Advanced Programming Techniques
COSC1076 | Semester 1 2022
Assignment 1 | Implementing a Path Planning Algorithm
Assessment Type
Copyright By PowCoder代写 加微信 powcoder
Individual Assessment. Clarifications/updates may be made via announcements/rel- evant discussion forums.
Due Date Silence Policy Weight Submission
1 Overview
11.59pm, Sunday 10 April 2022 (Before Week 7)
From 5.00pm, Friday 08 April 2022 (Week 6)
30% of the final course mark
Online via Canvas. Submission instructions are provided on Canvas.
will implement a simplified algorithm for Path Planning, and use it with a simple In this assignment you will:
In this assignment you
simulated 2D robot moving around a room.
• Practice the programming skills such as: – Pointers
– Dynamic Memory Management
• Implement a medium size C++ program using predefined classes • Use a prescribed set of C++11/14 language features
This assignment is marked on three criteria, as given on the Marking Rubric on Canvas:
• Milestone 1: Writing Tests.
• Milestone 2-4: Implementation of the Path Planner.
• Style & Code Description: Producing well formatted, and well
documented code.
1.1 Relevant Lecture/Lab Material
Figure 1: An example robot
To complete this assignment, you will require skills and knowledge from workshop and lab material for Weeks 2 to 4 (inclusive). You may find that you will be unable to complete some of the activities until you have completed the relevant lab work. However, you will be able to commence work on some sections. Thus, do the work you can initially, and continue to build in new features as you learn the relevant skills.
1.2 Learning Outcomes
This assessment relates to all of the learning outcomes of the course which are:
• Analyse and Solve computing problems; Design and Develop suitable algorithmic solutions using software concepts and skills both (a) introduced in this course, and (b) taught in pre-requisite courses; Implement and Code the algorithmic solutions in the C++ programming language.
• Discuss and Analyse software design and development strategies; Make and Justify choices in software design and development; Explore underpinning concepts as related to both theoretical and practical applications of software design and development using advanced programming techniques.
• Discuss, Analyse, and Use appropriate strategies to develop error-free software including static code anal- ysis, modern debugging skills and practices, and C++ debugging tools.
• Implement small to medium software programs of varying complexity; Demonstrate and Adhere to good programming style, and modern standards and practices; Appropriately Use typical features of the C++ language include basic language constructs, abstract data types, encapsulation and polymorphism, dy- namic memory management, dynamic data structures, file management, and managing large projects containing multiple source files; Adhere to the C++14 ISO language features.
• Demonstrate and Adhere to the standards and practice of Professionalism and Ethics, such as described in the ACS Core Body of Knowledge (CBOK) for ICT Professionals.
2 Introduction
One challenge in robotics is called path planning. This is the process of the robot figuring out how to navigate between two points within some environment. In this assignment you will implement a simplified path planning algorithm for a robot moving about a simple 2D environment – a rectangular room with obstacles.
We will represent a simple 2D environment as a grid of ASCII characters. For example1:
Aspects of the environment are represented by different symbols:
Symbol Meaning
==========
=S…….=
========.=
=……=.=
==.=.=…=
=..=..=.==
=.===.=..=
=..==G==.=
===.======
==========
= (equal) . (dot) S
Wall or Obstacle within the environment. The robot cannot pass obstacles Empty/Open Space.
The start position of the robot
The goal point that the robot is trying to reach.
Each location in the environment is indexed by a (col,row) co-ordinate. The top-left corner of the environment is always the co-ordinate (0,0), the col-coordinate increases right-wards, and the row-coordinate increases down-wards. For the above environment, the four corners have the following co-ordinates:
Two dimensional environments can be designed in different ways. For this assignment we will use environments where:
1. There is one goal (ending) point denoted by character “G”. 2. The environment is always surrounded by walls.
1for illustration purposes we are using an environment of 10×10, but the grid size for the implementation is different. Please read the document carefully to find the appropriate grid size for each milestone.
(0,0) . . (9,0) .. ..
(0,9) . . (9,9)
3. The environment can contains junctions, corridors “open” space, loops or islands. For the purposes of this assignment we will make several important assumptions:
• The robot knows the map of the whole environment it is in, at the start.
