概率机器人第二章课后习题 第一题

  1. 机器人使用一个可以测量0~3m距离的传感器。为了简化,假定真实的距离在这个范围中均匀分布。很不幸的是,传感器会坏掉。当传感器故障时,不管传感器的锥形测量范围内实际测距结果应该是多少,其输出测距值均小于1m,已知对于传感器故障的先验概率是 p = 0.01
    设想机器人查询了N次传感器,每次测量值都小于1m。对于 N = 1 , 2 , . . . , 10 的传感器故障后的验概率是多少?用公式表示相关的概率模型。

解:
X 表示传感器的状态, X = 0 表示传感器故障, X = 1 表示传感器没有故障。且 P ( X 0 = 1 ) = 0.99 , P ( X 0 = 0 ) = 0.01
Z 表示传感器的测距值, P ( Z < 1 | X 0 = 0 ) = 1 , P ( Z < 1 | X 0 = 1 ) = 1 3
传感器的故障的后验概率可以表示为,

P ( X = 0 | Z < 1 ) = P ( Z < 1 | X = 0 ) P ( X = 0 ) P ( Z < 1 ) = P ( Z < 1 | X = 0 ) P ( X = 0 ) P ( Z < 1 | X = 0 ) P ( X = 0 ) + P ( Z < 1 | X = 1 ) P ( X = 1 )

N = 1 的时候,传感器故障的后验概率为:

P ( X 1 = 0 | Z < 1 ) = P ( Z < 1 | X 0 = 0 ) P ( X 0 = 0 ) P ( Z < 1 ) = P ( Z < 1 | X 0 = 0 ) P ( X 0 = 0 ) P ( Z < 1 | X 0 = 0 ) P ( X 0 = 0 ) + P ( Z < 1 | X 0 = 1 ) P ( X 0 = 1 ) = 1 × 0.01 1 × 0.01 + 1 3 × 0.99 = 1 34 0.029

此时传感器故障的概率分别为: P ( X 1 = 0 | Z < 1 ) = 0.029 , P ( X 1 = 1 | Z < 1 ) = 0.971
N = 2 的时候,传感器故障的后验概率为:

P ( X 2 = 0 | Z < 1 ) = P ( Z < 1 | X 1 = 0 ) P ( X 1 = 0 ) P ( Z < 1 ) = P ( Z < 1 | X 1 = 0 ) P ( X 1 = 0 ) P ( Z < 1 | X 1 = 0 ) P ( X 1 = 0 ) + P ( Z < 1 | X 1 = 1 ) P ( X 1 = 1 ) = 1 × 0.029 1 × 0.029 + 1 3 × 0.971 0.352

此时传感器故障的概率分别为: P ( X 2 = 0 | Z < 1 ) = 0.352 , P ( X 2 = 1 | Z < 1 ) = 0.648
以此类推:
N = 3 的时候,传感器故障的后验概率为: P ( X 3 = 0 | Z < 1 ) = 0.619 , P ( X 3 = 1 | Z < 1 ) = 0.381
N = 4 的时候,传感器故障的后验概率为: P ( X 4 = 0 | Z < 1 ) = 0.829 , P ( X 4 = 1 | Z < 1 ) = 0.171
N = 5 的时候,传感器故障的后验概率为: P ( X 5 = 0 | Z < 1 ) = 0.935 , P ( X 5 = 1 | Z < 1 ) = 0.065
N = 6 的时候,传感器故障的后验概率为: P ( X 6 = 0 | Z < 1 ) = 0.977 , P ( X 6 = 1 | Z < 1 ) = 0.023
N = 7 的时候,传感器故障的后验概率为: P ( X 7 = 0 | Z < 1 ) = 0.992 , P ( X 7 = 1 | Z < 1 ) = 0.008
N = 8 的时候,传感器故障的后验概率为: P ( X 8 = 0 | Z < 1 ) = 0.997 , P ( X 8 = 1 | Z < 1 ) = 0.003
N = 9 的时候,传感器故障的后验概率为: P ( X 9 = 0 | Z < 1 ) = 0.998 , P ( X 9 = 1 | Z < 1 ) = 0.002
N = 10 的时候,传感器故障的后验概率为: P ( X 10 = 0 | Z < 1 ) = 0.999 , P ( X 10 = 1 | Z < 1 ) = 0.001

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转载自blog.csdn.net/u012836279/article/details/80025363