Author: sdupont

I spent the past couple of weeks primarily on the design report and on finding solutions to a few of the outstanding gaps in our design. First, I decided that we should use the on-board Raspberry Pi WiFi to allow our robot to communicate with the the users (i.e. rescue team) of our system. Second, I was searching for some way to convert the CVBS analog video signal that comes out of the thermal camera model that we’ve picked out for our design into a digital form that can be used by our Raspberry Pi for image processing. I have found a component that should accomplish just this.

I am slightly behind schedule for the thermal image processing portion of the project. Next week, I need to finish testing the first few approaches to thermal image processing that we are trying using thermal imaging data available on line, and determine if other techniques should be used to solve this problem (such as a HOG type algorithm) as discussed in the design review report.

This week I delivered our group’s design presentation and continued working on our algorithms for detecting people given infra-red imaging data. Overall, on this portion of the project I am on track as next week I plan to test the accuracy of the algorithms that we have so far using IR imaging datasets online.

This week I also began thinking about how our system will represent, store and keep track of what the robot’s surroundings are (some of the more detailed aspects of the path planning portion of our design). I think in this portion of the project, we are somewhat behind as it was pointed out to us in the design review that we have not considered some of the important details in the path planning portion of the project. To help move things along here, it seems likely that I will take up part of this portion of the project to work on in addition to IR data processing. Next week I will work on a detailed design/plan of how our system will take in information from the Lidar scanner about its environment, store the information it has about its environment, and use that information to navigate (as well as the exact policy/way in which it will navigate), and what functionality we may want to include in this portion in addition to just how the robot will explore a building’s floor/rooms.

This week I continued learning about and working on algorithms and techniques for detecting people using IR imaging data, as well as looked into which specific hardware components (cameras and controllers) would be best suited for our project. Significant time this week has also gone into the design review presentation and slides.

Because we have made a pivot in the project (based on the fact that our original idea of using a drone to search an area for people would not have been able to cover a wide enough area to make for an effective product) we have pivoted to a different project idea, but one that will still be making use of detecting people using IR imaging, so this component of the project will still be useful and is not one that we are behind schedule in. In the next week I hope to have finally placed an order for an IR camera based on what I have found out about them this week, and test if simpler algorithms (such as edge detecting, or thresholding) will be sufficient to detect people (and not detect not-people) for our use case, or if more advanced methods (CNNs, for instance) will be needed.

The main thing I worked on this week was learning about and implementing algorithms to take thermal imaging data and tell where sources of heat in a given image are. For the most part I am on schedule, because I should be able to work on putting a thermal image processing algorithm on a Raspberry Pi next week as outlined in our planned schedule for the project, however there will likely need to be quite a bit more adjustments made to our thermal image processing algorithm (in terms of kind of data being received, and possible optimizations). I think this can be accomplished in the coming week and week after.