Coming into the final stretch of our project, we dedicated this week to achieving better obstacle detection and integrating our multiclass classification algorithm. We also introduced a Neopixel LED ring light on top of the robot with various color patterns for different modes and scents that ScentBot can identify.
We added two additional ultrasonic sensors, one on each side of the robot, and implemented new obstacle avoidance logic for when the robot detects objects on the side. We have seen a tremendous improvement in the robot not running into the scented object when exploring and scanning. Now, the robot is able to back up, and continue its scan and/or random exploration. ScentBot also now uses various sensor values to determine if a scent has been detected or confirmed which has improved the detection and confirmation performance.
We also explored utilizing propane and isobutane sprays for our third scent, as we hypothesized that substances with hydrocarbons would trigger the sensors. Upon testing with our sensor arrays, we discovered that the concentrations of TVOCs, Ethanol and other hydrocarbons was not high enough to trigger our sensors. We have decided to have our embedded Support Vector Classification (SVC) only work on the following: alcohol, paint thinner and ambient scent. We also integrated the SVC model on the Arduino Mega to only classify a scent after a global threshold has been reached. This was a decision made with considering the tradeoff between false positive rates and sensor sensitivity. This ensures that ScentBot is confident enough over a sampling period that there is a scented object.
We have come up with a test plan and run 20 initial trials with paint thinner and alcohol, introducing either 0, 1 or 2 unscented objects in trials to observe ScentBot’s performance. On average, we found that the classification is always correct, while convergence time is around 183s with an average first scan detection at 39cm. We expect this to be more true to ScentBot’s performance as we host more trial runs, which is our goal before our final demo. We are also working on fine-tuning the front ultrasonic sensor to prevent ScentBot from running into walls.
Linked is a successful test run, similar to the ones we plan to showcase at our final demonstration.