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===== Working With Us ===== | ===== Working With Us ===== | ||
+ | * We are hiring [[jobs|two doctoral students]] in machine learning for computer vision or robotics. | ||
* Check our thesis topics for [[theses/start|Bachelor and Master students]]. | * Check our thesis topics for [[theses/start|Bachelor and Master students]]. | ||
- | * [[https://ellis.eu/|ELLIS]] PhD Program: [[https://ellis.eu/news/ellis-phd-program-call-for-applications-deadline-november-15-2021|Call for Applications]] | + | <html><!-- |
+ | * [[https://ellis.eu/|ELLIS]] PhD Program: [[https://ellis.eu/news/ellis-phd-program-call-for-applications-deadline-november-15-2021|Call for Applications]] | ||
+ | --></html> | ||
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===== News ===== | ===== News ===== | ||
- | <HTML><table><tr valign="top"><td>2021-11-24</td><td>Justus Piater is a panelist at a public discussion on <a href="https://www.linkedin.com/posts/elsa-innsbruck_letzte-woche-fand-zum-elsa-day-am-24112021-activity-6871397038093869057-16-7">Privacy | + | <HTML><table><tr valign="top"><td>2022-06-02</td><td>Erwan Renaudo contributes a talk <i>Deep Learning for Fast Segmentation of E-waste Devices’ |
+ | Inner Parts in a Recycling Scenario</i> at <a href="https://icprai2022.sciencesconf.org/">ICPRAI 2022</a>, Paris/online. <span class="actions"><a href="javascript:void(0)" onclick="showHide('newsitem0', 'Abstract')">[Abstract]</a></span><blockquote id="newsitem0Abstract" style="display:none">Recycling obsolete electronic devices (E-waste) is a | ||
+ | dangerous task for human workers. Automated E-waste recycling | ||
+ | is an area of great interest but challenging for current robotic | ||
+ | applications. We focus on the problem of segmenting inner parts | ||
+ | of E-waste devices into manipulable elements. First, we extend | ||
+ | a dataset of hard-drive disk (HDD) components with labelled | ||
+ | occluded and non-occluded points of view of the parts, in order | ||
+ | to increase the diversity and the quality of the learning data | ||
+ | with different angles. We then perform an extensive evaluation | ||
+ | with three different state-of-the-art models, namely CenterMask, | ||
+ | BlendMask and SOLOv2 (including variants) and two types of | ||
+ | metrics: the average precision as well as the frame rate. Our | ||
+ | results show that instance segmentation using state-of-the-art | ||
+ | deep learning methods can precisely detect complex shapes along | ||
+ | with their boundaries, as well as being suited for fast tracking of | ||
+ | parts in a robotic recycling system. (Rojas et al. 2022) | ||
+ | </blockquote></td></tr><tr valign="top"><td>2022-05-17</td><td>Erwan Renaudo gives an invited talk <i>A Brief tour of autonomous robots' "Cognition"</i> at <a href="https://www.philosophie.uni-konstanz.de/ag-mueller/aktuelles/meldungsdetails-ag-mueller/2022/5/17/event/46426-Creating-Agency-and-Cogn/tx_cal_phpicalendar/">Creating Agency and Cognition in Automated Systems: What can we learn from the Octopus? International Hybrid Workshop</a>, Innsbruck. <span class="actions"><a href="javascript:void(0)" onclick="showHide('newsitem1', 'Abstract')">[Abstract]</a></span><blockquote id="newsitem1Abstract" style="display:none">In the design of "Cognitive Robots" software architectures, | ||
+ | researchers had to face many organizational problems due to | ||
+ | the particular nature of robots. Not only should they manage | ||
+ | to achieve complex tasks with long-terms goals, but they must | ||
+ | also be reactive to their surroundings to preserve their environment. | ||
+ | We will go over several layered control paradigms developed over | ||
+ | the history of robotics and see how these can relate to the | ||
+ | knowledge about the Octopus' brain organization, and discuss | ||
+ | how the Octopus itself can inspire cognitive robotic research. | ||
+ | </blockquote></td></tr><tr valign="top"><td>2022-05-11</td><td>Justus Piater gives an invited talk <i>Robots That Learn Like Humans?</i> at <a href="https://pintofscience.at/events/innsbruck">Pint of | ||
+ | Science</a>, Innsbruck. <span class="actions"><a href="javascript:void(0)" onclick="showHide('newsitem2', 'Abstract')">[Abstract]</a></span><blockquote id="newsitem2Abstract" style="display:none">Wouldn't it be great to have a helper robot that we can | ||
+ | task with our annoying chores? How would we teach the robot to | ||
