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COMP0037 Investigating Path Planning Algorithms
创建日期：2024-08-01 15:38:31
标签： COMP0037
Investigating Path Planning Algorithms

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COMP0037 Coursework 


“Path Planning in a Known World”

Investigating Path Planning Algorithms

Weighting: 40% of module total

Final Submission Format: each group submits both the source code and a report in PDF format. Both the code and the

report will be placed in a single zip file. The name of the file will be COMP0037_CW1_GROUP_n.zip, where n is the

name of your group.

Assignment Description

In this assignment, you will implement, investigate and optimize a number of discrete different planning algorithms which can

be used by a robot (the stdr simulation robot from lab exercise 2) in a warehouse-like environment. The robot will be given a

known occupancy grid map of the environment. A ROS node (the_boss) sends the robot a sequence of goal cells that the

robot needs to visit in turn. The robot has to plan a path from its current pose to get to the current goal. Both the structure of

the environment and the position of the robot are known perfectly all the time. Both the planner and the robot will collect

information on statistics such as travel distance and travel time. As explained below in the materials section, you will be

provided with reference code which implements some of the basic (and inefficient) path planning algorithms described in the

lectures, as well as a reference (and deliberately inefficient) controller to drive the robot about.

The assignment has two main parts:

1. Implement, investigate the properties of the path planning algorithms. This can be carried out independently of STDR.

2. Embed your path planning algorithms within a full ROS node and use these to drive the robot around. Explore

additional ways to improve the quality of both the path planning and the control of the robot.

The results of both parts of your investigation will be presented in a single report. This will be divided into two parts according to

the assignment above. The rubric gives the allocation of marks within each part separately. The overall mark for this piece of

coursework will be given by taking the weighted contributions of each part separately.

Note the percentages after each heading are the percentage of the overall coursework mark assigned to each section.

Part 1: Investigate Path Planning Algorithms (60%)

Planning Algorithm Investigation (45%):

The goal of this part of the coursework is for you to implement and evaluate a number of path planning algorithms described in

the first four weeks of the lectures. For reference, we provide implementations of the breadth first and depth first planners are

implemented. You should implement your algorithms in a similar way.

Instrument the path planning algorithms to store information on: the number of cells visited by the planner as it computes the

path, the total travel length of the planned path, and the total angle the robot has turned through when driving along that path.

Implement the Greedy Algorithm described in Week 02. The solutions should be sorted in order of Euclidean distance to the

goal. Cells which are closer to the goal should be searched first.

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关键词一 关键词二 关键词三 关键词四 关键词五 和法规和的发更好的风格和 ECON 615 FINC 612 CSC148 COMP 639 ACCT 203 ACCT 211 PSYC 101 MTH2009 COMP52315 PSYCO 432 statistics MATH4063 11 xxx 1 MA1MSP MAST30028 MATH3888 CS341 EEE30002 ES2F5 MCD4160 CC0933 ECON 1101 MCHM3001 CHEM3118 COMMGMT 2511 COMP41280 STAT 631 24T1 IRE379 SENG365 ECON433 FIT3139 MATH4602 LING5621M FINS5516 ECON3208 MN2177 L2 SM EEET1415 Finance DS4023 COMP3004 7CCSMRTS K1S5B6 Stat230 CSCI4211 CSI2132 ECON30130 MAS6100 ENVS222 COM2107 INFO1112 STAT 4004 FIT2100 comp2022 COMP4691 Physics 307 Econ 659 probability CSCI316 fir29 CSCI203 COMP3160 COMP6714 INFO1113 Physics 7B Physics Photonics S203031 STAT2005 COMP90015 CSCI 2110 CSCC46 Information CSC477 COMP4650 Statistical COMP 346 COMP1017 ELEC340 MATH1007 Programming function STAT 244 CS 134 Java cse13s Math 108A FW20 ECON3389 CSE 130 Science 331 COMP9020 engineering COSC 445 CSE 5523 GAME2012 visualization MATH 235 Math 370 CSC343 COGS 108 EE524 COMP10200 STAT 416 3FK4 MSCI 311 ECON6113 ACC40700 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