A Real Application of an Autonomous Industrial Mobile Manipulator within Industrial Context
Author/s
Outón, Jose Luis; Merino, Ibon; Villaverde, Iván; Ibarguren, Aitor; Herrero, Héctor; [et al.]Date
2021-05-27Keywords
Autonomous industrial mobile manipulator
Deep learning
Robotics
Perception
Sensor fusion
Autonomous navigation
Computer vision
Skills
State machine
Abstract
In modern industry there are still a large number of low added-value processes that
can be automated or semi-automated with safe cooperation between robot and human operators.
The European SHERLOCK project aims to integrate an autonomous industrial mobile manipulator
(AIMM) to perform cooperative tasks between a robot and a human. To be able to do this, AIMMs
need to have a variety of advanced cognitive skills like autonomous navigation, smart perception
and task management. In this paper, we report the project’s tackle in a paradigmatic industrial
application combining accurate autonomous navigation with deep learning-based 3D perception for
pose estimation to locate and manipulate different industrial objects in an unstructured environment.
The proposed method presents a combination of different technologies fused in an AIMM that
achieve the proposed objective with a success rate of 83.33% in tests carried out in a real environment.
Type
article