Final exam

1
Final exam

• Date Thursday, May 11
• Time 1030-1230
• Place 319 DBRT (right here)

2
Final exam

• The format of the exam will be almost identical
  to that of the midterm

3
Final exam

• The format of the exam will be almost identical
  to that of the midterm
• Except that there will be 15 rather than 10
  true/false and multiple-choice questions.

4
Final exam

• The format of the exam will be almost identical
  to that of the midterm
• Except that there will be 15 rather than 10
  true/false and multiple-choice questions.
• These 30 questions will emphasize
  concepts/content that we have emphasized in class
  and in homeworks, as well as readings from Skaar
  DelCastillo, Chaps. 1-6 (same as midterm).

5
Problem portion of the final exam.
6
Problem portion of the final exam.

• This will emphasize content since the midterm,
  but that content builds upon the manipulator
  kinematics prior to the midterm.

7
Problem portion of the final exam.

• This will emphasize content since the midterm
  especially content of the homeworks -- but that
  content builds upon the manipulator kinematics
  prior to the midterm.
• No formula sheets can be brought to class, but I
  will give you, at the exam, both Lagranges
  equations and the DH sheet that was attached to
  the midterm.

8
HW 10

• I will email everyone the solution to HW 10 early
  next week.
• You may pick up your graded HW 10 in the lab,
  357C Fitzpatrick, also early next week. Will
  email you the exact times lab will be open for
  this.
• Office hours include the regular Monday/Wednesday
  office hours, both this week and next.
• Email me any time.

9
Lagranges equations
10
Simulation of system response
11
Simulation of system response

• Kinetics equations
• Actuator dynamics
• Control laws
• Reference-trajectory determination
• Initial conditions
• Numerical integration

12
Nonholonomic, wheeled robots

• Attributes of kinematics.
• Advantages
• Problems

13
Estimation

• Stochastic framework (probabilities)
• Role of redundancy.
• Role of zero-mean observation errors and
  their effect upon the weighting of samples in
  optimal estimates.
• Role of the models and model error and their
  effect upon the weighting of samples in optimal
  estimates.