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Shanel’s Status Report 3/22

Shanel’s Status Report 3/22

The beginning of the week was spent deciding how to rework our project to something feasible that we would be able to deliver at the end of the semester. The group and I spent an initial meeting discussing what changes we are going to make: what to cut out, what to add, and what concerns we had. I then took this bullet point list and wrote out the full statement of work. Since we decided to add more to the…

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Team Status Report 3/22

Team Status Report 3/22

This week, the team focused on refactoring the project to meet the project goals with the coronovirus quarantines in place, and each member working remotely. Aditi is the only once in Pittsburgh. We had a few zoom meetings to discuss the future trajectory of the project. We came up with the following concerns over out original project – – All parts located in Pittsburgh while most of the team is not. – Not able to test on original test cases….

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Aditi’s Status Report 3/22

Aditi’s Status Report 3/22

This week, I worked with the team to refactor the project in order to meet or our goals. We are in different locations, and I am the only one in Pittsburgh. Therefore, I would be the only one having access to the robot hardware. Keeping this in mind, we decided to make the following changes: – We want to limit robot assembly and in person testing. To do this, we removed the CV portion of the project. This includes door…

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SHANEL’S STATUS REPORT 3/7

SHANEL’S STATUS REPORT 3/7

For the OCR algorithm, I got Tesseract set up and working on input image files. I also wrote a python script to start taking input from the Raspberry Pi Camera and process optical character recognition, but haven’t been able to test it. The process to download Tesseract and OpenCV onto the Raspberry Pi took longer than expected, but we finally got it. I also came up with a general navigation planning flow using a Global and Local SLAM subsystem modeled…

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Team Status Report 2/29

Team Status Report 2/29

Currently the single largest risk remains in the processing power requirement. We looked into Google Cartographer, which recommends 16GB RAM, but other projects have run Cartographer on embedded systems by using only 2D data like we are. We also plan to use ROS-provided SLAM libraries to do the fine-grain computations. The only significant change made to our design was the inclusion of two more ultrasound sensors, facing forward and angled up/down. These are intended to address the concern of low…

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Introduction and Project Summary

Introduction and Project Summary

Google Maps lacks accurate and comprehensive indoor positioning information. Businesses and establishments that upload their own floor plans are able to show specific details on indoor locations. However, most buildings do not have this information available online, making it difficult for visitors to navigate indoors.   The Robotic Indoor Plotting project will autonomously generate indoor floor plans, while labeling room descriptors and dimensions. When placed indoors, the robot will explore the space, creating a 2D map using built-in obstacle detection…

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