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IROS 2024 deadline is behind us. Now it’s time to start preparing for The 3rd BARN Challenge at ICRA 2024! See you in Japan in May!
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Submission Form: <a href="https://docs.google.com/forms/d/e/1FAIpQLSfZLMVluXE-HWnV9lNP00LuBi3e9HFOeLi30p9tsHUViWpqrA/viewform?usp=sf_link">https://docs.google.com/forms/d/e/1FAIpQLSfZLMVluXE-HWnV9lNP00LuBi3e9HFOeLi30p9tsHUViWpqrA/viewform?usp=sf_link</a><br>
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Competition Website: <a href="https://cs.gmu.edu/~xiao/Research/BARN_Challenge/BARN_Challenge24.html">https://cs.gmu.edu/~xiao/Research/BARN_Challenge/BARN_Challenge24.html</a><br>
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Participation Instructions: <a href="https://github.com/Daffan/nav-competition-icra2022">https://github.com/Daffan/nav-competition-icra2022</a><br>
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Lessons Learned from The BARN Challenge 2023: <a href="https://cs.gmu.edu/~xiao/papers/barn23_report.pdf">https://cs.gmu.edu/~xiao/papers/barn23_report.pdf</a> <br>
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Lessons Learned from The BARN Challenge 2022: <a href="https://cs.gmu.edu/~xiao/papers/barn22_report.pdf">https://cs.gmu.edu/~xiao/papers/barn22_report.pdf</a> <br>
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Dear roboticists,<br>
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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?<br>
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If your answer is yes to any of the above questions, we sincerely invite you to participate in our (3rd) ICRA 2024 BARN Challenge (<a href="https://cs.gmu.edu/~xiao/Research/BARN_Challenge/BARN_Challenge24.html">https://cs.gmu.edu/~xiao/Research/BARN_Challenge/BARN_Challenge24.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 ICRA2024.<br>
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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 ICRA2024 as fast as possible without collision.<br>
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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.<br>
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3. We will standardize a Jackal robot in the Gazebo simulation, including a Hokuyo 2D LiDAR, motor controller of 2m/s max speed, etc.<br>
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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. <br>
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5. A standardized scoring system is provided on the website.<br>
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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.<br>
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If you are interested in participating, please submit your navigation system at <a href="https://docs.google.com/forms/d/e/1FAIpQLSfZLMVluXE-HWnV9lNP00LuBi3e9HFOeLi30p9tsHUViWpqrA/viewform?usp=sf_link">https://docs.google.com/forms/d/e/1FAIpQLSfZLMVluXE-HWnV9lNP00LuBi3e9HFOeLi30p9tsHUViWpqrA/viewform?usp=sf_link</a><br>
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Co-Organizers:<br>
Xuesu Xiao (George Mason University)<br>
Zifan Xu (UT Austin)<br>
Garrett Warnell (US Army Research Lab / UT Austin)<br>
Peter Stone (UT Austin / Sony AI)<br>
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Sponsor:<br>
Clearpath Robotics, <a href="https://clearpathrobotics.com/">https://clearpathrobotics.com/</a><br>
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Thanks<br>
Xuesu<br>
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Xuesu Xiao, Ph.D.<br>
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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></div>
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