Human-Robot Collaboration and Safety Management for Logistics and Manipulation Tasks

To realize human-robot collaboration in manufacturing, industrial robots need to share an environment with humans and to work hand in hand. This introduces safety concerns but also provides the opportunity to take advantage of human-robot interactions to control the robot. The main objective of this work is to provide HRI without compromising safety issues in a realistic industrial context. In the paper, a region-based filtering and reasoning method for safety has been developed and integrated into a human-robot collaboration system. The proposed method has been successfully demonstrated keeping safety during the showcase evaluation of the European robotics challenges with a real mobile manipulator.

[1]  Anders Robertsson,et al.  On Distributed Knowledge Bases for Robotized Small-Batch Assembly , 2015, IEEE Transactions on Automation Science and Engineering.

[2]  Bernardo Cunha,et al.  A Skill-Based Architecture for Pick and Place Manipulation Tasks , 2015, EPIA.

[3]  Luís Paulo Reis,et al.  Rich and robust human-robot interaction on gesture recognition for assembly tasks , 2017, 2017 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC).

[4]  Il Hong Suh,et al.  Improvisational goal-oriented action recommendation under incomplete knowledge base , 2012, 2012 IEEE International Conference on Robotics and Automation.

[5]  Nuno Lau,et al.  Multi-object tracking with distributed sensing , 2016, 2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI).

[6]  Bruno Siciliano,et al.  EuRoC - The Challenge Initiative for European Robotics , 2014, ISR 2014.

[7]  Luís Paulo Reis,et al.  Skill-based anytime agent architecture for logistics and manipulation tasks: EuRoC Challenge 2, Stage II - Realistic Labs: Benchmarking , 2017, 2017 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC).

[8]  Peter Teunissen,et al.  An Integrity and Quality Control Procedure for Use in Multi Sensor Integration , 1990 .

[9]  Rainer Bischoff,et al.  The Strategic Research Agenda for Robotics in Europe [Industrial Activities] , 2010 .

[10]  Gi Hyun Lim,et al.  Two-step learning about normal and exceptional human behaviors incorporating patterns and knowledge , 2016, 2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI).

[11]  Sebastian Thrun,et al.  Probabilistic robotics , 2002, CACM.

[12]  Nuno Lau,et al.  Improving and Benchmarking Motion Planning for a Mobile Manipulator Operating in Unstructured Environments , 2017, EPIA.

[13]  Gunnar Bolmsjö,et al.  Human and Robot Interaction based on Safety Zones in a Shared Work Environment , 2014, 2014 9th ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[14]  Lorenzo Molinari Tosatti,et al.  Safe Human-Robot Cooperation in an Industrial Environment , 2013 .

[15]  Gi Hyun Lim,et al.  Interactive teaching and experience extraction for learning about objects and robot activities , 2014, The 23rd IEEE International Symposium on Robot and Human Interactive Communication.

[16]  Il Hong Suh,et al.  Ontology Representation and Instantiation for Semantic Map Building by a Mobile Robot , 2012, IAS.

[17]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[18]  Augusto Luis Ballardini,et al.  ira_laser_tools: a ROS LaserScan manipulation toolbox , 2014, ArXiv.