parts or Subfunctions -- References -- 3.2 Templates and Anchors -- 3.2.1 A Mathematical Framework for Legged Locomotion -- 3.2.2 Templates and Anchors: Hierarchies of Models -- 3.2.3 Templates in Dynamics, Control, and Modeling -- 3.2.4 Sources of Templates -- Notions of Templates -- 3.2.4.1 Dimensionality Reduction in Dynamical Systems. , 3.2.4.2 Templates Based on Mechanical Intuition -- 3.2.4.3 Data-Driven Model Reduction -- 3.2.5 Conclusion -- References -- 3.3 A Simple Model of Running -- 3.3.1 Running Like a Spring-Loaded Inverted Pendulum (SLIP) -- 3.3.1.1 Physical Mechanisms and Robots Related to the SLIP Model -- 3.3.2 Mathematical and Physics-Based SLIP Model -- 3.3.2.1 Ground Reaction Forces During Stance -- 3.3.2.2 Stride Maps: Behavior Investigated Step-by-Step -- 3.3.2.3 Stability of Locomotion -- 3.3.3 Some Insights into Running Aided by SLIP-based Models -- 3.3.3.1 Adaptive, Resilient Locomotion Based on Open-Loop Stability -- 3.3.3.2 Reducing Energetic Costs through Compliant Interaction -- 3.3.3.3 Momentum Trading to Bene t Stability -- 3.3.3.4 Useful Inef ciency: Inef ciency can Bene t Robustness -- References -- 3.4 Simple Models of Walking -- 3.4.1 Walking Like an Inverted Pendulum -- 3.4.2 Passive Walking Mechanisms: Physical Models and Physics-Based Math Models -- 3.4.3 Mathematical Equations Governing a Bipedal Inverted Pendulum (IP) Model -- 3.4.3.1 Behavior Within a Single Stance Phase -- 3.4.3.2 Stance Leg Liftoff and Swing Leg Touchdown -- 3.4.3.3 The Mechanics of Switching from One Stance Leg to the Next -- 3.4.3.4 Stride Maps: Behavior Investigated Step-by-Step -- 3.4.3.5 Stability of Locomotion -- 3.4.4 Some Insights into Walking Aided by Inverted Pendulum Models -- 3.4.4.1 Walking Includes a Pendular Flow of Energy -- 3.4.4.2 Walking Includes the Catching of Repeated Falls -- 3.4.4.3 Momentum is Exchanged During Double Stance -- 3.4.5 Integration of Walking and Running Models -- References -- 3.5 Locomotion as an Oscillator -- 3.5.1 Locomotion as an Oscillator -- 3.5.2 Stride Registration as Phase Estimation -- 3.5.3 Recovery from Perturbations -- 3.5.4 Subsystems as Coupled Oscillators -- 3.5.5 Legged Locomotion Oscillators are Hybrid Dynamical Systems. , 3.5.6 Advanced Application: Data Driven Floquet Models -- 3.5.7 Summary -- References -- 3.6 Model Zoo: Extended Conceptual Models -- 3.6.1 More Detailed Representations of the Leg -- 3.6.1.1 Extending the Number of Limbs (B-SLIP, Q-SLIP) -- 3.6.1.2 Rimless Wheel -- 3.6.1.3 Stance Leg Adaptation (VLS and E-SLIP) -- 3.6.1.4 Clock-Torque SLIP (CT-SLIP) -- 3.6.1.5 Linear Inverted Pendulum Mode (LIPM) -- 3.6.1.6 Addition of Leg Mass to IP (Acrobot, Simplest Walking Model) -- 3.6.1.7 Addition of Mass to SLIP Leg (M-SLIP) -- 3.6.1.8 Extending SLIP with Leg Segments (F-SLIP, 2-SEG, 3-SEG) -- 3.6.1.9 Ankle Actuated IP -- 3.6.1.10 Curved Feet Model -- 3.6.2 Upper Body Modeling -- 3.6.2.1 Virtual Pivot Point (VPP) -- 3.6.2.2 Force Modulated Compliant Hip (FMCH) -- 3.6.3 Extension to 3D -- 3.6.3.1 3D SLIP -- 3.6.3.2 3D IP -- 3.6.4 Extension with Muscle Models -- References -- Part II Control -- 4 Control of Motion and Compliance -- Introduction -- 4.1 Stability and Robustness of Bipedal Walking -- 4.1.1 Introduction -- 4.1.2 Stability Criteria Related to Instantaneous Properties of the Walking System -- 4.1.2.1 Projected Center of Mass -- 4.1.2.2 Zero Moment Point -- 4.1.2.3 Capture Point or Extrapolated Center of Mass -- 4.1.2.4 Virtual Pivot Point -- 4.1.2.5 Angular Momentum -- 4.1.2.6 Zero Rate of Angular Momentum Point -- 4.1.3 Stability Criteria for Limit Cycles -- 4.1.3.1 De nition of Stability and Orbital Stability in the Sense of Lyapunov -- 4.1.3.2 Stability Analysis of Walking Using Lyapunov's First Method -- 4.1.3.3 Applicability of Limit Cycle Stability Concepts to Feedback-Controlled Robots and Humans -- 4.1.4 Robustness Measures of Walking -- 4.1.4.1 Robustness