• Robot can only be located at cells marked as empty/open spaces.
• It may not be possible for the robot to reach every empty space.
• The robot can move-to (or reach) any one of 4 cells, that are to the left, right, up, or down from the
robots originating cell. Robot cannot move diagonally.
• For this assignment the direction the robot is “facing” is ignored.
In this assignment, the path planning problem is divided into two parts:
1. Identify Reachable Positions: Identify all possible locations that the robot can reach given the starting position, and calculate the number of steps need to reach each position from start. The pseudo-code for the algorithm you need to implement is provided to you in Section 3.2.1.
2. Path Planning: Using the identified reachable positions, finds a path from the robot’s starting position to the specified goal co-ordinate. You will have to develop the pseudo-code for this part. A description of the algorithm you need to implement is provided to you in Section 3.3.1.
While there are many ways to navigate a 2D environment, you must implement the algorithms provided in this document. If you don’t, you will receive a NN grade.
3 Assessment Details
The task for this assignment is to write a full C++ program that:
1. Reads in a 20×20 environment from standard-input (std::cin).
2. Finds the robot’s starting position within the environment (denoted by “S”).
3. Executes the Identify Reachable Positions algorithm (Section 3.2.1).
4. Executes the Path Planning algorithm (Section 3.3.1) to find a path.
5. Prints out the environment and the path to be followed by robot to standard output (std::cout).
You may assume that the environment is a fixed size of 20×20, except for Milestone 4.
This assignment has four Milestones. To receive a PA/CR grade, you only need to complete Milestones 1 & 2. To receive higher grades, you will need to complete Milestones 3 & 4. Take careful note of the Marking Rubric on Canvas. Milestones should be completed in sequence. For example, if you attempt Milestone 3, but your Milestone 2 is buggy, you won’t get any marks for Milestone 3.
3.1 Milestone 1: Writing Tests
Before starting out on implementation, it is good practice to write some tests. We are going to use I/O-blackbox testing. That is, we will give our program an environment to solve (as Input), and then test that our program’s Output is what we expect it to be.
To run I/O-blackbox testing, we need to design appropriate environments and workout what should be the output if our program is 100% correct.
A test consists of two text-files:
1.
2.
A test passes if the output of your program matches the expected output. Section 4.4 explains how to run your
tests using the diff tool. We will also do a demo in the lectorial (Workshop).
You should aim to write a minimum of four tests2. We will mark your tests based on how suitable they are for testing that your program is 100% correct. Just having four tests is not enough for full marks. Identify scenarios where your program might break and construct tests accordingly.
The starter code contains a folder with one sample test case. This should give you an idea of how your tests should be formatted (the sample will not be counted when marking).
2This is upto M3, for M4 you should write additional tests.
3.2 Milestone 2: Identify Reachable Positions
In this milestone, you will implement a Reachable Positions algorithm that starts from the “start” position and explore the environment in a systematic way. The pseudo-code for the algorithm you need to implement is provided below:
3.2.1 Reachable Positions Algorithm
In this algorithm, a position in the environment that the robot can reach is denoted by a node and each node will contain the (col,row) co-ordinate and distanceToS (the distance that the algorithm took to reach that position from the robot’s starting position, S).
Pseudocode for the Reachable Positions algorithm
4 5 6 7 8 9
10 11 12 13
Input: E – the environment
Input: S – start location of the robot in the environment
Let O be a list of nodes (positions with distances) the robot can reach. Initially contains S. This is
also called the open-list.
Let C be a temporary list of nodes. Initially empty. This is also called the closed-list. Define a variable p and point it to the start node in O
for Each node q that the robot can reach from pa do
Set the distanceToS of q to be one more that that of p
Add q to O if and only if there is no item in O with the same co-ordinate as q.
Add p to closed-list C.
Select a node p from the open-list, O, that is NOT in the closed-list C. until no such position p can be found
awhen picking q, you should do that in the following order relative to p: up, right, down, left
A video of a worked example of the above algorithm is provided on canvas (assignment 1 page).
3.2.2 Implementation details
It is important to have a good design for our programs and use suitable data structures and classes. In Assignment 1, you will implement our design3. You will implement 3 classes:
• Node class – to represent a position (col, row, distanceToS) of the robot.
