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Aditti’s Status Report for 2/18

This week I focused on finalizing the robot CAD. I worked with Caroline to develop an effective layout for our parts on the robot and did the SolidWorks for the base plate. I also worked on researching controller strategies like pure pursuit and PID control for robot motion and finalized some algorithms – down-sampling and wavefront segmentation for vision, A* with visibility graphs for global path planning, and Runge-Kutta and PID control for motion. Some of the courses that cover these topics include: 18-370 (Fundamentals of Controls), 16-311 (Intro to Robotics), 16-385 (Computer Vision), and 18-794 (Pattern Recognition Theory).

I also started looking into alternatives for multi-threading on the Arduino as we discovered that we will need to have the robot sensing and moving at the same time to make good use of time. So far, I have found some approaches that make use of millis() based timing instead of delay() along with OOP to make a state machine on the Arduino. Additionally, I worked on preparing the slides for the design review and preparing for presenting next week. We plan on laser-cutting the robot chassis tomorrow (Sunday 02/19) and assembling the robot as and when the parts come in. Next week I plan on starting to test out the motors and calibrate them so that the robot can move along a fixed path. This will involve implementing the PID controller and odometry as well. Since we will be testing out the alternative approach of random motion before path planning, I’ve decided to prioritize odometry over path planning for the moment. 

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Team Status Report for 2/18

This week we worked on getting started on several aspects of our robot, including the CAD design and the Wavefront Segmentation algorithm for our path planning. We also ordered all the parts for our robot and received them, focusing on how different parts will integrate together. Additionally, we researched how to connect the Arduino and Wifi module to Azure, which is now the decided cloud platform for our ScentBot. Towards the end of the week, we collected this information onto our Design Review slides. 

We have attached a photo of our completed CAD design.

 

With the parts we have ordered, we anticipate a few challenges, which we also discussed with our advisors. These would be good motor control and getting the robot to follow a straight path since we are assembling the robot using custom-built parts. We are also considering an alternate path planning approach because of the high dependence on sensor sensitivity in our project. 

If the sensors are sensitive enough to detect an object from a distance farther than the 0.5m radial distance, we will change our test setup to have a single-scented object. This will be placed in a scent diffuser/spray to create a radial distribution of scent for our robot to follow. The robot will “randomly” explore the map until it detects a scent, and will follow in the direction of increasing probability. The robot will receive a travel distance and angle to follow and will reorient itself to a different angular orientation after this set distance. An image of our alternate testing approach is shown.

The Wavefront Segmentation algorithm runs on a letter size sheet of paper within 0.22s on average, and can detect objects present on a white background. It thresholds the images for faster computation, and calculates and prints the location of the centroids of the objects. One challenge we immediately faced was making sure shadows do not overlap within the image capture from the overhead camera.  

 

The principles that we utilized to solve the problem of determining our robot design to fit our use-case requirements involved research into differential-drive robots, PID control, wavefront segmentation, Runge-Kutta localization, A* graph search, visibility graph, state machines on the Arduino, fluid dynamics & distributions, and chemical compositions and gas sensor types.

 

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Aditti’s Status Report for 2/11

This past week I focused on researching different sensor modules and robot chassis for our use-case scents and shortlisted parts for ordering. I also worked on the CV pipeline for finding centroids of various objects on a map by thresholding and segmenting. The model takes in a raw camera image, maps it to a 4×4 grid, and finds the centroid coordinates of each object on the map. The code still needs to be tested with the images from the actual camera that we will end up using. Since we are behind on ordering parts, I think robot assembly + CAD will have to be completed within the next week, which is why I decided to work on the segmentation section this week. By next week I aim to finalize the robot CAD and assemble the robot and also start thinking about path planning logic.