12,063 research outputs found
A ROS2 based communication architecture for control in collaborative and intelligent automation systems
Collaborative robots are becoming part of intelligent automation systems in
modern industry. Development and control of such systems differs from
traditional automation methods and consequently leads to new challenges.
Thankfully, Robot Operating System (ROS) provides a communication platform and
a vast variety of tools and utilities that can aid that development. However,
it is hard to use ROS in large-scale automation systems due to communication
issues in a distributed setup, hence the development of ROS2. In this paper, a
ROS2 based communication architecture is presented together with an industrial
use-case of a collaborative and intelligent automation system.Comment: 9 pages, 4 figures, 3 tables, to be published in the proceedings of
29th International Conference on Flexible Automation and Intelligent
Manufacturing (FAIM2019), June 201
Blockchain Solutions for Multi-Agent Robotic Systems: Related Work and Open Questions
The possibilities of decentralization and immutability make blockchain
probably one of the most breakthrough and promising technological innovations
in recent years. This paper presents an overview, analysis, and classification
of possible blockchain solutions for practical tasks facing multi-agent robotic
systems. The paper discusses blockchain-based applications that demonstrate how
distributed ledger can be used to extend the existing number of research
platforms and libraries for multi-agent robotic systems.Comment: 5 pages, FRUCT-2019 conference pape
Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Age
Simultaneous Localization and Mapping (SLAM)consists in the concurrent
construction of a model of the environment (the map), and the estimation of the
state of the robot moving within it. The SLAM community has made astonishing
progress over the last 30 years, enabling large-scale real-world applications,
and witnessing a steady transition of this technology to industry. We survey
the current state of SLAM. We start by presenting what is now the de-facto
standard formulation for SLAM. We then review related work, covering a broad
set of topics including robustness and scalability in long-term mapping, metric
and semantic representations for mapping, theoretical performance guarantees,
active SLAM and exploration, and other new frontiers. This paper simultaneously
serves as a position paper and tutorial to those who are users of SLAM. By
looking at the published research with a critical eye, we delineate open
challenges and new research issues, that still deserve careful scientific
investigation. The paper also contains the authors' take on two questions that
often animate discussions during robotics conferences: Do robots need SLAM? and
Is SLAM solved
Furniture models learned from the WWW: using web catalogs to locate and categorize unknown furniture pieces in 3D laser scans
In this article, we investigate how autonomous robots can exploit the high quality information already available from the WWW concerning 3-D models of office furniture. Apart from the hobbyist effort in Google 3-D Warehouse, many companies providing office furnishings already have the models for considerable portions of the objects found in our workplaces and homes. In particular, we present an approach that allows a robot to learn generic models of typical office furniture using examples found in the Web. These generic models are then used by the robot to locate and categorize unknown furniture in real indoor environments
Towards the Safety of Human-in-the-Loop Robotics: Challenges and Opportunities for Safety Assurance of Robotic Co-Workers
The success of the human-robot co-worker team in a flexible manufacturing
environment where robots learn from demonstration heavily relies on the correct
and safe operation of the robot. How this can be achieved is a challenge that
requires addressing both technical as well as human-centric research questions.
In this paper we discuss the state of the art in safety assurance, existing as
well as emerging standards in this area, and the need for new approaches to
safety assurance in the context of learning machines. We then focus on robotic
learning from demonstration, the challenges these techniques pose to safety
assurance and indicate opportunities to integrate safety considerations into
algorithms "by design". Finally, from a human-centric perspective, we stipulate
that, to achieve high levels of safety and ultimately trust, the robotic
co-worker must meet the innate expectations of the humans it works with. It is
our aim to stimulate a discussion focused on the safety aspects of
human-in-the-loop robotics, and to foster multidisciplinary collaboration to
address the research challenges identified
NASA space station automation: AI-based technology review
Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures
A Passivity-based Nonlinear Admittance Control with Application to Powered Upper-limb Control under Unknown Environmental Interactions
This paper presents an admittance controller based on the passivity theory
for a powered upper-limb exoskeleton robot which is governed by the nonlinear
equation of motion. Passivity allows us to include a human operator and
environmental interaction in the control loop. The robot interacts with the
human operator via F/T sensor and interacts with the environment mainly via
end-effectors. Although the environmental interaction cannot be detected by any
sensors (hence unknown), passivity allows us to have natural interaction. An
analysis shows that the behavior of the actual system mimics that of a nominal
model as the control gain goes to infinity, which implies that the proposed
approach is an admittance controller. However, because the control gain cannot
grow infinitely in practice, the performance limitation according to the
achievable control gain is also analyzed. The result of this analysis indicates
that the performance in the sense of infinite norm increases linearly with the
control gain. In the experiments, the proposed properties were verified using 1
degree-of-freedom testbench, and an actual powered upper-limb exoskeleton was
used to lift and maneuver the unknown payload.Comment: Accepted in IEEE/ASME Transactions on Mechatronics (T-MECH
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