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Final project on solving the spatially-dependant reliable shortest path problem (SD-RSPP) algorithm for AER1516 - Motion Planning for Robotics graduate-level course at University of Toronto.

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Solving the Spatially-Dependant Reliable Shortest Path Problem (SD-RSPP)

This repository contains project files to solve the SD-RSPP with two methods: a multi-criteria hierarchical A* (SDRSP-HA*) algorithm and a mixed-integer programming (MIP) model using Gurobipy.

  • Institution: University of Toronto
  • Course: AER1516 - Motion Planning for Robotics with Dr. Jonathan Kelly
  • Dates: Winter 2022
  • Project Status: Complete

Setup

  1. Need to update versions of packages used and

Packages Used

  • python - version 3.7.7
  • numpy - version 1.19.1
  • networkx - version 4.12.0
  • matplotlib - version 3.3.1
  • gurobi - version 9.0.3
  • scipy - version 2.18.200

References

  1. Gurobi Optimizer: Gurobi is an industrial mixed-integer programming solver that works with many programming languages including Python. In order to use Gurobi, you need an academic license, which can be found here: https://www.gurobi.com/academia/academic-program-and-licenses/. In addition, you must download the gurobi software from this site or if you use the Anaconda Distribution for Python, you can run the following code:
pip3 install gurobi

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Final project on solving the spatially-dependant reliable shortest path problem (SD-RSPP) algorithm for AER1516 - Motion Planning for Robotics graduate-level course at University of Toronto.

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