CS 7638 | QUESTIONS AND ANSWERS | 2025/2026
UPDATE | WITH PASSED SOLUTION
explain localization (histogram filter) Answer - Localization assumes that the
map of the environment is already known. You then use measurements and
movements to build a belief of where the robot is in the environment.
What is the limit distribution of a robot? (infinite movements but no
measurements) Answer - The result will be a uniform distribution. So the more
we more, the more information we will lose about the environment and our
location.
What is the formula for entropy? Answer - -SUM(P(Xi) log(P(Xi))
In Histogram Filter, how is the Sense/measurement function calculated?
Answer - Using Products (multiplication) followed by normalization. (Using
baye's theorem)
In Histogram Filter,, how is the Move/motion function calculated? Answer -
Using convolution (addition). (using total probability). The operation of a
weighted sum is called a convolution.
How does the memory scale wrt. the number of state variables in a Localization
method? (linearly? Quadratically? exponentially) Answer - Exponentially. If
each variable had 20 possible values (bins) then the joint probability table will
be 20^n where n is the number state dimensions.
, What is the number of one issue with localization grid (histogram) method?
Answer - The memory allocation is exponential.
What is standford's first self driving car called? Answer - Junior - uses lasers
and radar
What is Kalman filter used for? Answer - Tracking & localization of the robot. It
helps track the movement of other objects in our environment so we don't
collide with them.
Is Kalman Filter discrete or continious? Answer - continious
Is Kalman filter uni-modal or multi-modal? Answer - uni-modal (using
Gaussians)
Is Monte Carlo Localization discrete or continuous? Answer - discrete
Is Monte Carlo Localization Uni-modal or Multi-modal? In (Histogram Filter)
Answer - Multi-modal
Are particle filters discrete or continious? Answer - Continious
Are particle filters uni-modal or multi-modal? Answer - multi-modal
Explain a gaussian Answer - A gaussian is a normal distribution (uni-modal)
where the area underneath sums up to 1.
In Kalman filters, how is measurement update calculated? Answer - Using
Baye's rule (products)
UPDATE | WITH PASSED SOLUTION
explain localization (histogram filter) Answer - Localization assumes that the
map of the environment is already known. You then use measurements and
movements to build a belief of where the robot is in the environment.
What is the limit distribution of a robot? (infinite movements but no
measurements) Answer - The result will be a uniform distribution. So the more
we more, the more information we will lose about the environment and our
location.
What is the formula for entropy? Answer - -SUM(P(Xi) log(P(Xi))
In Histogram Filter, how is the Sense/measurement function calculated?
Answer - Using Products (multiplication) followed by normalization. (Using
baye's theorem)
In Histogram Filter,, how is the Move/motion function calculated? Answer -
Using convolution (addition). (using total probability). The operation of a
weighted sum is called a convolution.
How does the memory scale wrt. the number of state variables in a Localization
method? (linearly? Quadratically? exponentially) Answer - Exponentially. If
each variable had 20 possible values (bins) then the joint probability table will
be 20^n where n is the number state dimensions.
, What is the number of one issue with localization grid (histogram) method?
Answer - The memory allocation is exponential.
What is standford's first self driving car called? Answer - Junior - uses lasers
and radar
What is Kalman filter used for? Answer - Tracking & localization of the robot. It
helps track the movement of other objects in our environment so we don't
collide with them.
Is Kalman Filter discrete or continious? Answer - continious
Is Kalman filter uni-modal or multi-modal? Answer - uni-modal (using
Gaussians)
Is Monte Carlo Localization discrete or continuous? Answer - discrete
Is Monte Carlo Localization Uni-modal or Multi-modal? In (Histogram Filter)
Answer - Multi-modal
Are particle filters discrete or continious? Answer - Continious
Are particle filters uni-modal or multi-modal? Answer - multi-modal
Explain a gaussian Answer - A gaussian is a normal distribution (uni-modal)
where the area underneath sums up to 1.
In Kalman filters, how is measurement update calculated? Answer - Using
Baye's rule (products)
