Lab 10a - Jetbot self-driving

Robotics II

Poznan University of Technology, Institute of Robotics and Machine Intelligence

Laboratory 7: NVIDIA Jetbot self-driving

Back to the course table of contents

The aim of this task is to create an autonomous control NVIDIA Jetbot robot.

  1. Check the instruction and example notebooks related to NVIDIA Jetbot.
  2. The whole project instruction is included in the repository README file. Go to and enjoy.

RULES AND REGULATIONS - “JetBot Grand Prix – Artificial Intelligence Robotics Challenge”

1. Objectives

The objectives of the challange are:

The course is conducted using the NVIDIA AI IoT JetBot platform

2. Teams

Students work in teams of 4-5 people

Each team: chooses a name (e.g., F1 style) is responsible for one JetBot (“race car”)

The team is fully responsible for: - the code - the AI model - the robot’s configuration

3. Structure of competition

We will have 7 labs for competition.

Lab 1

Introduction to the robot: - camera - motors - Jetson Nano access to the environment (Jupyter / SSH)

Lab 2

Understanding robot control and the basics of movement

Work with:

RACE 1 – Time Trial (manual)

POINTS CALCULATOR:

\(P = P_{max}​ ⋅ \frac{T_{team}}{​T_{best​​}}\)

where:

\(P_{max} = 25\)

\(T_{team}\)- the time of a given team

\(​T_{best​​}\)- best time in round

LAB 3,4 – Data Collection, Model Training and AI Control

Understanding AI input data and building the first AI model

Work with:

LAB 5 First AI Race

Work with:

RACE 2 – AI Challenge (scored)

POINTS CALCULATOR:

\(P = P_{max}​ ⋅ \frac{T_{team}}{​T_{best​​}}\)

where:

\(P_{max} = 25\)

\(T_{team}\)- the time of a given team

\(​T_{best​​}\)- best time in round

LAB 6 - Iteration and Improvements

Work with:

LAB 7 – Final: JetBot Grand Prix

Presentation of the final solution

FINAL RACE

POINTS CALCULATOR:

\(P = P_{max}​ ⋅ \frac{T_{team}}{​T_{best​​}}\)

where:

\(P_{max} = 25\)

\(T_{team}\)- the time of a given team

\(​T_{best​​}\)- best time in round

DETAILED REGULATIONS

JetBot Grand Prix – Rules and Participation Guidelines

1. General Rules

1.1. Every student must belong to a project team

1.2. Teams consist of 3-5 members

1.3. Each team works with one robot (JetBot)

1.4. The team is responsible for the entire solution (code, model, configuration)

1.5. All tasks must be completed independently by the team

1.6. Use of documentation and educational materials is allowed

1.7. Copying solutions without understanding them is prohibited

2. Team Organization

2.1. Each team must choose a name (used for identification)

2.2. Team composition is fixed for the entire semester

2.3. Any changes require instructor approval

2.4. Each member must be able to explain the project

2.5. Lack of participation may result in individual grading

3. Hardware and Environment

3.1. All teams must use the provided robots

3.2. Hardware configuration must remain consistent with course standards

3.3. Unauthorized hardware modifications are prohibited

3.4. Software modifications (code, AI models) are allowed

3.5. Each team is responsible for the technical condition of the robot

3.6. Any hardware issues must be reported immediately

4. Artificial Intelligence Requirements

4.1. Autonomous tasks must use camera input

4.2. Models must be trained on team-collected or provided data

4.3. The model must operate in real time

4.4. Teams must be able to explain how their model works

4.5. Use of standard architectures (e.g., CNNs) is allowed

5. Prohibited Practices

5.1. Hardcoding the track (e.g., predefined movement without camera input)

5.2. Manual control during autonomous runs

5.3. Use of unauthorized sensors

5.4. Remote control from external systems (e.g., phone, laptop during run)

5.5. Copying code from other teams

5.6. Using pre-trained models without understanding them

5.7. Modifying the competition environment (e.g., moving track elements)

5.8. Interfering with other teams’ work

6. Run Rules

6.1. The better result is counted

6.2. The run starts on instructor’s signal

6.3. The run ends when:

6.4. The robot must operate autonomously when required

7. Timing and Penalties

7.1. Time is measured from start to finish

7.2. Penalties are added for errors

Penalties:

8. Testing Conditions

8.1. All teams compete under the same conditions

8.2. The track is identical for all participants

8.3. Lighting conditions may change during competitions

8.4. The instructor may introduce minor track modifications

8.5. Teams do not have prior access to the final track

9. Scoring

9.1. Points are awarded based on competition results

9.2. Solution quality is also evaluated

Evaluation components:

9.3. Competition results – 40%

9.4. Documentation and Solution quality (mode, code on github required) – 30%

9.5. Presentation – 20%

9.6. Reproducibility – 10%

10. Documentation

10.1. Each team must submit a report

10.2. The report must include:

10.3. Reports must be submitted on time

10.4. Missing report results in grade reduction

11. Knowledge Verification

11.1. Teams may be asked to present their solution

11.2. The instructor may ask technical questions

11.3. Each team member should understand the solution

11.4. Lack of understanding may result in individual grade reduction

12. Reproducibility

12.1. The solution must be runnable by the instructor

12.2. Code must be organized and documented

12.3. A clear run instruction must be provided

12.4. Failure to reproduce results leads to point loss

13. Safety

13.1. Actions that may damage hardware are prohibited

13.2. The robot must be used as intended

13.3. Work must stop in case of malfunction

13.4. Teams are responsible for improper usage

14. Final Provisions

14.1. Final interpretation of the rules belongs to the instructor

14.2. Minor changes to the rules may be introduced during the course

14.3. The goal is learning, not only competition

14.4. Participation implies acceptance of these rules