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.
| Original language | English |
|---|---|
| Article number | 1276 |
| Pages (from-to) | 1276 |
| Number of pages | 1 |
| Journal | Electronics |
| Volume | 10 |
| Issue number | 11 |
| DOIs | |
| Publication status | Published - 27 May 2021 |
Keywords
- Autonomous industrial mobile manipulator
- Deep learning
- Robotics
- Perception
- Sensor fusion
- Autonomous navigation
- Computer vision
- Skills
- State machine
Project and Funding Information
- Project ID
- info:eu-repo/grantAgreement/EC/H2020/820689/EU/Seamless and safe human centred robotic applications for novel collaborative workplaces/SHERLOCK
- Funding Info
- This research was funded by EC research project “SHERLOCK—Seamless and safe humancentered robotic applications for novel collaborative workplace”. Grant number: 820689 (https://www.sherlock-project.eu accessed on 12 March 2021).