Analysis via the Basin of Attraction -- 4.1.4.2 Robustness Analysis via the Gait Sensitivity Norm -- 4.1.4.3 Robustness Analysis Based on Lyapunov's Second Method. , 4.1.4.4 Pseudospectra for Robustness Analysis of the Matrix Spectrum -- 4.1.5 Recovery from Large Perturbations and Pushes -- 4.1.6 Discussion & Outlook -- References -- 4.2 Optimization as Guiding Principle of Locomotion -- 4.2.1 Introduction -- 4.2.2 Forward and Inverse Dynamics Models of Locomotion -- 4.2.3 Formulating Legged Locomotion as Optimal Control Problem -- 4.2.4 Application of Optimal Control to Generate Locomotion in Humans and Robots -- 4.2.5 What Is the Cost Function of Human Locomotion? The Inverse Optimal Control Problem -- 4.2.6 Application of Inverse Optimal Control to Analyze Optimality in Human Locomotion -- 4.2.7 Discussion & Outlook -- Acknowledgements -- References -- 4.3 Ef ciency and Compliance in Bipedal Walking -- 4.3.1 Introduction -- 4.3.2 Different Models of Compliance -- 4.3.2.1 Constant Compliance -- 4.3.2.2 Variable Compliance -- 4.3.2.3 Extension of Compliance Models to Coupled Joints -- 4.3.3 Using Optimal Control for Compliance Studies -- 4.3.4 Optimization-Based Compliance Studies in Humans -- 4.3.4.1 Constant Parallel Compliance Models for Running and Walking -- 4.3.4.2 Compliance Modulation in Human Walking in Different Situations -- 4.3.5 Optimization-Based Compliance Studies in Robots -- 4.3.5.1 Constant Serial Compliance in Robots -- 4.3.5.2 Variable Rest Length Results in Robots -- 4.3.5.3 Variable Compliance in Robots -- 4.3.6 Discussion & Outlook -- References -- 4.4 Impedance Control for Bio-inspired Robots -- 4.4.1 Rigid Body Dynamics -- 4.4.2 Task/Operational Spaces -- 4.4.3 Impedance & Admittance -- 4.4.4 Impedance of a Robot -- 4.4.5 Impedance Control -- 4.4.5.1 Impedance Control Through Joint Control -- 4.4.5.2 Impedance Control Through Kinematic Con guration Control -- 4.4.5.3 Impedance Control Through Contact Control -- 4.4.6 Emulation of Muscle Models -- References. , 4.5 Template Models for Control -- 4.5.1 Introduction -- 4.5.1.1 A Design Process for Template-Based Control -- 4.5.2 Template Model Selection -- 4.5.2.1 Linear CoM Models for Walking -- 4.5.2.2 SLIP Models for Running -- 4.5.2.3 Perspectives of Template Model Selection -- 4.5.3 Template Model Control -- 4.5.3.1 Control of Linear CoM Models for Walking -- 4.5.3.2 Control for SLIP-Based Models -- 4.5.3.3 Beyond Tracking Control for Pendular Models -- 4.5.4 Establishing a Template/Anchor Relationship -- 4.5.4.1 Realizing Template Dynamics Through Task-Space Control -- Replicating the Dynamics of CoM Templates -- Exploiting Redundancy -- 4.5.4.2 Lifting Other Properties of Template Control -- 4.5.4.3 Anchoring the Template Through Less Model-Intensive Methods -- 4.5.4.4 Template-Inspired Mechanical Design -- 4.5.5 Conclusions -- References -- 4.6 Control Based on Passive Dynamic Walking -- 4.6.1 Introduction -- 4.6.2 Passive Dynamic Walking on a Slope -- 4.6.2.1 Model Description and Equations of Motion -- Single Stance Phase (Continuous Dynamics) -- Foot-Ground Contact Event -- Foot-Strike Phase (Discontinuous Dynamics) -- 4.6.2.2 Analysis Using Poincaré Return Map -- 4.6.2.3 Passive Dynamic Walking in 3-Dimensions -- 4.6.3 Powered Bipedal Robots Inspired from Passive Dynamics -- 4.6.3.1 Collisionless Walking -- 4.6.3.2 Actuating Passive Dynamic Walking Robots -- 4.6.3.3 Discrete-Decision Continuous Action Control -- Control Problem -- Schematic Example -- Discrete Linear Quadratic Regulator (DLQR) -- Other Goals -- Factors to Consider While Designing the Controller -- Example: Controlling a Bipedal Walking Robot -- Computing the Linearization -- 4.6.4 Discussion and Challenges -- 4.6.4.1 Energy Ef ciency and Dynamic Walking -- 4.6.4.2 Stability and Robustness -- 4.6.4.3 Versatility, Maneuverability, and Agility -- 4.6.4.4 Mechanical Design. , 4.6.4.5 Estimation.

