MTC-LU-UoB-Airbus

Human-robot collaboration on the shop floor presents a significant set of challenges. In this project the team will develop methods for enabling a shop floor mobile robot to assist a human in logistical and assembly tasks, by bringing tools, parts and assisting in the assembly process to reduce the strain on the human worker. The scenario is as follows. In structure assembly, equipment installation and final assembly of an aircraft, many operations are repetitive, and can involve manipulating quite heavy tools for long periods of time in sometimes un-ergonomic positions. In this project a shop floor application will be developed to enable safer, faster, and more ergonomic operations on an airframe by using a robot in collaboration with a human. The robot will pick and carry a large number of fixing elements or assembly parts and the relevant tools from a storage area and bring them to a worker at the airframe assembly. The robot and the human will then work together to apply the fixing elements and parts. The key steps in the scenario are:

  • Identifying and grasping required tools and materials from a work-surface.
  • Placing the tools and materials on the mobile platform in a safe configuration for transport.
  • Navigating to the worker, and waiting alongside.
  • Grasping materials or a tool taking into account wrenches to be applied in its operation.
  • Positioning the material or presenting the tool for co-manipulation by the human, who will then apply it to each fixing to perform the task.
  • The robot will learn the human applied forces, and assist the human by adapting the end effector forces over time (i.e. in a gravity compensated mode).
  • The robot will interpret foot motion in order to follow the human as they walk along the airframe to enable continued fixing.

Key scientific and technical challenges that must be met which go beyond the state of the art:

  • Flexible Grasping – Grasping and fetching of parts and tools of possible novel shape. We will build on our recent breakthrough work on this.
  • Force based Human-Robot interaction – The robot works as a multiplier of the human’s own abilities, co-applying forces at the end effector in the desired way.
  • Adaptive Interaction and Machine Learning – Learning will be used to allow the human to train the robot over time to apply assistive forces optimally. In addition the robot must interpret the human’s body motions to correctly follow the human.

 

 

Project:
EuRoC

Partners:
MTC, Loughborough University, University of Birmingham, Airbus

Sector
Transport

Keywords
Robotics

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