新手区slam基础孙作雷robot master distribution.pptx

新手区slam基础孙作雷robot master distribution.pptx

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The Fundamental of Mobile Robot Machine Perception and Interaction Group (MPIG) assignments.shmtu@ Send an email with specified subject ‘Robot stuff’ to assignments.shmtu@ An automatic reply will come. All you need would be included! assignments.shmtu@ /sunzuolei/robotcourse All the codes accompanying this course are open-sourced at Github. The project homepage: /sunzuolei/robotcourse.git The git repository: Learn more about git: /wiki/Git_(software) /p/tortoisegit/ The best GUI-based git client on Windows: Gaussian Distribution 30 April 1777 – 23 February 1855 German mathematician and physical scientist /wiki/Normal_distribution Variance What is this? Expectation Mean 17 17 19 18 19 17 17 19 18 19 What is the expectation of the five students? 17 17 19 18 19 The uniform distribution Expectation 18 Continuous space Discrete space Expectation 17 17 19 18 19 18 7 23 38 4 18 17 17 19 18 19 18 7 23 38 4 18 18 Are the two datasets with the same expectation the same? 17 17 19 18 19 18 7 23 38 4 18 18 The former samples are clustered very close to 18 whereas the latter samples are really far from 18 in most cases. 17 17 19 18 19 18 7 23 38 4 18 18 The E doesn’t capture the spread of the data. Can we calculate this somehow? 17 17 19 18 19 18 Subtract the mean / E from each data item then compute the E. -1 -1 1 0 1 7 23 38 4 18 18 -11 5 20 -14 0 0 0 17 17 19 18 19 18 -1 -1 1 0 1 7 23 38 4 18 18 -11 5 20 -14 0 0 0 1 1 1 0 1 0.8 121 25 400 196 0 148.4 Mean Mean 17 17 19 18 19 18 7 23 38 4 18 18 0.8 148.4 Mean Mean Variance Variance The variance is a measure of how far the data is spread. Its small if the data is centered around the mean, its large if the data falls far away from the mean. 17 17 19 18 19 18 7 23 38 4 18 18 0.8 148.4 Mean Mean Variance Variance Expectation / Mean (Co)Variance Expectation / Mean (Co)Variance (Co)Variance Variance is the average quadratic deviation from the mean. If taking the square root of it, then we get standard deviation. function mu = com

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