+ | perform these tasks? Can we build such robots by equipping them | ||
+ | with artificial intelligence? We will discuss how human and | ||
+ | machine learning differ and how this impacts what skills, | ||
+ | including for communication, our helper robot will be able to | ||
+ | learn.</blockquote></td></tr><tr valign="top"><td>2022-04-28</td><td>Simon Haller-Seeber contributes a talk <i>STAIR Learning Lab</i> at <a href="http://rie.science">Robotics in Education 2022</a>, online.</td></tr><tr valign="top"><td>2022-02-19</td><td>Justus Piater gives an invited talk <i>Learning as a Creative Process in Humans and | ||
+ | Machines</i> at <a href="https://www.philosophie.uni-konstanz.de/ag-mueller/online-workshop-on-agency-life-and-creativity/">Workshop | ||
+ | on “Agency, Life, and Creativity”</a>, online. <span class="actions"><a href="javascript:void(0)" onclick="showHide('newsitem4', 'Abstract')">[Abstract]</a></span><blockquote id="newsitem4Abstract" style="display:none">Humans constantly engage in creative activity such as | ||
+ | finding explanations, improving technology, or solving novel | ||
+ | problems in everyday life. Even imitating other humans, e.g. while | ||
+ | learning a new skill, is creative in that the imitator has to | ||
+ | infer the conceptual structure underlying the observed | ||
+ | manifestation and to regenerate the latter from the former. In | ||
+ | contrast, current AI-enabled agents are unable to generate and | ||
+ | draw upon such conceptual structures. Their learning is mostly | ||
+ | driven by statistics, and any ability to produce novelty is | ||
+ | largely limited to trial and error. I will try to characterize | ||
+ | this fundamental difference between learning in human and | ||
+ | artificial agents, and will discuss possible technological | ||
+ | approaches that might help close this gap.</blockquote></td></tr><tr valign="top"><td>2021-11-24</td><td>Justus Piater is a panelist at a public discussion on <a href="https://www.linkedin.com/posts/elsa-innsbruck_letzte-woche-fand-zum-elsa-day-am-24112021-activity-6871397038093869057-16-7">Privacy | ||
in the Digital Age</a>, online. (Organized by ELSA Innsbruck)</td></tr><tr valign="top"><td>2021-10-22</td><td>Justus Piater gives an invited talk <i>Robotik und KI in der Medizin – nur | in the Digital Age</a>, online. (Organized by ELSA Innsbruck)</td></tr><tr valign="top"><td>2021-10-22</td><td>Justus Piater gives an invited talk <i>Robotik und KI in der Medizin – nur | ||
Bedarfserweckung?</i> at <a href="https://medical-update-hall.com/veranstaltungen/">Medical | Bedarfserweckung?</i> at <a href="https://medical-update-hall.com/veranstaltungen/">Medical | ||
- | Update Hall 2021 – Fit für das neue Jahrzehnt</a>, UMIT, Hall in Tirol.</td></tr><tr valign="top"><td>2021-08-26</td><td>Justus Piater contributes a talk <i>Digital Science at the University of Innsbruck</i> at Aurora Research Conference Digital Society & Global Citizenship, Vrije Universiteit Amsterdam. <span class="actions"><a href="javascript:void(0)" onclick="showHide('newsitem2', 'Abstract')">[Abstract]</a></span><blockquote id="newsitem2Abstract" style="display:none">Growing data processing capacities and progress in | + | Update Hall 2021 – Fit für das neue Jahrzehnt</a>, UMIT, Hall in Tirol.</td></tr><tr valign="top"><td>2021-08-26</td><td>Justus Piater contributes a talk <i>Digital Science at the University of Innsbruck</i> at Aurora Research Conference Digital Society & Global Citizenship, Vrije Universiteit Amsterdam. <span class="actions"><a href="javascript:void(0)" onclick="showHide('newsitem7', 'Abstract')">[Abstract]</a></span><blockquote id="newsitem7Abstract" style="display:none">Growing data processing capacities and progress in |
analytical methods and artificial intelligence are motivating | analytical methods and artificial intelligence are motivating | ||
entire branches of science to raise new questions and to develop | entire branches of science to raise new questions and to develop | ||
