<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Past &amp; Upcoming Events | AI LAB @ UniBw Munich</title><link>https://unibwm-ifs-ailab.github.io/not_used_event/</link><atom:link href="https://unibwm-ifs-ailab.github.io/not_used_event/index.xml" rel="self" type="application/rss+xml"/><description>Past &amp; Upcoming Events</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Wed, 28 May 2025 00:00:00 +0000</lastBuildDate><image><url>https://unibwm-ifs-ailab.github.io/media/icon_hu4951135369306263711.png</url><title>Past &amp; Upcoming Events</title><link>https://unibwm-ifs-ailab.github.io/not_used_event/</link></image><item><title>Project MOREALIS Completion</title><link>https://unibwm-ifs-ailab.github.io/not_used_event/morealis-abschluss-2025/</link><pubDate>Wed, 28 May 2025 00:00:00 +0000</pubDate><guid>https://unibwm-ifs-ailab.github.io/not_used_event/morealis-abschluss-2025/</guid><description>&lt;p>During the course of this project, we worked together to develop a prototypical assistance system capable of continuously monitoring the pilot and the aircraft and intervening when required to ensure flight safety. On the day of the project final meeting, Prakash Jamakatel presented the work done by the UniBw M - FMFF in the development of the cognitive state estimation system, context determination system with plan and goal recognition, dialogue system, intervention management, and flight path planning system. On the same day, together with other project partners, we also demonstrated the cockpit prototype.&lt;/p>
&lt;p>Special thanks to all partners for making MOREALIS project a success!&lt;/p></description></item><item><title>LEAP @ CoRL 2024</title><link>https://unibwm-ifs-ailab.github.io/not_used_event/corl2024/</link><pubDate>Sat, 09 Nov 2024 00:00:00 +0000</pubDate><guid>https://unibwm-ifs-ailab.github.io/not_used_event/corl2024/</guid><description>&lt;p>At the &lt;strong>LEAP (Learning Effective Abstractions for Planning)&lt;/strong> workshop, held as part of the Conference on Robot Learning (CoRL) 2024, Björn Döschl presented his latest research titled &lt;em>&amp;ldquo;Say-REAPEx: An LLM-Modulo UAV Online Planning Framework for Search and Rescue.&amp;rdquo;&lt;/em> The event brought together leading researchers in planning and robot learning, with a focus on abstraction-based methods. The workshop fostered engaging discussions and offered valuable feedback from peers working at the forefront of AI and robotics.&lt;/p>
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