A Human-Centric Framework for Robotic Task Learning and Optimization

[1]  Kimberly A. Ingraham,et al.  The role of user preference in the customized control of robotic exoskeletons , 2022, Science Robotics.

[2]  Francesco Braghin,et al.  Review on Patient-Cooperative Control Strategies for Upper-Limb Rehabilitation Exoskeletons , 2021, Frontiers in Robotics and AI.

[3]  Asad Ali Shahid,et al.  Pairwise Preferences-Based Optimization of a Path-Based Velocity Planner in Robotic Sealing Tasks , 2021, IEEE Robotics and Automation Letters.

[4]  Dario Piga,et al.  Human-robot collaboration in sensorless assembly task learning enhanced by uncertainties adaptation via Bayesian Optimization , 2021, Robotics Auton. Syst..

[5]  Alberto Bemporad,et al.  Global optimization based on active preference learning with radial basis functions , 2020, Mach. Learn..

[6]  Marco Forgione,et al.  Robot control parameters auto-tuning in trajectory tracking applications , 2020 .

[7]  P. Show,et al.  Prospects of Industry 5.0 in algae: Customization of production and new advance technology for clean bioenergy generation , 2020 .

[8]  Septimiu E. Salcudean,et al.  Robotics In Vivo: A Perspective on Human-Robot Interaction in Surgical Robotics , 2020, Annu. Rev. Control. Robotics Auton. Syst..

[9]  Minsu Kim,et al.  Fast Adaptation of Deep Reinforcement Learning-Based Navigation Skills to Human Preference , 2020, 2020 IEEE International Conference on Robotics and Automation (ICRA).

[10]  Muhammad Mujtaba Asad,et al.  Collaborative Robots and Industrial Revolution 4.0 (IR 4.0) , 2020, 2020 International Conference on Emerging Trends in Smart Technologies (ICETST).

[11]  Giulio Rosati,et al.  Human-Robot Collaboration in Manufacturing Applications: A Review , 2019, Robotics.

[12]  Antonio Barrientos,et al.  A training system for Industry 4.0 operators in complex assemblies based on virtual reality and process mining , 2019, Robotics Comput. Integr. Manuf..

[13]  Marco Caimmi,et al.  Assisting Operators in Heavy Industrial Tasks: On the Design of an Optimized Cooperative Impedance Fuzzy-Controller With Embedded Safety Rules , 2019, Front. Robot. AI.

[14]  S. Nahavandi Industry 5.0—A Human-Centric Solution , 2019, Sustainability.

[15]  Francesco Braghin,et al.  Mechanical and Control Design of an Industrial Exoskeleton for Advanced Human Empowering in Heavy Parts Manipulation Tasks , 2019, Robotics.

[16]  Koji Tsuda,et al.  Application of Bayesian Optimization for Pharmaceutical Product Development , 2019, Journal of Pharmaceutical Innovation.

[17]  Giorgio Metta,et al.  Adaptable Workstations for Human-Robot Collaboration: A Reconfigurable Framework for Improving Worker Ergonomics and Productivity , 2019, IEEE Robotics & Automation Magazine.

[18]  Ercan Öztemel,et al.  Literature review of Industry 4.0 and related technologies , 2018, J. Intell. Manuf..

[19]  Igor Zubrycki,et al.  Graphical Programming Interface for Enabling Non-technical Professionals to Program Robots and Internet-of-Things Devices , 2017, IWANN.

[20]  Xiaolong Xu,et al.  Big data challenges and opportunities in the hype of Industry 4.0 , 2017, 2017 IEEE International Conference on Communications (ICC).

[21]  Rubén Saborido,et al.  A preference-based evolutionary algorithm for multiobjective optimization: the weighting achievement scalarizing function genetic algorithm , 2015, J. Glob. Optim..

[22]  Thorsten Joachims,et al.  The K-armed Dueling Bandits Problem , 2012, COLT.

[23]  Lothar Thiele,et al.  A Preference-Based Evolutionary Algorithm for Multi-Objective Optimization , 2009, Evolutionary Computation.

[24]  Luís N. Vicente,et al.  A particle swarm pattern search method for bound constrained global optimization , 2007, J. Glob. Optim..

[25]  Wayne L. Tabor,et al.  Global and local optimization using radial basis function response surface models , 2007 .

[26]  K. Schittkowski,et al.  Nonlinear Programming: Algorithms, Software, and Applications , 2003 .

[27]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[28]  Alberto Tellaeche,et al.  PIROS: Cooperative, Safe and Reconfigurable Robotic Companion for CNC Pallets Load/Unload Stations , 2020, EuRoC.

[29]  S. Calinon Learning from Demonstration ( Programming by Demonstration ) ∗ , 2018 .