ABCDEFGHIJKLMNOPQRSTUVWX
1
WeekDebate DayFor TeamAgainst TeamDebate proposition
2
4Sep 21Jecia Mao, Guanqing Chen, Sahil P. PatelAlina 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.
3
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.
4
7Oct 14Nathan Baek, Laura FleigNadia Kim, Wendy Xiao, Zixuan ZhuWe can never enforce absolute (i.e., 100%) safety for human-robot interaction.
5
10Nov 2Valerie Liang, Sahil P. PatelAditya Shrinivasan, Yuanhong ZengSafe (reinforcement) learning is fundamentally Mission Impossible for robots in real-world deployment.
6
11Nov 9Luoxin Ye, Huarui ZhouShuning Wang, Qining ShenZero-sum games are a useful abstraction of safe robot operation in uncertain environments.
7
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.
8
14Dec 2Zizhe Zhang, Zijun Xiang, Leyang LiQingchen Li, Nancy Wu, Geeta Chandra Raju BethalaWith enough data we can solve safety and alignment in human-centered robotics.
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100