Automated Inspection of Pressure Vessels through a Climbing Robot with Sliding Autonomy

AIR is a climbing robot designed for nondestructive testing and inspection of weld seams in tanks and vessels of the oil and gas industry. In this paper a Fuzzy control system is proposed to a optimal selection of Levels of Autonomy (LoA) at each moment, mixing joystick inputs from an operator and sensor information from the environment to ensure that the movement of tracking weld seams is being achieved while allowing the operator to have full control of the robot's movements without having to control each maneuver manually. Experiments were executed in a simulator environment and are presented along with future ideas for research.

[1]  André Schneider de Oliveira,et al.  Intelligent environment recognition and prediction for NDT inspection through autonomous climbing robot , 2018, J. Intell. Robotic Syst..

[2]  Michael A. Goodrich,et al.  Human-Robot Interaction: A Survey , 2008, Found. Trends Hum. Comput. Interact..

[3]  André Schneider de Oliveira,et al.  Enhancing Robot Capabilities of Environmental Perception through Embedded GPU , 2017, 2017 VII Brazilian Symposium on Computing Systems Engineering (SBESC).

[4]  H. Campbell,et al.  A framework for human collaborative robots, operations in South African automotive industry , 2015, 2015 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM).

[5]  Christopher D. Wickens,et al.  A model for types and levels of human interaction with automation , 2000, IEEE Trans. Syst. Man Cybern. Part A.

[6]  Alberto Tellaeche,et al.  Human robot interaction in industrial robotics. Examples from research centers to industry , 2015, 2015 IEEE 20th Conference on Emerging Technologies & Factory Automation (ETFA).

[7]  Terrence Fong,et al.  A Survey of Methods for Safe Human-Robot Interaction , 2017, Found. Trends Robotics.

[8]  Holly A. Yanco,et al.  Blending human and robot inputs for sliding scale autonomy , 2005, ROMAN 2005. IEEE International Workshop on Robot and Human Interactive Communication, 2005..

[9]  Hidenori Kimura,et al.  Human-robot collaboration in precise positioning of a three-dimensional object , 2009, Autom..

[10]  Michael A. Goodrich,et al.  Experiments in adjustable autonomy , 2001, 2001 IEEE International Conference on Systems, Man and Cybernetics. e-Systems and e-Man for Cybernetics in Cyberspace (Cat.No.01CH37236).

[11]  Gita Reese Sukthankar,et al.  An adjustable autonomy paradigm for adapting to expert-novice differences , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[12]  Clint Heyer.  Human-robot interaction and future industrial robotics applications , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[13]  Jess R. Kerlin,et al.  Towards the Principled Study of Variable Autonomy in Mobile Robots , 2015, 2015 IEEE International Conference on Systems, Man, and Cybernetics.

[14]  Henry Hexmoor,et al.  Types and Limits of Agent Autonomy , 2003, Agents and Computational Autonomy.

[15]  Daniel DeLaurentis,et al.  Optimization of Shared Autonomy Vehicle Control Architectures for Swarm Operations , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[16]  Victor Callaghan,et al.  Explorations of Autonomy: An Investigation of Adjustable Autonomy in Intelligent Environments , 2012, 2012 Eighth International Conference on Intelligent Environments.

[17]  Ronald C. Arkin,et al.  Mixed-Initiative Human-Robot Interaction: Definition, Taxonomy, and Survey , 2015, 2015 IEEE International Conference on Systems, Man, and Cybernetics.

[18]  Øyvind Netland,et al.  An Experiment on the Effectiveness of Remote, Robotic Inspection Compared to Manned , 2013, 2013 IEEE International Conference on Systems, Man, and Cybernetics.