Language: English

UID:

Format: 1 online resource (671 pages) : , color illustrations

ISBN: 0-12-803774-1 , 0-12-803766-0

Note: Front Cover -- Bioinspired Legged Locomotion -- Copyright -- Contents -- List of Contributors -- About the Editors -- 1 Introduction -- 1.1 What Is Bio-Inspired Legged Locomotion? -- 1.2 Organization of the Book -- References -- Part I Concepts -- 2 Fundamental Subfunctions of Locomotion -- Preamble-Things to Consider "Before Walking -- 2.1 Stance -- 2.1.1 Effects of Gait -- 2.1.2 Effects of Size -- 2.1.3 Summary -- References -- 2.2 Leg Swinging -- 2.2.1 Characterizing Features of Leg Swinging -- 2.2.2 Leg Swinging Effects in Locomotion -- 2.2.2.1 Contributing to Stance Phase Dynamics -- 2.2.2.2 Trade-off Between Versatility, Robustness, and Ef ciency -- 2.2.2.3 Distribution of Energies in Forward, Lateral, and Vertical Directions -- 2.2.2.4 Recovery from Perturbations -- 2.2.3 Swing Leg Modeling and Control -- 2.2.3.1 Massless Swing Leg -- 2.2.3.2 Mass in the Swing Leg -- References -- 2.3 Balancing -- 2.3.1 The Neural Control of Balance: Standing vs. Walking -- Sensory feedback control -- References -- 3 Conceptual Models of Legged Locomotion -- A Role for Simple Conceptual Models -- 3.1 Conceptual Models Based on Empirical Observations -- 3.1.1 Observing, Imagining, and Gaining Insights into Locomotion -- 3.1.2 Locomotion as a Complex System Behavior -- 3.1.3 Some Characteristics of Whole-Body Locomotion -- 3.1.3.1 The Trunk: Bouncing Along -- 3.1.3.2 The Stance Leg: Acting Like a Spring -- 3.1.3.3 The Swing Leg: Recirculating for Touchdown -- 3.1.4 Whole-Body Conceptual Models as an Integration of Parts or Subfunctions -- References -- 3.2 Templates and Anchors -- 3.2.1 A Mathematical Framework for Legged Locomotion -- 3.2.2 Templates and Anchors: Hierarchies of Models -- 3.2.3 Templates in Dynamics, Control, and Modeling -- 3.2.4 Sources of Templates -- Notions of Templates -- 3.2.4.1 Dimensionality Reduction in Dynamical Systems. , 3.2.4.2 Templates Based on Mechanical Intuition -- 3.2.4.3 Data-Driven Model Reduction -- 3.2.5 Conclusion -- References -- 3.3 A Simple Model of Running -- 3.3.1 Running Like a Spring-Loaded Inverted Pendulum (SLIP) -- 3.3.1.1 Physical Mechanisms and Robots Related to the SLIP Model -- 3.3.2 Mathematical and Physics-Based SLIP Model -- 3.3.2.1 Ground Reaction Forces During Stance -- 3.3.2.2 Stride Maps: Behavior Investigated Step-by-Step -- 3.3.2.3 Stability of Locomotion -- 3.3.3 Some Insights into Running Aided by SLIP-based Models -- 3.3.3.1 Adaptive, Resilient Locomotion Based on Open-Loop Stability -- 3.3.3.2 Reducing Energetic Costs through Compliant Interaction -- 3.3.3.3 Momentum Trading to Bene t Stability -- 3.3.3.4 Useful Inef ciency: Inef ciency can Bene t Robustness -- References -- 3.4 Simple Models of Walking -- 3.4.1 Walking Like an Inverted Pendulum -- 3.4.2 Passive Walking Mechanisms: Physical Models and Physics-Based Math Models -- 3.4.3 Mathematical Equations Governing a Bipedal Inverted Pendulum (IP) Model -- 3.4.3.1 Behavior Within a Single Stance Phase -- 3.4.3.2 Stance Leg Liftoff and Swing Leg Touchdown -- 3.4.3.3 The Mechanics of Switching from One Stance Leg to the Next -- 3.4.3.4 Stride Maps: Behavior Investigated Step-by-Step -- 3.4.3.5 Stability of Locomotion -- 3.4.4 Some Insights into Walking Aided by Inverted Pendulum Models -- 3.4.4.1 Walking Includes a Pendular Flow of Energy -- 3.4.4.2 Walking Includes the Catching of Repeated Falls -- 3.4.4.3 Momentum is Exchanged During Double Stance -- 3.4.5 Integration of Walking and Running Models -- References -- 3.5 Locomotion as an Oscillator -- 3.5.1 Locomotion as an Oscillator -- 3.5.2 Stride Registration as Phase Estimation -- 3.5.3 Recovery from Perturbations -- 3.5.4 Subsystems as Coupled Oscillators -- 3.5.5 Legged Locomotion Oscillators are Hybrid Dynamical Systems. , 3.5.6 Advanced Application: Data Driven Floquet Models -- 3.5.7 Summary -- References -- 3.6 Model Zoo: Extended Conceptual Models -- 3.6.1 More Detailed Representations of the Leg -- 3.6.1.1 Extending the Number of Limbs (B-SLIP, Q-SLIP) -- 3.6.1.2 Rimless Wheel -- 3.6.1.3 Stance Leg Adaptation (VLS and E-SLIP) -- 3.6.1.4 Clock-Torque SLIP (CT-SLIP) -- 3.6.1.5 Linear Inverted Pendulum Mode (LIPM) -- 3.6.1.6 Addition of Leg Mass to IP (Acrobot, Simplest Walking Model) -- 3.6.1.7 Addition of Mass to SLIP Leg (M-SLIP) -- 3.6.1.8 Extending SLIP with Leg Segments (F-SLIP, 2-SEG, 3-SEG) -- 3.6.1.9 Ankle Actuated IP -- 3.6.1.10 Curved Feet Model -- 3.6.2 Upper Body Modeling -- 3.6.2.1 Virtual Pivot Point (VPP) -- 3.6.2.2 Force Modulated Compliant Hip (FMCH) -- 3.6.3 Extension to 3D -- 3.6.3.1 3D SLIP -- 3.6.3.2 3D IP -- 3.6.4 Extension with Muscle Models -- References -- Part II Control -- 4 Control of Motion and Compliance -- Introduction -- 4.1 Stability and Robustness of Bipedal Walking -- 4.1.1 Introduction -- 4.1.2 Stability Criteria Related to Instantaneous Properties of the Walking System -- 4.1.2.1 Projected Center of Mass -- 4.1.2.2 Zero Moment Point -- 4.1.2.3 Capture Point or Extrapolated Center of Mass -- 4.1.2.4 Virtual Pivot Point -- 4.1.2.5 Angular Momentum -- 4.1.2.6 Zero Rate of Angular Momentum Point -- 4.1.3 Stability Criteria for Limit Cycles -- 4.1.3.1 De nition of Stability and Orbital Stability in the Sense of Lyapunov -- 4.1.3.2 Stability Analysis of Walking Using Lyapunov's First Method -- 4.1.3.3 Applicability of Limit Cycle Stability Concepts to Feedback-Controlled Robots and Humans -- 4.1.4 Robustness Measures of Walking -- 4.1.4.1 Robustness Analysis via the Basin of Attraction -- 4.1.4.2 Robustness Analysis via the Gait Sensitivity Norm -- 4.1.4.3 Robustness Analysis Based on Lyapunov's Second Method. , 4.1.4.4 Pseudospectra for Robustness Analysis of the Matrix Spectrum -- 4.1.5 Recovery from Large Perturbations and Pushes -- 4.1.6 Discussion & Outlook -- References -- 4.2 Optimization as Guiding Principle of Locomotion -- 4.2.1 Introduction -- 4.2.2 Forward and Inverse Dynamics Models of Locomotion -- 4.2.3 Formulating Legged Locomotion as Optimal Control Problem -- 4.2.4 Application of Optimal Control to Generate Locomotion in Humans and Robots -- 4.2.5 What Is the Cost Function of Human Locomotion? The Inverse Optimal Control Problem -- 4.2.6 Application of Inverse Optimal Control to Analyze Optimality in Human Locomotion -- 4.2.7 Discussion & Outlook -- Acknowledgements -- References -- 4.3 Ef ciency and Compliance in Bipedal Walking -- 4.3.1 Introduction -- 4.3.2 Different Models of Compliance -- 4.3.2.1 Constant Compliance -- 4.3.2.2 Variable Compliance -- 4.3.2.3 Extension of Compliance Models to Coupled Joints -- 4.3.3 Using Optimal Control for Compliance Studies -- 4.3.4 Optimization-Based Compliance Studies in Humans -- 4.3.4.1 Constant Parallel Compliance Models for Running and Walking -- 4.3.4.2 Compliance Modulation in Human Walking in Different Situations -- 4.3.5 Optimization-Based Compliance Studies in Robots -- 4.3.5.1 Constant Serial Compliance in Robots -- 4.3.5.2 Variable Rest Length Results in Robots -- 4.3.5.3 Variable Compliance in Robots -- 4.3.6 Discussion & Outlook -- References -- 4.4 Impedance Control for Bio-inspired Robots -- 4.4.1 Rigid Body Dynamics -- 4.4.2 Task/Operational Spaces -- 4.4.3 Impedance & Admittance -- 4.4.4 Impedance of a Robot -- 4.4.5 Impedance Control -- 4.4.5.1 Impedance Control Through Joint Control -- 4.4.5.2 Impedance Control Through Kinematic Con guration Control -- 4.4.5.3 Impedance Control Through Contact Control -- 4.4.6 Emulation of Muscle Models -- References. , 4.5 Template Models for Control -- 4.5.1 Introduction -- 4.5.1.1 A Design Process for Template-Based Control -- 4.5.2 Template Model Selection -- 4.5.2.1 Linear CoM Models for Walking -- 4.5.2.2 SLIP Models for Running -- 4.5.2.3 Perspectives of Template Model Selection -- 4.5.3 Template Model Control -- 4.5.3.1 Control of Linear CoM Models for Walking -- 4.5.3.2 Control for SLIP-Based Models -- 4.5.3.3 Beyond Tracking Control for Pendular Models -- 4.5.4 Establishing a Template/Anchor Relationship -- 4.5.4.1 Realizing Template Dynamics Through Task-Space Control -- Replicating the Dynamics of CoM Templates -- Exploiting Redundancy -- 4.5.4.2 Lifting Other Properties of Template Control -- 4.5.4.3 Anchoring the Template Through Less Model-Intensive Methods -- 4.5.4.4 Template-Inspired Mechanical Design -- 4.5.5 Conclusions -- References -- 4.6 Control Based on Passive Dynamic Walking -- 4.6.1 Introduction -- 4.6.2 Passive Dynamic Walking on a Slope -- 4.6.2.1 Model Description and Equations of Motion -- Single Stance Phase (Continuous Dynamics) -- Foot-Ground Contact Event -- Foot-Strike Phase (Discontinuous Dynamics) -- 4.6.2.2 Analysis Using Poincaré Return Map -- 4.6.2.3 Passive Dynamic Walking in 3-Dimensions -- 4.6.3 Powered Bipedal Robots Inspired from Passive Dynamics -- 4.6.3.1 Collisionless Walking -- 4.6.3.2 Actuating Passive Dynamic Walking Robots -- 4.6.3.3 Discrete-Decision Continuous Action Control -- Control Problem -- Schematic Example -- Discrete Linear Quadratic Regulator (DLQR) -- Other Goals -- Factors to Consider While Designing the Controller -- Example: Controlling a Bipedal Walking Robot -- Computing the Linearization -- 4.6.4 Discussion and Challenges -- 4.6.4.1 Energy Ef ciency and Dynamic Walking -- 4.6.4.2 Stability and Robustness -- 4.6.4.3 Versatility, Maneuverability, and Agility -- 4.6.4.4 Mechanical Design. , 4.6.4.5 Estimation.

