Authors:
Mario di Castro
1
;
Jorge Camarero Vera
2
;
Alessandro Masi
3
and
Manuel Ferre Pérez
2
Affiliations:
1
UPM-CSIC, CERN and European Organization for Nuclear Research, Spain
;
2
UPM-CSIC, Spain
;
3
CERN and European Organization for Nuclear Research, Switzerland
Keyword(s):
Mobile Robots and Intelligent Autonomous Systems, Virtual Environment, Virtual and Augmented Reality, Perception and Awareness.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Cognitive Robotics
;
Engineering Applications
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Robotics and Automation
;
Signal Processing, Sensors, Systems Modeling and Control
;
Virtual Environment, Virtual and Augmented Reality
;
Vision, Recognition and Reconstruction
Abstract:
Intelligent robotic systems are becoming essential for industry and harsh environments, such as the CERN accelerator
complex. Aiming to increase safety and machine availability, robots can help perform repetitive and
dangerous tasks, which humans either prefer to avoid or are unable to do because of hazards, size constraints,
or the extreme environments in which they take place, such as outer space or radioactive experimental areas.
A fundamental part of intelligent robots is the perception of the environment that is possible to obtain only
knowing the 6D pose of the objects around the robotic system. In this paper, we present a novel algorithm
to estimate the 6D pose of an object that can be manipulated by a robot. The proposed algorithms works
consistently in unstructured and harsh environments presenting several constraints like variable luminosity,
difficult accessibility and light reflections. The algorithm detects the position and rotation of an object using
3D cameras. The pro
cedure has been developed using Point Cloud Library to manage the point cloud created
with an RGBD Camera. The position and rotation of an object is useful in augmented reality systems to help
the tele-operator and for the realization of autonomous or semi-autonomous tasks.
(More)