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WeekDebate DayFor TeamAgainst TeamDebate proposition
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4Sep 21
Jecia Mao, Guanqing Chen, Sahil P. Patel (+5)
Alina Pan, Jiaming Wen, Kai Hua LiuA robot that fails less often than humans performing the same type of task should be considered safe enough for deployment.
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6Oct 7Carter Ung, Lujia YangChengyu Xiao, Lurui WangLearning-based methods (e.g., RL) are more useful than optimization-based methods (e.g., MPC) for deploying robots around people.
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7Oct 14Nathan Baek, Laura FleigWendy Xiao, Zixuan ZhuWe can never enforce absolute (i.e., 100%) safety for human-robot interaction.
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10Nov 2Valerie Liang, Sahil P. PatelZizhe Zhang (+2), Yuanhong ZengSafe (reinforcement) learning is fundamentally Mission Impossible for robots in real-world deployment.
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11Nov 9
Huarui Zhou, Geeta Chandra Raju Bethala (+2)
Shuning Wang, Qining ShenZero-sum games are a useful abstraction of safe robot operation in uncertain environments.
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12Nov 16Fanxiu Sophie Qiu, Yuze Cai, Qi SunSiwen Hu, Sophia Qian, Fangrong ZhangExplicit representations of human skill level and productive failures are both essential for a robot coach to effectively teach humans.
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14Dec 2 Zijun Xiang, Leyang LiQingchen Li, Nancy WuWith enough data we can solve safety and alignment in human-centered robotics.
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