Language: English

UID:

Format: 1 online resource (671 pages) : , color illustrations

ISBN: 0-12-803774-1 , 0-12-803766-0

Note: Front Cover -- Bioinspired Legged Locomotion -- Copyright -- Contents -- List of Contributors -- About the Editors -- 1 Introduction -- 1.1 What Is Bio-Inspired Legged Locomotion? -- 1.2 Organization of the Book -- References -- Part I Concepts -- 2 Fundamental Subfunctions of Locomotion -- Preamble-Things to Consider "Before Walking -- 2.1 Stance -- 2.1.1 Effects of Gait -- 2.1.2 Effects of Size -- 2.1.3 Summary -- References -- 2.2 Leg Swinging -- 2.2.1 Characterizing Features of Leg Swinging -- 2.2.2 Leg Swinging Effects in Locomotion -- 2.2.2.1 Contributing to Stance Phase Dynamics -- 2.2.2.2 Trade-off Between Versatility, Robustness, and Ef ciency -- 2.2.2.3 Distribution of Energies in Forward, Lateral, and Vertical Directions -- 2.2.2.4 Recovery from Perturbations -- 2.2.3 Swing Leg Modeling and Control -- 2.2.3.1 Massless Swing Leg -- 2.2.3.2 Mass in the Swing Leg -- References -- 2.3 Balancing -- 2.3.1 The Neural Control of Balance: Standing vs. Walking -- Sensory feedback control -- References -- 3 Conceptual Models of Legged Locomotion -- A Role for Simple Conceptual Models -- 3.1 Conceptual Models Based on Empirical Observations -- 3.1.1 Observing, Imagining, and Gaining Insights into Locomotion -- 3.1.2 Locomotion as a Complex System Behavior -- 3.1.3 Some Characteristics of Whole-Body Locomotion -- 3.1.3.1 The Trunk: Bouncing Along -- 3.1.3.2 The Stance Leg: Acting Like a Spring -- 3.1.3.3 The Swing Leg: Recirculating for Touchdown -- 3.1.4 Whole-Body Conceptual Models as an Integration of Parts or Subfunctions -- References -- 3.2 Templates and Anchors -- 3.2.1 A Mathematical Framework for Legged Locomotion -- 3.2.2 Templates and Anchors: Hierarchies of Models -- 3.2.3 Templates in Dynamics, Control, and Modeling -- 3.2.4 Sources of Templates -- Notions of Templates -- 3.2.4.1 Dimensionality Reduction in Dynamical Systems. , 3.2.4.2 Templates Based on Mechanical Intuition -- 3.2.4.3 Data-Driven Model Reduction -- 3.2.5 Conclusion -- References -- 3.3 A Simple Model of Running -- 3.3.1 Running Like a Spring-Loaded Inverted Pendulum (SLIP) -- 3.3.1.1 Physical Mechanisms and Robots Related to the SLIP Model -- 3.3.2 Mathematical and Physics-Based SLIP Model -- 3.3.2.1 Ground Reaction Forces During Stance -- 3.3.2.2 Stride Maps: Behavior Investigated Step-by-Step -- 3.3.2.3 Stability of Locomotion -- 3.3.3 Some Insights into Running Aided by SLIP-based Models -- 3.3.3.1 Adaptive, Resilient Locomotion Based on Open-Loop Stability -- 3.3.3.2 Reducing Energetic Costs through Compliant Interaction -- 3.3.3.3 Momentum Trading to Bene t Stability -- 3.3.3.4 Useful Inef ciency: Inef ciency can Bene t Robustness -- References -- 3.4 Simple Models of Walking -- 3.4.1 Walking Like an Inverted Pendulum -- 3.4.2 Passive Walking Mechanisms: Physical Models and Physics-Based Math Models -- 3.4.3 Mathematical Equations Governing a Bipedal Inverted Pendulum (IP) Model -- 3.4.3.1 Behavior Within a Single Stance Phase -- 3.4.3.2 Stance Leg Liftoff and Swing Leg Touchdown -- 3.4.3.3 The