Table of Contents

## About Robotics: Computational Motion Planning Course

Robotic systems typically include three components: a mechanism that is capable of exerting forces and torques on the environment, a perception system for sensing the world, and a decision and control system which modulates the robot’s behavior to achieve the desired ends.

In this course, we will consider the problem of how a robot decides what to do to achieve its goals. This problem is often referred to as Motion Planning and it has been formulated in various ways to model different situations.

You will learn some of the most common approaches to addressing this problem including graph-based methods, randomized planners, and artificial potential fields. Throughout the course, we will discuss the aspects of the problem that make planning challenging.

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## Robotics: Computational Motion Planning Quiz Answers

### Robotics: Computational Motion Planning Week 1 Quiz Answers

#### Quiz 1: Graph-based Planning Methods

Q1. If you use the Grassfire or breadth first search procedure to plan a path through a grid from a node A to a node B, then you use the same procedure to plan a path from node B to node A, will the two paths have the same length?

- Yes
- No

2. If you use the Grassfire or breadth first search procedure to plan a path through a grid from a node A to a node B, then you use the same procedure to plan a path from node B to node A, are the two paths guaranteed to be the same except in opposite directions?

- Yes
- No

Q3. If you use the grassfire algorithm to plan a path through a series of grids with increasing dimension, 2 dimensional, 3 dimensional, 4 dimensional etc. The amount of computational effort required increases ___________ with the dimension of the problem.

- linearly
- logarithmically
- exponentially
- quadratically

Q4. Generally speaking, which procedure would take less time to find a solution to a typical path planning problem on a discrete grid or graph?

- Grassfire/Breadth first search
- Dijksta’s algorithm
- A*

### Robotics: Computational Motion Planning Week 2 Quiz Answers

#### Quiz 1: Configuration Space

Q1. Configuration Space obstacles allow us to model:

- Only the shape of the robot
- Only the shapes of the obstacles in the environment
- Both the geometry of the robot and the shapes of the obstacles in the environment

Q2. The effective dimension of the configuration space of the robot is determined by:

- The dimensionality of the workspace, for example a robot restricted to the plane will have a 2 dimensional configuration space while a robot moving in 3 dimensions will have a 3 dimensional configuration space.
- The number of joints or degrees of freedom that the robot mechanism has. For example a robots that can translate and rotate in the plan will have a 3 dimensional configuration space reflecting 2 degrees of translational freedom and 1 rotational. A robot with 5 revolute joints will have a 5 dimensional configuration space.

Q3. True or false: the Visibility graph method is complete because it will always find a path through space if one exists and report failure if there is no path.

- True
- False

Q4. True or false, the Trapezoidal Decomposition method is complete because it will always find a path through space if one exists and report failure if there is no path.

- True
- Fasle

### Robotics: Computational Motion Planning Week 3 Quiz Answers

#### Quiz 1: Sampling-based Methods

Q1. True or false : The Probabilistic RoadMap procedure tries to builds a graph that captures the structure of the entire configuration space before it tries to find a route between two points.

- True
- Fasle

Q2. True or false: the Probabilistic Roadmap (PRM) method is complete because it will always find a path through space if one exists and report failure if there is no path.

- True
- False

Q3. True or false: the Rapidly Exploring Random Tree (RRT) method is complete because it will always find a path through space if one exists and report failure if there is no path.

- True
- False

### Robotics: Computational Motion Planning Week 4 Quiz Answers

#### Quiz 1: Artificial Potential Fields

Q1. Artificial Potential Fields are designed to (click all that apply):

- Attract the robot to the goal
- Repel the robot from the goal
- Attract the robot to obstacles
- Repel the robot from obstacles

Q2. True or false: the Artificial Potential field method is complete because it will always find a path through space if one exists and report failure if there is no path.

- True
- False

Q3. True or false: Artificial Potential Field methods can lead the robot to become stuck at locations other than the desired goal location.

- True
- Fasle

#### Get all Quiz Answers of Robotics Specialization

Course 01: Robotics: Aerial Robotics Quiz Answers

Course 02: Robotics: Computational Motion Planning Quiz Answers

Course 03: Robotics: Mobility Quiz Answers