https://github.com/rishikesh-jadhav/enpm661-planning-for-autonomous-robots

This repository showcases my work in Planning for Autonomous Robots, focusing on planning techniques applied to industrial robots such as KUKA. The work involves leveraging Moveit in Gazebo for proficient execution of pick and place operations. Throughout the course, I also learned various 2D search algorithms, ranging from A* to RRT and its types.
https://github.com/rishikesh-jadhav/enpm661-planning-for-autonomous-robots

gazebo manipulator-robotics motion-planning moveit path-planning ros-noetic rviz

Last synced: about 1 month ago
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This repository showcases my work in Planning for Autonomous Robots, focusing on planning techniques applied to industrial robots such as KUKA. The work involves leveraging Moveit in Gazebo for proficient execution of pick and place operations. Throughout the course, I also learned various 2D search algorithms, ranging from A* to RRT and its types.

• Host: GitHub
• URL: https://github.com/rishikesh-jadhav/enpm661-planning-for-autonomous-robots
• Owner: Rishikesh-Jadhav
• Created: 2024-01-06T21:23:43.000Z (12 months ago)
• Default Branch: main
• Last Pushed: 2024-01-08T01:05:08.000Z (12 months ago)
• Last Synced: 2024-01-08T22:37:30.244Z (12 months ago)
• Topics: gazebo, manipulator-robotics, motion-planning, moveit, path-planning, ros-noetic, rviz
• Language: Python
• Homepage:
• Size: 1.62 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# ENPM661-Planning-for-Autonomous-Robots

This repository serves as a comprehensive record of my academic journey in ENPM661 during the Spring of 2023. It encompasses solutions and code submissions for all projects, providing dedicated folders for each project, along with accompanying documentation and resources.

## 📚 Course Overview

The Planning for Autonomous Robots course explores planning techniques essential for realizing autonomous robots. Covering task planning, motion planning, and trajectory planning, the curriculum emphasizes traditional motion planning techniques with a focus on integrating physics into the planning process. Mobile robots are used as examples throughout the course, and the techniques introduced are equally applicable to robot manipulators.

1. **Planning Concepts**

2. **Geometric Modeling and Transformations**

3. **Deterministic, Feasible, and Optimal Planning in Discrete State Spaces**

4. **Deterministic, Feasible, and Optimal Planning in Continuous State Spaces**

5. **Planning Under State Transition Uncertainty**

6. **Motion Planning Under Differential Constraints**

7. **Advanced Topics in Motion Planning**

## 📄 Project List

- Click [here](https://github.com/Rishikesh-Jadhav/Enhanced-Path-Planning-through-Comparative-Analysis-of-RRT-and-Its-Variants-on-TurtleBot-in-Gazebo) to access the ENPM661 Final Project.

### [Project 1](https://github.com/Rishikesh-Jadhav/ENPM661-Planning-for-Autonomous-Robots/tree/main/Project1): Generating Nodes for 15-Puzzle Problem

- **Objective**: Implementing node generation for the 15-puzzle problem.

### [Project 2](https://github.com/Rishikesh-Jadhav/ENPM661-Planning-for-Autonomous-Robots/tree/main/Project2): Point Robot Planning using BFS/Dijkstra Algorithm

- **Objective**: Implementing planning for a point robot using BFS/Dijkstra algorithm.

### [Project 3 - Phase A](https://github.com/Rishikesh-Jadhav/ENPM661-Planning-for-Autonomous-Robots/tree/main/Project3-PhaseA): Path Planning for Turtlebot using Dijkstra*

- **Objective**: Implementing path planning for a Turtlebot using Dijkstra algorithm.

- **Phase 1**: Implemented path planning using Dijkstra 

### [Project 3 - Phase B](https://github.com/Rishikesh-Jadhav/ENPM661-Planning-for-Autonomous-Robots/tree/main/Project3-PhaseB): Path Planning for Turtlebot using  A*

- **Objective**: Implementing path planning for a Turtlebot using A* algorithm.

- **Phase 2**: Implemented path planning using A* & Simulation with non-holonomic constraints

  

### [Project 4](https://github.com/Rishikesh-Jadhav/ENPM661-Planning-for-Autonomous-Robots/tree/main/Project4): Path Planning for Robot Manipulators using OMPL

- **Objective**: Implementing path planning for KUKA robot manipulator using OMPL.

## 📚 References

- **Textbook:** [Planning Algorithms](http://planning.cs.uiuc.edu/) by Steven LaValle, Cambridge University Press, 2006.

- **Mobile Robotics: Mathematics, Models, and Methods** by Alonzo Kelly, Cambridge University Press, 2013.

- **Principles of Robot Motion: Theory, Algorithms, and Implementations** by Howie Choset et al., MIT Press, 2005.

- **Probabilistic Robotics** by Sebastian Thrun et al., MIT Press, 2006.

- **Introduction to Autonomous Mobile Robots** by Roland Siegwart et al., MIT Press, 2011.

- **Mastering ROS for Robotics Programming - Second Edition** by Lentin Joseph and Jonathan Cacace.