Mechanics of Switching from One Stance Leg to the Next -- 3.4.3.4 Stride Maps: Behavior Investigated Step-by-Step -- 3.4.3.5 Stability of Locomotion -- 3.4.4 Some Insights into Walking Aided by Inverted Pendulum Models -- 3.4.4.1 Walking Includes a Pendular Flow of Energy -- 3.4.4.2 Walking Includes the Catching of Repeated Falls -- 3.4.4.3 Momentum is Exchanged During Double Stance -- 3.4.5 Integration of Walking and Running Models -- References -- 3.5 Locomotion as an Oscillator -- 3.5.1 Locomotion as an Oscillator -- 3.5.2 Stride Registration as Phase Estimation -- 3.5.3 Recovery from Perturbations -- 3.5.4 Subsystems as Coupled Oscillators -- 3.5.5 Legged Locomotion Oscillators are Hybrid Dynamical Systems. , 3.5.6 Advanced Application: Data Driven Floquet Models -- 3.5.7 Summary -- References -- 3.6 Model Zoo: Extended Conceptual Models -- 3.6.1 More Detailed Representations of the Leg -- 3.6.1.1 Extending the Number of Limbs (B-SLIP, Q-SLIP) -- 3.6.1.2 Rimless Wheel -- 3.6.1.3 Stance Leg Adaptation (VLS and E-SLIP) -- 3.6.1.4 Clock-Torque SLIP (CT-SLIP) -- 3.6.1.5 Linear Inverted Pendulum Mode (LIPM) -- 3.6.1.6 Addition of Leg Mass to IP (Acrobot, Simplest Walking Model) -- 3.6.1.7 Addition of Mass to SLIP Leg (M-SLIP) -- 3.6.1.8 Extending SLIP with Leg Segments (F-SLIP, 2-SEG, 3-SEG) -- 3.6.1.9 Ankle Actuated IP -- 3.6.1.10 Curved Feet Model -- 3.6.2 Upper Body Modeling -- 3.6.2.1 Virtual Pivot Point (VPP) -- 3.6.2.2 Force Modulated Compliant Hip (FMCH) -- 3.6.3 Extension to 3D -- 3.6.3.1 3D SLIP -- 3.6.3.2 3D IP -- 3.6.4 Extension with Muscle Models -- References -- Part II Control -- 4 Control of Motion and Compliance -- Introduction -- 4.1 Stability and Robustness of Bipedal Walking -- 4.1.1 Introduction -- 4.1.2 Stability Criteria Related to Instantaneous Properties of the Walking System -- 4.1.2.1 Projected Center of Mass -- 4.1.2.2 Zero Moment Point -- 4.1.2.3 Capture Point or Extrapolated Center of Mass -- 4.1.2.4 Virtual Pivot Point -- 4.1.2.5 Angular Momentum -- 4.1.2.6 Zero Rate of Angular Momentum Point -- 4.1.3 Stability Criteria for Limit Cycles -- 4.1.3.1 De nition of Stability and Orbital Stability in the Sense of Lyapunov -- 4.1.3.2 Stability Analysis of Walking Using Lyapunov's First Method -- 4.1.3.3 Applicability of Limit Cycle Stability Concepts to Feedback-Controlled Robots and Humans -- 4.1.4 Robustness Measures of Walking -- 4.1.4.1 Robustness Analysis via the Basin of Attraction -- 4.1.4.2 Robustness Analysis via the Gait Sensitivity Norm -- 4.1.4.3 Robustness Analysis Based on Lyapunov's Second Method. , 4.1.4.4 Pseudospectra for Robustness Analysis of the Matrix Spectrum -- 4.1.5 Recovery from Large Perturbations and Pushes -- 4.1.6 Discussion & Outlook -- References -- 4.2 Optimization as Guiding Principle of Locomotion -- 4.2.1 Introduction -- 4.2.2 Forward and Inverse Dynamics Models of Locomotion -- 4.2.3 Formulating Legged Locomotion as Optimal Control Problem -- 4.2.4 Application of Optimal Control to Generate Locomotion in Humans and Robots -- 4.2.5 What Is the Cost Function of Human Locomotion? The Inverse Optimal Control Problem -- 4.2.6 Application of Inverse Optimal