59 research outputs found
Design of an Energy-Aware Cartesian Impedance Controller for Collaborative Disassembly
Human-robot collaborative disassembly is an emerging trend in the sustainable
recycling process of electronic and mechanical products. It requires the use of
advanced technologies to assist workers in repetitive physical tasks and deal
with creaky and potentially damaged components. Nevertheless, when
disassembling worn-out or damaged components, unexpected robot behaviors may
emerge, so harmless and symbiotic physical interaction with humans and the
environment becomes paramount. This work addresses this challenge at the
control level by ensuring safe and passive behaviors in unplanned interactions
and contact losses. The proposed algorithm capitalizes on an energy-aware
Cartesian impedance controller, which features energy scaling and damping
injection, and an augmented energy tank, which limits the power flow from the
controller to the robot. The controller is evaluated in a real-world flawed
unscrewing task with a Franka Emika Panda and is compared to a standard
impedance controller and a hybrid force-impedance controller. The results
demonstrate the high potential of the algorithm in human-robot collaborative
disassembly tasks.Comment: 7 pages, 6 figures, presented at the 2023 IEEE International
Conference on Robotics and Automation (ICRA). Video available at
https://www.youtube-nocookie.com/embed/SgYFHMlEl0
Toward privacy-sensitive human-robot interaction: Privacy terms and human-data interaction in the personal robot era
Can we have personal robots without giving away personal data? Besides, what is the role of a robots Privacy Policy in that question? This work explores for the first time privacy in the context of consumer robotics through the lens of information communicated to users through Privacy Policies and Terms and Conditions. Privacy, personal and non-personal data are discussed under the light of the human-robot relationship, while we attempt to draw connections to dimensions related to personalization, trust, and transparency. We introduce a novel methodology to assess how the "Organization for Economic Cooperation and Development Guidelines Governing the Protection of Privacy and Trans-Border Flows of Personal Data"are reflected upon the publicly available Privacy Policies and Terms and Conditions in the consumer robotics field. We draw comparisons between the ways eight consumer robotic companies approach privacy principles. Current findings demonstrate significant deviations in the structure and context of privacy terms. Some practical dimensions in terms of improving the context and the format of privacy terms are discussed. The ultimate goal of this work is to raise awareness regarding the various privacy strategies used by robot companies while ultimately creating a usable way to make this information more relevant and accessible to users
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