About the internship

The demand for Path Planning Algorithm Engineers has spiked very high in the recent years, because of the extensive development & technology adoption towards automation, robotics and autonomous vehicles. In this course/internship you will learn the solid fundamentals of programming from scratch to advance concept which are necessary to work on projects using the path planning algorithms such as RRT & RRT*. 

 

Internship program will involve you to build real-world applications using the numerical modeling software called Scilab & Scilab-Xcos. It will be 100% practical & hands-on oriented content, taught online to meet the industry requirements. Learning at an internship will give you the opportunity to extend yourself to build any system and take up the projects of your interest.

 

Every participant will require a laptop and the Scilab software (given by Decibels after registration) to take part in the internship. Every student will have to build the models along with the trainer and involve in everyday reporting. 



Learning outcomes:

  • Clarity on Path Planning algorithm usage in real life scenarios such as Warehouse robot & Car Parking Path Planning
  • Understanding programming of loops (for, while loops) & conditional statements (if, If-else).
  • Programming Sampling based path planning algorithm RRT* to find the shortest path to avoid obstacles
  • Analysis of number on nodes on the time and convergence on RRT* path planning algorithm to a solution


Weekly learning goals:

Week 1, Interns will learn Scilab & Scilab-Xcos software tools by solving the simpler problems, taking up assignments, and building the models. 

Week 2, Interns will gain an understanding of Path planning algorithm and their use case in the real-life applications. You will also gain program commands required in order to write a path planning algorithm by completing assignments.

Week 3, Interns will be introduced to a sampling-based path planning algorithm and will be guided to the process of understanding, programming and visualization of path planning algorithm for path planning for a warehouse robot.

Week 4, Interns will be given a problem statement on building a path planning algorithm for car parking. Interns will have think, understand the application and build the algorithm for the application individually to prepare a document of the results obtained.  Assigned Projects are very important to learn the application of tools and also an opportunity to understand, how to build and analyze a system.


Projects are given the highest preference during the learning, because industries always look for engineers with the project experience. By involving more projects, you can gain the experience that industry demands, so forth you get hired. 

Internship date & eligibility

Internship name

4-week Path Planning Algorithm Engineer

Internship start date

Monday, 14 February 2022

Internship end date

Friday, 11 March 2022

Last date of registration

Saturday, 12 February 2022

Mode of delivery

Online 

Software used

Scilab & Xcos  

 

Applicable for

Mechanical/Electronics/Automobile/Mechatronics/Robotics

Certification by & Host details

Decibels Lab Pvt Ltd 

(Recognized as Start-up by Department for Promotion of Industry and Internal Trade Ministry of Commerce & Industry Government of India) (Certificate Number: DIPP45372)

Fee

1999 INR (For students) / 2999 INR (Graduates/Working professionals)
Course access duration 60 days for students / 90 days for Graduates/Working professionals

Intern intake 

30 interns only

Selection criteria

First, come registration basis

Session timings

Self-paced learning with recorded sessions (1 hour of learning & 2 hours of practice/day as your time planning)

Doubt clarification

It’s 100% practical & self-paced, provided with step by step guide to achieving the model. For critical issues or doubts you face, you can fill the doubt clarification form. Our team will answer via email or via live zoom meetings.

