Humanoid robots locomotion

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Table of contents

1 Introduction 
1.1 Motivation
1.2 Locomotion controllers adaptation
1.3 Goals and methods
1.4 Contributions
1.5 Outline
1.6 List of publications
1.6.1 Conference papers
2 Humanoid robot locomotion control 
2.1 Humanoid robots locomotion
2.1.1 Characteristics of humanoid locomotion
2.1.2 Statically and dynamically balanced locomotion
2.2 Biped locomotion control strategies
2.2.1 Control based on dynamic models
2.2.2 Biologically inspired control
2.2.3 Biped locomotion controller optimization
2.2.4 Biped locomotion controller adaptation
2.2.5 Conclusions
3 Background 
3.1 Mathematical optimization
3.1.1 Metaheuristics
3.2 Evolutionary algorithms
3.2.1 Multi-objective optimization
3.2.2 Pareto eciency
3.3 NSGA-II
3.3.1 SBX and polynomial mutation
4 A general framework for biped locomotion control optimization 
4.1 Problem definition
4.2 Exploration framework
4.3 Selecting the components of the framework
4.3.1 Robot model
4.3.2 Locomotion controller
4.3.3 Environment variable
4.3.4 Optimized locomotion features
4.3.5 Simulator
4.3.6 Optimization algorithm
4.4 Sensitivity analysis on the environment variable
4.5 Correlation analysis
4.5.1 Tuning the optimization setup
5 Optimizing the control of biped locomotion in different conditions
5.1 Locomotion control of the iCub on oors with diffcerent frictions
5.1.1 Optimization framework setup
5.1.2 Stage 1: Locomotion control optimization
5.1.3 Stage 1 results
5.1.4 Stage 2: Optimization on oors with different frictions
5.1.5 Stage 2 results
5.1.6 Conclusions
5.2 Controller optimization of the DARwIn-OP on oors with different slopes
5.2.1 Optimization framework setup
5.2.2 Stage 1: Preliminary optimization
5.2.3 Stage 1 results
5.2.4 Stage 2: Optimization on noors with different slopes
5.2.5 Stage 2 results
5.2.6 Conclusions
5.3 Effects of mass and volume changes on the control of a virtual humanoid robot
5.3.1 Optimization framework setup
5.3.2 Locomotion control optimization under different body’s mass and height values
5.3.3 Results
5.3.4 Conclusions
5.4 Discussion
6 An adaptive approach to humanoid locomotion 
6.1 Problem deffnition
6.2 Adaptation framework overview
6.3 Functions of the adaptation framework
6.3.1 Selection of the solution for the identification process
6.3.2 Identification of the new context
6.3.3 Selecting the nal solution
7 Humanoid locomotion adaptation to unknown terrain features 
7.1 Wilcoxon test
7.1.1 Procedure
7.2 Adapting the iCub’s locomotion control to dierent coecients of friction
7.2.1 Adaptation framework setup
7.2.2 Results
7.2.3 Conclusions
7.3 Making the DARwIn-OP walk up ramps with dierent slopes
7.3.1 Adaptation framework setup
7.3.2 Results
7.3.3 Conclusions
7.4 Discussion
8 Summary and perspectives 
8.1 Goals
8.2 Methodology and contributions
8.3 Conclusions
8.4 Discussion
8.4.1 Main advantages and disadvantages
8.4.2 Towards a full-edged implementation of the adaptation framework
8.5 Perspectives
8.5.1 Time cost and safety of the adaptation framework
8.5.2 Adding feedback to the adaptation process
8.5.3 Automatization of the exploration phase
8.5.4 Duration of each trial
8.5.5 Optimizing towards multiple context variables
8.5.6 Relation between context values and locomotion features
8.5.7 Optimizing a humanoid for total mass and height