STUPIDSID
Answer following questions in brief:-
1(a)
Briefly explain the role of Robotics in industries.
5 M
1(b)
Explain in brief the forward and reverse Kinematics.
5 M
1(c)
Explain heuristic function with example.
5 M
1(d)
List sensors used for reactive robot.
5 M
2(a)
Describe DH parameters with suitable sketch.
6 M
2(b)
Find kinematic transformation matrix using D-H method for following robot.
14 M
3(a)
Explain how will you formulate search problem? Formulate 8 puzzle problem.
6 M
3(b)
Explain Depth-first search with example.
4 M
3(c)
What do you mean by an admissible heuristic function? Explain with example.
5 M
3(d)
Describe IDA* search giving suitable example.
5 M
4(a)
Describe backward chaining algorithm for propositional logic.
6 M
4(b)
Represent following sentences in first order logic using consistent vocabulary.
(i) Every person who buys a policy is smart.
(ii) No person buys an expensive policy.
(iii) There is an agent who sells policies only to people who are not insured.
(iv) There is an agent who sells policies only to people who are not insured.
(i) Every person who buys a policy is smart.
(ii) No person buys an expensive policy.
(iii) There is an agent who sells policies only to people who are not insured.
(iv) There is an agent who sells policies only to people who are not insured.
4 M
4(c)
Describe backward chaining with example.
10 M
5(a)
You have a new burglar alarm installed. It reliably detects burglary, but also responds to minor earthquakes. Two neighbors, John and Mary, promise to call the police when they hear the alarm. John almost always calls when he hears the alarm, but sometimes confuses the alarm with the phone ringing and calls then also. On the other hand, Mary likes loud music and sometimes doesn't hear the alarm. Given evidence about who has and hasn't called, you'd like to estimate the probability of a burglary.
Draw a Bayesian network for this domain with suitable probability tables.
Draw a Bayesian network for this domain with suitable probability tables.
10 M
5(b)
Give steps in designing the Reactive Behavioral System.
10 M
6(a)
What is planning problem? How it differs from search problem?
5 M
6(b)
Explain Screw Transformation.
5 M
6(c)
Explain supervised, unsupervised and reinforcement learning with example.
10 M
7(a)
Describe following electrical actuators: DC motor; Synchronous motor; Stepper motor.
10 M
7(b)
Explain following sensors used in robotic applications: Potentiometer; Inductor; Capacitor; LVDT.
10 M
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