• NodeList class – provides a method for storing a list of node objects as used in pseudo-code above. • PathPlanner class – that executes the reachable positions algorithm and path planning algorithms. • The main file that uses these classes, and does any reading/writing to standard input/output.
You are given these classes in the starter code. You may add any of your own code, but you must not modify the definitions of the provided class methods and fields.
3.2.3 Node Class
The Node class represents a position of the robot. It is a tuple (col,row,distanceToS), which is the x-y location of the robot, and the distance that the algorithm took to reach that position from the robot’s starting position. It contains getters for this information and setter for distanceToS.
3This won’t be the case for Assignment 2, where you will have to make these decisions for yourself.
// Constructor/Desctructor
Node(int row, int col, int distanceToS);
// get row-coodinate of the node
int getRow();
// get column-coodinate of the node
int getCol();
//getter and setter for distance to source
int getDistanceToS();
void setDistanceToS(int distanceToS);
3.2.4 NodeList Class
The NodeList class provides a method for storing a list of Node objects. It stores an array of Node objects.
Since it’s an array we also need to track the number of position objects in the NodeList. You must implement the NodeList class using an array.
// NodeList: list of node objects
// You may assume a fixed size for M1, M2, M3
Node* nodes[NODE_LIST_ARRAY_MAX_SIZE];
// Number of nodes currently in the NodeList
int length;
The constant NODE_LIST_ARRAY_MAX_SIZE is the maximum number of objects that can be in a NodeList. This
constant is given in the Types.h header file. #define ENV_DIM 20
#define NODE_LIST_ARRAY_MAX_SIZE 4*(ENV_DIM * ENV_DIM)
The NodeList class has the following methods:
// Constructor/Desctructor
NodeList();
~NodeList();
// Copy Constructor
// Produces a DEEP COPY of the NodeList
NodeList(NodeList& other);
// Number of elements in the NodeList
int getLength();
// Get a pointer to the ith node in the node list
NodePtr get(int i);
// Add a COPY node element to the BACK of the nodelist
// This class now has control over the pointer
// And should delete the pointer if the position-distance
// is removed from the list
void addBack(NodePtr newNode);
// Checks if the list contains a node with the same co-ordinate
// as the given node.
bool containsNode(NodePtr node);
// Remove everything from the list
// Don’t forget to clean-up the memory!
void clear();
These methods let you add positions to the NodeList, and get a pointer to an existing position. Be aware, that the NodeList class has full control over all position objects that are stored in the array. Thus, if position objects are removed from the array you must remember to “delete” the objects.
3.2.5 PathPlanner Class
The PathPlanner class executes the two parts (reachable positions algorithm, path planning algorithm) of the
path planning algorithm by using the NodeList and Node classes. It has two main components:
1. getReachableNodes: Execute the reachable positions algorithm. Returns a DEEP COPY of the reachable NodeList in reachable positions algorithm.
2. getPath: [To be implemented for milestone 3]. Execute path Planning algorithm and Get a DEEP COPY of the path the robot should travel.
// Constructor/Destructor
// Initialise a with a given maze of size (rows,cols)
PathPlanner(Env env, int rows, int cols);
~PathPlanner();
// Set The initial position
void initialPosition(int row, int col);
// Method for Milestone 2
// Return a DEEP COPY of the NodeList of all node’s
// that the robot can reach
NodeList* getReachableNodes();
// Method for Milestone 3
// Get the path from the starting position to the given co-ordinate
// The path should be a DEEP COPY
NodeList* getPath(int toRow, int toCol);
This uses a custom data type Env, which is given in the Types.h. It is a 2D array of characters that represents a environment using the format in Section 2. It is a fixed size, because we assume the size of the environment is known.
// A 2D array to represent the environment or observations
// REMEMBER: in a environment, the location (x,y) is found by env[y][x]!
typedef char Env[ENV_DIM][ENV_DIM];
It is very important to understand the Env type. It is defined as a 2D array. If you recall from lectures/labs, a 2D array is indexed by rows then columns. So if you want to look-up a position (col,row) in the environment, you find this by env[row][col], that is, first you look-up the row value, then you look-up the col value.
