26 Aug

CREATE: Input estimation experiments of vehicles' demos.

Zida Wu

17 Aug

PID control for blimp motion

Shahrul Kamil bin Hassan (Kamil)

Previously, a P controller was used for simplicity as it removes the requirement of keeping track of time at each time step. However, with the unstable motion of the blimp, a PID controller is needed to further stabilize the system. This is the result: The parameters were tuned based on the trac...

16 Aug

RoCo Webapp - Loading Components with POST Method

Jaehoon Song

When we use POST method to create data to send it to the server, we do not need to list the models using known_models.py. Previously, we needed to put the name of the component in known_models python script like this: Then, we need to run the thumbnails python script to create the thumbnails...

15 Aug

Relative Position Detection Algorithm for High-Level Strategies

Shahrul Kamil bin Hassan (Kamil)

In the past 2 weeks, I tried to develop and algorithm that can be used if we have a blimp that have a camera facing down. With the camera, we would be able to detect the field of interest and control the robots within the field. In this case, the current algorithm can be used to control any vehicle...

15 Aug

Robustness of a Frequency-Diverse Network When One Frequency is Unusable

Bhavik Joshi

One thing that I wanted to do this week was to validate the effect of including frequency diversity in the network that we made for our robots. So, I programmed one ESP32 feather board with a 433 MHz packet radio on its stack to send out a lot of garbage values over the 433 MHz band extremely quickl...

14 Aug

Combining mesh networking, vision processing, and origami cars

Jillian Naldrien Pantig

During SURP 2021’s week 8, Shahrul Kamil bin Hassan (Team Arnhold), Bhavik Joshi (Team Arnhold), Marisa Duran (Team Arnhold), and I integrated the three epics in the Arnhold project which are Mesh Networking, Vision Processing, and Feedback Controlled Cars. The integration can be seen below. A...

14 Aug

Integrating an OpenMV camera to an origami car to create visual feedback control

Jillian Naldrien Pantig

During SURP 2021’s week 8, Bhavik Joshi (Team Arnhold), Marisa Duran (Team Arnhold), and I managed to integrate the vision processing and feedback controlled cars epic. Using Marisa’s OpenMV code and my code for controlling the cars, we were able to put an OpenMV camera in one of my four-wheeled o...

14 Aug

Controlling three origami cars with one joystick using mesh networking

Jillian Naldrien Pantig

During SURP 2021’s Week 7, Bhavik Joshi (Team Arnhold) and I were able to create a swarm of car robots using his Mesh Networking code and my cars. The cars were controlled by a single joystick through Sudarshian Seshadri’s (Team Arnhold) React-app dash. A gif of the car swarm is attached below. ...

11 Aug

FORAY - Update on Live Ball (with Distance) Detection

Aaron John Sabu

The video in the last post depicted a very slow detection of the ball. I also tested a CPU-trained model but, as expected, it was quite slow: To improve the performance of the algorithm, I replaced the original FasterRCNN model (torchvision.models.detection.fasterrcnn_resnet50_fpn()) with a mo...

11 Aug

Visualizing Rotation with AprilTags and Dashboard

Marisa Duran

Yesterday, I successfully integrated the camera with the dashboard (and the ESP32 featherboard). In the video demo below, I have the featherboard calling functions on the openMV camera, asking it to detect an apriltag and return rotation information (x, y, and z euler angles from the apriltags). The...

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