Control to Analyze Optimality in Human Locomotion -- 4.2.7 Discussion & Outlook -- Acknowledgements -- References -- 4.3 Ef ciency and Compliance in Bipedal Walking -- 4.3.1 Introduction -- 4.3.2 Different Models of Compliance -- 4.3.2.1 Constant Compliance -- 4.3.2.2 Variable Compliance -- 4.3.2.3 Extension of Compliance Models to Coupled Joints -- 4.3.3 Using Optimal Control for Compliance Studies -- 4.3.4 Optimization-Based Compliance Studies in Humans -- 4.3.4.1 Constant Parallel Compliance Models for Running and Walking -- 4.3.4.2 Compliance Modulation in Human Walking in Different Situations -- 4.3.5 Optimization-Based Compliance Studies in Robots -- 4.3.5.1 Constant Serial Compliance in Robots -- 4.3.5.2 Variable Rest Length Results in Robots -- 4.3.5.3 Variable Compliance in Robots -- 4.3.6 Discussion & Outlook -- References -- 4.4 Impedance Control for Bio-inspired Robots -- 4.4.1 Rigid Body Dynamics -- 4.4.2 Task/Operational Spaces -- 4.4.3 Impedance & Admittance -- 4.4.4 Impedance of a Robot -- 4.4.5 Impedance Control -- 4.4.5.1 Impedance Control Through Joint Control -- 4.4.5.2 Impedance Control Through Kinematic Con guration Control -- 4.4.5.3 Impedance Control Through Contact Control -- 4.4.6 Emulation of Muscle Models -- References. , 4.5 Template Models for Control -- 4.5.1 Introduction -- 4.5.1.1 A Design Process for Template-Based Control -- 4.5.2 Template Model Selection -- 4.5.2.1 Linear CoM Models for Walking -- 4.5.2.2 SLIP Models for Running -- 4.5.2.3 Perspectives of Template Model Selection -- 4.5.3 Template Model Control -- 4.5.3.1 Control of Linear CoM Models for Walking -- 4.5.3.2 Control for SLIP-Based Models -- 4.5.3.3 Beyond Tracking Control for Pendular Models -- 4.5.4 Establishing a Template/Anchor Relationship -- 4.5.4.1 Realizing Template Dynamics Through Task-Space Control -- Replicating the Dynamics of CoM Templates -- Exploiting Redundancy -- 4.5.4.2 Lifting Other Properties of Template Control -- 4.5.4.3 Anchoring the Template Through Less Model-Intensive Methods -- 4.5.4.4 Template-Inspired Mechanical Design -- 4.5.5 Conclusions -- References -- 4.6 Control Based on Passive Dynamic Walking -- 4.6.1 Introduction -- 4.6.2 Passive Dynamic Walking on a Slope -- 4.6.2.1 Model Description and Equations of Motion -- Single Stance Phase (Continuous Dynamics) -- Foot-Ground Contact Event -- Foot-Strike Phase (Discontinuous Dynamics) -- 4.6.2.2 Analysis Using Poincaré Return Map -- 4.6.2.3 Passive Dynamic Walking in 3-Dimensions -- 4.6.3 Powered Bipedal Robots Inspired from Passive Dynamics -- 4.6.3.1 Collisionless Walking -- 4.6.3.2 Actuating Passive Dynamic Walking Robots -- 4.6.3.3 Discrete-Decision Continuous Action Control -- Control Problem -- Schematic Example -- Discrete Linear Quadratic Regulator (DLQR) -- Other Goals -- Factors to Consider While Designing the Controller -- Example: Controlling a Bipedal Walking Robot -- Computing the Linearization -- 4.6.4 Discussion and Challenges -- 4.6.4.1 Energy Ef ciency and Dynamic Walking -- 4.6.4.2 Stability and Robustness -- 4.6.4.3 Versatility, Maneuverability, and Agility -- 4.6.4.4 Mechanical Design. , 4.6.4.5 Estimation.

