Inspiration
The project draws inspiration from various robotics teams that have undertaken similar endeavors in the past.
What it does
CleanMars is designed to discover, collect, and classify trash. It employs algorithms to navigate to designated areas, identify when trash needs to be collected, and utilize object detection to classify the type of trash.
How we built it
The project was built using a combination of hardware and software. Algorithms were developed to guide the robot to its target locations and determine when trash should be collected. Object detection techniques were employed to classify the collected trash. Additionally, the team gained hands-on experience with hardware components during the development process.
Challenges we ran into
Several challenges were encountered during the development process. One significant challenge was the robot's tendency to collide with walls, which required troubleshooting and refinement of the navigation algorithms. Additionally, many team members were new to working with hardware, which presented a learning curve at the outset of the project.
Accomplishments that we're proud of
Despite the challenges faced, the team successfully achieved its objectives for CleanMars. The project was able to perform the intended tasks, demonstrating the team's perseverance and problem-solving skills.
What we learned
The project provided valuable learning experiences for the team members, particularly in the realms of hardware and AI models. Through hands-on experimentation and collaboration, team members gained insights into the complexities of integrating hardware and software components in a robotics project.
What's next for CleanMars
Looking ahead, the team plans to expand the project by developing a Mars Rover capable of collecting trash on the Martian surface. This ambitious endeavor will involve further refinement of the robot's capabilities and adaptation to the unique challenges posed by the Martian environment.
Built With
- 3dprinting
- arduino
- micro-controller
- object-detection
- orangepi
- python
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