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aspects of digital science.</blockquote></td></tr><tr valign="top"><td>2021-08-24</td><td>Justus Piater contributes a lecture <i>Picking and Placing</i> at <a href="https://www.uibk.ac.at/informatik/forschung/gmar-robotics-school-2021.html">2021 GMAR Summer School</a>, Villa Blanka, Innsbruck.</td></tr><tr valign="top"><td>2021-07-01</td><td>Justus Piater and Matteo Saveriano give an invited talk <i>Making Robots Learn to Perceive and Act with Understanding</i> at <a href="https://webservices.scientificnet.org/rest/entries/api/v1/blobs/200894">Workshop | aspects of digital science.</blockquote></td></tr><tr valign="top"><td>2021-08-24</td><td>Justus Piater contributes a lecture <i>Picking and Placing</i> at <a href="https://www.uibk.ac.at/informatik/forschung/gmar-robotics-school-2021.html">2021 GMAR Summer School</a>, Villa Blanka, Innsbruck.</td></tr><tr valign="top"><td>2021-07-01</td><td>Justus Piater and Matteo Saveriano give an invited talk <i>Making Robots Learn to Perceive and Act with Understanding</i> at <a href="https://webservices.scientificnet.org/rest/entries/api/v1/blobs/200894">Workshop | ||
and Open Lab on Field Robotics - Interdisciplinary aspects of | and Open Lab on Field Robotics - Interdisciplinary aspects of | ||
- | robotics and its applications in outdoor scenarios</a>, NOI Techpark, Bolzano, Italy.</td></tr><tr valign="top"><td>2021-05-26</td><td>Justus Piater contributes a talk <i>Intelligente und interaktive Systeme</i> at <a href="http://www.gmar.at/aktuell/">GMAR Robotics Science | + | robotics and its applications in outdoor scenarios</a>, NOI Techpark, Bolzano, Italy.</td></tr></table></HTML> |
- | Talks</a>, online.</td></tr><tr valign="top"><td>2021-03-24</td><td>Justus Piater gives an invited lecture <i>Machine Learning, Perception, And Abstract Concepts</i> at Invited lecture at Ontario Tech U, Canada, online. <span class="actions"><a href="javascript:void(0)" onclick="showHide('newsitem6', 'Abstract')">[Abstract]</a></span><blockquote id="newsitem6Abstract" style="display:none">With every spectacular achievement of a machine learning | + | |
- | system, the long-elusive AI breakthrough is popularly proclaimed | + | |
- | to be just around the corner. Most recent successes have been due | + | |
- | in large part to massive data and computation, in particular using | + | |
- | deep artificial neural networks. But can artificial cognition | + | |
- | really be achieved just by further scaling up existing | + | |
- | machine-learning techniques? I discuss examples of simple, | + | |
- | perceptual problems that are easily solved by humans but very | + | |
- | difficult for today's machine learning methods. These problems | + | |
- | reflect how humans conceptualize their world. Their mastery is | + | |
- | thus likely to be an essential prerequisite for autonomous robots | + | |
- | to attain higher levels of cognitive abilities. To get there, a | + | |
- | few core issues can be identified that should drive research in | + | |
- | cognitive robotics.</blockquote></td></tr><tr valign="top"><td>2021-01-28</td><td>Matteo Saveriano gives an invited talk <i>Making robots to learn from human observation?</i> at <a href="https://www.bmeia.gv.at/en/austrian-embassy-ottawa/news/events/detail/article/showcasing-young-austrian-scholars-and-scientists-an-original-seven-part-virtual-lectures-ser/">Showcasing Young Austrian Scholars and Scientists, Austrian cultural forum, Ottawa</a>, online.</td></tr><tr valign="top"><td>2021-01-14</td><td>Matteo Saveriano gives an invited talk <i>Hierarchical action decomposition and motion learning for the execution of manipulation tasks</i> at <a href="http://www.gmar.at/aktuell/">Hello Tyrol calling! Robotics Talk online, GMAR, Innsbruck</a>, online.</td></tr><tr valign="top"><td>2020-11-19</td><td>Justus Piater gives an invited talk <i>Machine Learning in Robotics</i> at <a href="https://baiome.org/">bAIome PI Talk, Center for | + | |
- | Biomedical AI, University Medical Center Hamburg-Eppendorf</a>, online. <span class="actions"><a href="javascript:void(0)" onclick="showHide('newsitem10', 'Abstract')">[Abstract]</a></span><blockquote id="newsitem10Abstract" style="display:none">Machine Learning increasingly equips robots with | + | |
- | learning capabilities and flexibility. This will enable them to | + | |
- | act purposefully in unstructured environments and to react to | + | |
- | unforeseen events. People can teach them intuitively to perform | + | |
- | tasks instead of having to program them in painstaking ways. | + | |
- | Robots can learn from experience and can improve their behavior | + | |
- | over time. In this talk I will give an overview of methods, | + | |
- | opportunities, and challenges of machine learning in | + | |
- | robotics.</blockquote></td></tr></table></HTML> | + | |
[[news|Older News]] | [[news|Older News]] |