Internship Activity Plan

    1. Softwares download

    2. How to use Discussions option

    3. Course access duration

    4. Piracy & infringement warning

    1. Day 1: Live session

    2. Day 1 Introduction

    3. Day 2: Scilab introduction & Scilab Programing Part 1

    4. Day 2: Scilab introduction & Scilab Programing Part 2

    5. Day 2: Scilab introduction & Scilab Programing Part 3

    6. Day 3: Scilab Xcos introduction & Practice Part 1

    7. Day 3: Scilab Xcos introduction & Practice Part 2

    8. Day 3: Scilab Xcos introduction & Practice Part 3

    9. Day 3: Scilab Xcos introduction & Practice Part 4

    10. Day 4: Practice Scilab Xcos with real time problems Part 1

    11. Day 4: Practice Scilab Xcos with real time problems Part 2

    12. Day 4: Practice Scilab Xcos with real time problems Part 3

    13. Day 4: Practice Scilab Xcos with real time problems Part 4

    14. Day 1 Introduction to Internship by Suraj (07 Sep 2020)

    15. Day 5: Creating data visualization & analysis graphs in Scilab Part 1

    16. Day 5: Creating data visualization & analysis graphs in Scilab Part 2

    17. Day 5: Creating data visualization & analysis graphs in Scilab Part 3

    18. Day 5: Creating data visualization & analysis graphs in Scilab Part 4

    19. Day 5: Creating data visualization & analysis graphs in Scilab Part 5

    20. Day 5: Creating data visualization & analysis graphs in Scilab Part 6

    21. Day 5: Creating data visualization & analysis graphs in Scilab part 7 (Help video)

    1. Query Reporting: Path Planning Algorithm Engineer

    1. Aerodynamic forces modeling (3 cases)

    2. NEDC drive cycle

    3. Motor Data

    4. Sales

    1. Day 1 Session 1 (Introduction to Loops)

    2. Day 1 Session 2 (Nested loops)

    3. Day 2 Session 1 (Conditional Statements)

    4. Day 2 Session 2 (Functions)

    5. Day 2 Assignment on Loops and Conditional statements

    6. Assignment Submission (Loops and conditional statements)

    7. Comparison document for assignment 1 on loops and conditional statements

    8. Comparison document for assignment 2 on loops and conditional statements

    9. Day 3 Session 1 (Introduction to SLAM)

    10. Day 3 Session 2 (Overview of Path Planning)

    11. Quiz on Path Planning

    12. Day 4 Session 1 (Applications of Path planning algorithm)

    13. Day 4 Session 2 (Configuration Space)

    14. Day 4 Session 3 (Obstacle representation in algorithm)

    15. Day 4 Session 4 (Graphs and Cost)

    16. Day 4 Session 5 (Graph Search)

    17. Day 5 Session 1 (Path Planners)

    18. Day 5 Session 2 (Sampling based path planning)

    19. Quiz on Sampling based method of path planning

    1. Day 1 (Rapidly Exploring Random Tree*)

    2. Day 2 Session 1 Warehouse Robot path Planning (Configuraton Space)

    3. Day 2 Session 2 Warehouse Robot path Planning (Distance Function)

    4. Day 2 Session 3 Warehouse Robot path Planning (Steer Function)

    5. Day 3 Session 1 Warehouse Robot path Planning (No Collision Function)

    6. Day 3 Session 2 Warehouse Robot path Planning (RRT Algorithm)

    7. Day 4 Session 1 Warehouse Robot path Planning (RRT Algorithm)

    8. Day 4 Session 2 Warehouse Robot path Planning (RRT Algorithm Results Discussion)

    9. Day 5 Session 1 Warehouse Robot path Planning (RRT* Algorithm)

    10. Day 5 Session 2 Warehouse Robot path Planning (Results Discussion)

About this course

  • ₹1,999.00
  • 75 lessons
  • 16 hours of video content

Feedback from participants



FAQ

  • Why I should take up this internship

    MBD is the highest paid job in the core sectors. Application of MBD has found it's application in every sector. This internship will help you gain skill & experience to build your profile & to start your career. That's the motive for 1000 of students to apply for this internship.

  • Should I have any prerequisite knowledge to learn this course?

    No, you don't need to have past exposure. The learning will from fundamentals.

  • Should I need a laptop? & Practice projects individually?

    Yes, you will need a laptop to practice & also to perform the projects individually.

  • How the teaching will happen?

    From the start date of the internship, you will receive 1 hour of practice content every day (Recorded videos). You will have to complete the learning every day and take up the assigned activities by end of every day.

  • What should I do, if I get a doubt?

    We will fix a meeting with engineers, you can clarify your doubts via zoom meetings. You need to report the doubts/issues over the form provided to you.

  • How many projects I will work on?

    You will work on 2 to 3 projects, which are guided by a mentor. You can take up as many projects individually.