Language: English

UID:

Format: X, 123 p. 36 illus., 27 illus. in color. , online resource.

Edition: 1st ed. 2021.

ISBN: 9783030408862

Series Statement: Studies in Computational Intelligence, 888

Content: This book discusses biologically inspired robotic actuators designed to offer improved robot performance and approaching human-like efficiency and versatility. It assesses biological actuation and control in the human motor system, presents a range of technical actuation approaches, and discusses potential applications in wearable robots, i.e., powered prostheses and exoskeletons. Gathering the findings of internationally respected researchers from various fields, the book provides a uniquely broad perspective on bioinspired actuator designs for robotics. Its scope includes fundamental aspects of biomechanics and neuromechanics, actuator and control design, and their application in (wearable) robotics. The book offers PhD students and advanced graduate students an essential introduction to the field, while providing researchers a cutting-edge research perspective.

Note: Introduction -- Recent research on biological actuation - what can we learn from biology -- Variable impedance actuators and their relation to biology -- State of the art of engineered actuators approaching muscle behaviours -- Applying compliant actuators in wearable robots Verstraten, Flynn, Toxiri, Calanca, Lefeber -- Conclusions.

In: Springer Nature eBook

Additional Edition: Printed edition: ISBN 9783030408855

Additional Edition: Printed edition: ISBN 9783030408879

Language: English

DOI: 10.1007/978-3-030-40886-2

URL: https://doi.org/10.1007/978-3-030-40886-2

UID:

Format: x, 123 Seiten : , Illustrationen, Diagramme (überwiegend farbig).

ISBN: 978-3-030-40885-5

Series Statement: Studies in computational intelligence volume 888

Note: Aus der Einleitung: "This book is based on the outcomes of the IEEE BioRob 2018 Workshop "Novel bioinspired actuator designs for robotics (BioAct)", which was held in Enschede, The Netherlands, on August 28, 2018. Moreover, it is supported by contributors of the IEEE AIM 2017 Workshop "Promoting Elastic Actuators for Robotics (PEAR): novel approaches and biomedical applications", which was held in Munich, Germany, on July 3, 2017."

Additional Edition: Erscheint auch als Online-Ausgabe ISBN 978-3-030-40886-2

Language: English

Keywords: Konferenzschrift

Author information: Pott, Peter Paul.

Author information: Beckerle, Philipp.

Author information: Seyfarth, André, 1970-

UID:

ISSN: 1873-2380

In: Journal of biomechanics, Amsterdam [u.a.] : Elsevier Science, 1968, 45(2012), 14, Seite 2472-2475, 1873-2380

In: volume:45

In: year:2012

In: number:14

In: pages:2472-2475

Language: English

DOI: 10.1016/j.jbiomech.2012.06.030

URL: Volltext

Author information: Maus, Horst-Moritz 1982-

UID:

ISSN: 0021-9290

In: Journal of biomechanics, New York, NY [u.a.] : Elsevier Science, 1968, 45(2012), 14, Seite 2472-2475, 0021-9290

In: volume:45

In: year:2012

In: number:14

In: pages:2472-2475

Language: English

DOI: 10.1016/j.jbiomech.2012.06.030

Author information: Maus, Horst-Moritz 1982-

UID:

Format: 11

ISSN: 1742-5689

In: Interface, London : The Royal Society, 2004, Volume 12 (2015), issue 103, 20140899, Seite 1-11, 1742-5689

In: volume:12

In: year:2015

In: number:103

In: pages:20140899

In: extent:11

Language: English

DOI: 10.1098/rsif.2014.0899

Author information: Guckenheimer, John 1945-

Author information: Ludwig, Christian 1979-

Author information: Reger, Johann 1971-

Author information: Seyfarth, Andre 1970-

Author information: Maus, Horst-Moritz 1982-