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This project implements search-based algorithms that yield a sub-optimal path if one exists. Path findingalgorithms, such as Weighted A*, have been used to find a sub-optimal path for the robot from the user-defined start to endpoint. The project also generates animation to visualize the exploration of each of the mentioned search-based methods.It first checks that the user inputs do not lie in the obstacle space. Note that the obstacle space is pre-definedand static.

In Weighted A*, the heuristic cost is multiplied by an inflation factor, epsilon. If epsilon is 1, Weighted A* reduces to A*.

Unlike A* and Weighted A*, Depth-first search(DFS) has no concept of cost-to-come and cost-to-goal. Moreover, it isbased on a Last-In-First-Out (LIFO) queue. A LIFO queue is simply known as a stack.

Figure 1 - Comparison of A*, Weighted A*, and DFS

• Implement tree based algorithms such as PRM and RRT

• Python3
• Python3 Libraries: Numpy, OpenCV-Python, Math, Queue, Time, Sys, Ast

• Install Python3, Python3-tk, and the necessary libraries: (if not already installed)

These commands are based for Linux systems such as Ubuntusudo apt install python3sudo apt install python3-pippip3 install numpy opencv-python queue

• Check if your system successfully installed all the dependencies
• Open terminal using Ctrl+Alt+T and enter python3
• The terminal should now present a new area represented by >>> to enter python commands
• Now use the following commands to check libraries: (Exit python window using Ctrl+Z if an error pops up whilerunning the below commands)

import numpyimport cv2import queue

• Using the terminal, clone this repository and go into the project directory, and run the main program:

git clone https://github.com/urastogi885/sub-optimal-path-findercd sub-optimal-path-finder

• If you have a compressed version of the project, extract it, go into project directory, open the terminal, and runthe robot explorer.

python3 robot_explorer.py <start_x,start_y> <goal_x,goal_y> <robot_radius> <clearance> <method> <animation>

• An example for usingWeighted A* for a rigid robot:

python3 robot_explorer.py 50,30 150,150 2 1 0 1

• The output in theOverview section has been generated using the above arguments.