<html>
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8">
</head>
<body style="overflow-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;">
<div>
<div>IROS deadline is behind us, so it’s time to start your submission to the 2nd BARN Challenge at ICRA 2023! </div>
<div><br>
</div>
<div>Submission Form: <a href="https://docs.google.com/forms/d/e/1FAIpQLScYKxIZ2HYSDMLx3BxlYkxugmpy1OrrewYk_MSlDOv2hei7LQ/viewform?usp=sf_link">https://docs.google.com/forms/d/e/1FAIpQLScYKxIZ2HYSDMLx3BxlYkxugmpy1OrrewYk_MSlDOv2hei7LQ/viewform?usp=sf_link</a></div>
<div> </div>
<div>Competition Website: <a href="https://cs.gmu.edu/~xiao/Research/BARN_Challenge/BARN_Challenge23.html">https://cs.gmu.edu/~xiao/Research/BARN_Challenge/BARN_Challenge23.html</a></div>
<div> </div>
<div>Participation Instructions: <a href="https://github.com/Daffan/nav-competition-icra2022">https://github.com/Daffan/nav-competition-icra2022</a></div>
<div><br>
</div>
<div>Lessons Learned from The BARN Challenge 2022 Last Year: <a href="https://cs.gmu.edu/~xiao/papers/barn22_report.pdf">https://cs.gmu.edu/~xiao/papers/barn22_report.pdf</a> </div>
<div><br>
</div>
<div> </div>
<div>Dear roboticists,</div>
<div> </div>
<div>are you interested in agile robot navigation in highly constrained spaces with a lot of obstacles around, e.g., cluttered households or after-disaster scenarios? Do you think mobile robot navigation is mostly a solved problem? Are you looking for a hands-on
project for your robotics class, but may not have (sufficient) robot platforms for your students?</div>
<div> </div>
<div>If your answer is yes to any of the above questions, we sincerely invite you to participate in our (2nd) ICRA 2023 BARN Challenge (<a href="https://cs.gmu.edu/~xiao/Research/BARN_Challenge/BARN_Challenge23.html">https://cs.gmu.edu/~xiao/Research/BARN_Challenge/BARN_Challenge23.html</a>)!
The BARN Challenge aims at evaluating state-of-the-art autonomous navigation systems to move robots through highly constrained environments in a safe and efficient manner. The task is to navigate a standardized Clearpath Jackal robot from a predefined start
to a goal location as quickly as possible without any collision. The challenge will take place both in the simulated BARN dataset and in physical obstacle courses at ICRA2023.</div>
<div> </div>
<div>1. The competition task is designing ground navigation systems to navigate through all 300 BARN environments (<a href="https://cs.gmu.edu/~xiao/Research/BARN/BARN.html">https://cs.gmu.edu/~xiao/Research/BARN/BARN.html</a>) and physical obstacle courses
constructed at ICRA2023 as fast as possible without collision.</div>
<div> </div>
<div>2. The 300 BARN environments can be the training set for learning-based methods, or to design classical approaches in. During the simulation competition, we will generate another 50 unseen environments unavailable to the participants before the competition.</div>
<div> </div>
<div>3. We will standardize a Jackal robot in the Gazebo simulation, including a Hokuyo 2D LiDAR, motor controller of 2m/s max speed, etc.</div>
<div> </div>
<div>4. Participants can use any approaches to tackle the navigation problem, such as using classical sampling-based or optimization-based planners, end-to-end learning, or hybrid approaches. We will provide baselines for reference. </div>
<div> </div>
<div>5. A standardized scoring system is provided on the website.</div>
<div> </div>
<div>6. We will invite the top teams in simulation to compete in the real world. The team who achieves the fastest collision-free navigation in the physical obstacle courses wins.</div>
<div> </div>
<div>If you are interested in participating, please submit your navigation system at <a href="https://docs.google.com/forms/d/e/1FAIpQLScYKxIZ2HYSDMLx3BxlYkxugmpy1OrrewYk_MSlDOv2hei7LQ/viewform?usp=sf_link">https://docs.google.com/forms/d/e/1FAIpQLScYKxIZ2HYSDMLx3BxlYkxugmpy1OrrewYk_MSlDOv2hei7LQ/viewform?usp=sf_link</a></div>
<div> </div>
<div>Co-Organizers:</div>
<div>Xuesu Xiao (George Mason University / Everyday Robots)</div>
<div>Zifan Xu (UT Austin)</div>
<div>Garrett Warnell (US Army Research Lab / UT Austin)</div>
<div>Peter Stone (UT Austin / Sony AI)</div>
<div> </div>
<div>Sponsor:</div>
<div>Clearpath Robotics, <a href="https://clearpathrobotics.com/">https://clearpathrobotics.com/</a></div>
<div> </div>
<div><br>
</div>
<div>Thanks</div>
<div>Xuesu</div>
</div>
<br>
<div>
<div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);"><br class="Apple-interchange-newline">
-----------------------</div>
<div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);">Xuesu Xiao, Ph.D.<br>
--<br>
Assistant Professor<br>
Department of Computer Science<br>
George Mason University<br>
<a href="mailto:xiao@gmu.edu">xiao@gmu.edu</a><br>
<a href="https://cs.gmu.edu/~xiao/">https://cs.gmu.edu/~xiao/</a><br>
</div>
</div>
</body>
</html>