20TTP409 - Path Planning And Path Following Algorithms Report Writing - IT Assignment Help

Assignment Task

Path planning and path following algorithms 

Introduction  

This coursework requires to design and implement an integrated path-planning and path-following algorithm to guide the autonomous ground vehicle. It is required your  algorithm can plan a path and guide the vehicle to follow the path from start to goal in a square area. The vehicle needs to avoid five obstacles on the path. The  scenario is given in Figure 1. 

The configuration space is a square defined by the corners at (0,0) and (200, 200),  denoted as the grey area. Five obstacles with different shapes appear at random  places on the path. As examples, the position of obstacles in three other different  running are illustrated in Figure 2. 

The coordinates of obstacles can be obtained from the provided codes. The vehicle  model is given as  

The circle: 

xc=randi([xcmin xcmax]); 

yc=randi([ycmin ycmax]); 

centers_circle=[xc yc]; % coordinate of the circle centre 

radius=15; % radius 

The square: 

xs=randi([xsmin xsmax]);  

ys=randi([ysmin ysmax]);  

ceters_rectangle=[xs ys]; % coordinate of the right-down vertex of the square width=35; % side length 

 The pentagon: 

x_pentagon=[xp1 xp2 xp3 xp4 xp5 xp1]; % x_coordinate of the pentagon vertices y_pentagon=[yp1 yp2 yp3 yp4 yp5 yp1]; % y_coordinate of the pentagon vertices 

The hexagon: 

x_hexagon=[xh1 xh2 xh3 xh4 xh5 xh6 xh1]; % x_coordinate of the hexagon vertices y_hexagon=[yh1 yh2 yh3 yh4 yh5 yh6 yh1]; % y_coordinate of the hexagon vertices 

The triangle: 

xt=[xt1 xt2 xt3 xt1]; % x_coordinate of the hexagon vertices 

yt=[yt1 yt2 yt3 yt1]; % y_coordinate of the hexagon vertices 

Requirement

The task of this coursework is to design an integrated path-planning and path following algorithm. It requires that your algorithm can plan a feasible path and drive  the vehicle following the planned path. Meanwhile, it requires your vehicle can avoid  the five obstacles appear on the path and cannot touch the boundaries of the grey  area. Different functioning parts in your algorithm should work as an integrity to  satisfy all the requirements. The vehicle initial x-axis position is a random value  between [5 m, 15 m], while the vehicle y-axis position is a random value between [10 m, 20 m]. The initial heading angle is a random value between [0 deg, 90 deg]. To  simplify the problem, it is assumed that vehicle maintains a constant speed at 8 m/s. 

There is no constraint on what algorithm you can use. You can use Voronoi diagram,  Cell decomposition, Potential field, Probabilistic road mapping or Rapidly exploring  random trees algorithm to fulfil the path planning. Similarly, you can use carrot-

chasing, nonlinear guidance law, pure pursuit with LOS, vector field or LQR  algorithm to fulfil the path following. Also, you can design innovative algorithms to  realise objectives. The algorithm should be tested and demonstrated using  simulation programme. A programme template in Matlab m-file will be provided to  facilitate the simulation, but this is not compulsory to use this template. You can use  Simulink-based environment if you like. 

A written report no more than six pages is required from this coursework (except for  the cover page, table of contents and appendixes). The report should 1) present in a  logical and structured way; 2) describe the design of algorithm (including the  derivation process and formulation of problems) clearly in a mathematically sound  way, so that other people can use it as an instruction to recreate your algorithm; 3)  demonstrate the performance of your algorithm with good visibility in comparison to  the requirements using simulation data (i.e. present both your planned and actual trajectory in a logical way to show the performance); 4) discuss the advantages and  disadvantages of your algorithm and how you tuned those critical parameters in your  algorithm for this path-following task. Note that appendixes, although can be  regarded as supporting materials, will not be marked. 

You need to run your code at least three times to validate the robustness of your algorithm (i.e. your algorithm is effective in at least three different driving scenarios).  As the simulation results, the trajectories of your vehicle for at least three different  driving scenarios need to be clearly plotted in your report with proper annotations.

This 20TTP409 - IT Assignment has been solved by our IT Experts at My Uni Paper. Our Assignment Writing Experts are efficient to provide a fresh solution to this question. We are serving more than 10000+Students in Australia, UK & US by helping them to score HD in their academics. Our Experts are well trained to follow all marking rubrics & referencing style.

Be it a used or new solution, the quality of the work submitted by our assignment Experts remains unhampered. You may continue to expect the same or even better quality with the used and new assignment solution files respectively. There’s one thing to be noticed that you could choose one between the two and acquire an HD either way. You could choose a new assignment solution file to get yourself an exclusive, plagiarism (with free Turnitin file), expert quality assignment or order an old solution file that was considered worthy of the highest distinction.