Particle filters are a good way of keeping track of a set of hypotheses when performing SLAM. With regards to the FastSL

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Particle Filters Are A Good Way Of Keeping Track Of A Set Of Hypotheses When Performing Slam With Regards To The Fastsl 1 (227.4 KiB) Viewed 38 times

Particle filters are a good way of keeping track of a set of hypotheses when performing SLAM. With regards to the FastSLAM algorithm discussed in the video, select all the true statements in the following set. Select one or more: ✔a. Each particle must keep a hypothesis of the noise in the motion model * b. Each particle must keep a hypothesis of the robot's observations * ✓C. Each particle must keep a hypothesis of the position of the robot d. Particles do not keep a hypothesis of the variance in landmark positions e. Particles do not keep a hypothesis of the robot's sensor model ✓f. Each particle must keep a hypothesis of the positions of landmarks g. Particles do not keep a hypothesis of the variance in the robot's positon ✔h. Each particle must keep a hypothesis of the path followed by the robot* Your answer is incorrect. The correct answers are: Each particle must keep a hypothesis of the position of the robot, Each particle must keep a hypothesis of the positions of landmarks, Particles do not keep a hypothesis of the robot's sensor model, Particles do not keep a hypothesis of the variance in the robot's positon