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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 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*

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*

Database System Concepts
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
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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 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
Transcribed Image Text: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
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