The getReachableNodes method executes the reachable positions algorithm in Section 3.2.1 and returns a deep copy of the nodesExplored field. Be aware that this is a deep copy, so you need to return a new NodeList ob ject.
Importantly, the getReachableNodes method must not modify the environment it is given. The getReachableNodes method will generate a list of nodes the robot explored (“closedList” C in pseudo-code) and will store this list
of nodes in a private field.
The implementation of getPath method is part of milestone 3 and will be discussed in detail in Section 3.3.
3.2.6 main file The main file:
1. Reads in an environment from standard input.
2. Executes the forward search algorithm.
3. Gets the nodes explored in the forward search.
4. Gets the full navigation path (to be implemented in Milestone 3).
5. Outputs the environment (with the path) to standard output (to be implemented in Milestone 3).
The starter code gives you the outline of this program. It has two functions for you to implement that read in the environment and print out the solution.
// Read a environment from standard input.
void readEnvStdin(Env env);
// Print out a Environment to standard output with path.
// To be implemented for Milestone 3
void printPath(Env env, NodeList* solution);
Some hints for this section are:
• You can read one character from standard input by:
std::cin >> c;
• Remember that is ignores all white space including newlines! 3.3 Milestone 3: Finding the path
For Milestone 3, you will implement the getPath method of class PathPlanner and printEnvStdout method in main.cpp.
3.3.1 Implementing getPath method
This method finds a path from the robot’s starting position to the specified goal position using the NodeList generated in your Milestone 2. Then the path found should be returned as a deep copy. The path should contain an ordered sequence of Node objects including the starting position and the given goal position. You may assume that the goal co-ordinate can be reached from the starting position.
The Path Planning algorithm is not given to you as a pseudo code. However, the following hint is given to help you formulate a pseudo-code.
Hint: “Start from the goal node in the NodeList you computer for M2. Then search for the the four neighbours of the goal node in NodeList (you should do that in the following order relative to current node: up, right, down, left). If there is a neighbour that has distanceToS one less than the goal node. Then that should be the node in the path before the goal node. Repeat this backtracking process for each node you add to the path until you reach the start node.”
Think carefully the path that you return must be from start to finish, not finish to start.
Be aware that the returned path is a deep copy of the path, so you need to return a new NodeList object.
3.3.2 Printing the path
The next step is showing the path the robot should take in navigating from where it started until it reached the goal. You should implement this in printPath method in main.cpp. For example, using the environment from the Introduction section, the robot’s path is below:
==========
=S>>>>>>v=
========v=
=…v<<=v=
==.=v=^<<=
=..=>v=.==
=.===v=..=
=..==G==.=
===.======
==========
When showing the output of the path, it must show the direction in needs to be in order to get to the next position. To represent the robot’s direction, we use the 4 symbols shown below:
Symbol Meaning
> Move Right < Move Left
v Move Down.
When printing the environment, you might find it easier to first update the environment with navigation path, and then print out the whole environment.
3.4 Milestone 4: Dynamic Array Allocation
This is a challenging Milestone. Attempt this once you have completed the other milestones. For Milestones 1 - 3, we assume that the environment is always of a fixed size (20x20). This means, that for
the Env data type and the NodeList class we could define the size of the arrays before-hand. For Milestone 4, you must modify your implementation to accommodate two significant changes:
• Use a Environment of any rectangular size.
• Dynamically resize the nodes field of the Nodelist as more elements are required in the array, rather
than use a fixed size.
To do this, you will need to modify a number of aspects of your implementation to dynamically allocate memory for 1D and 2D arrays. You will need to consider the following modifications:
• Change the type of Env to a generic 2D array: typedef char** Env;
The milestone4.h file in the starter code has a sample method to help you dynamically allocate memory
for a 2D array.
• Change the type of the field nodes in the NodeList class to a generic 1D array of pointers:
Node** nodes;
• Create memory as necessary for the environment and NodeList.
• When reading in the environment, you will need to be able to spot newline characters. You can’t do this
if you follow the suggestion for Milestone 2. Instead you will need the get method of std
程序代写 CS代考 加微信: powcoder QQ: 1823890830 Email: powcoder@163.com