Upkie agent that can balance and crouch

Projet pointeur rouge - projet beta Adimaker 24/25

PID control interface for Windows and Linux using Python. The application communicates with an Arduino device via a serial connection, displaying sensor readings and allowing users to adjust PID control parameters dynamically. Can be used with any microcontroller through Serial over USB.

Demonstracijski program za robota Lego EV3, ki se zna premikati po danih točkah na poligonu.

A navigation simulation of differential drive robot based on PID control and model predictive control

Roll control system for the IREC 2020-21 rocket (Endurance) and Drag control system for the IREC 2021-22 rocket (Intrepid)

python lib for linear quadratic control

Controlling ultrasound output based on temperature sensor feedback.

ROS-based PI controller for robotic path tracking with Gazebo simulation and path visualization

Autonomous navigation system for a Crazyflie quadrotor in Webots simulator. Utilizes A* path planning algorithm and integrates real-time object recognition with YOLO.

The Controllers package provides various controllers for the robot, including a position controller that utilizes a PID algorithm for controlling the robot's position. The primary node in this package is positionController, which is responsible for managing the robot's movement towards a goal position.

PID Logger, Tuner and FOPDT Simulator using OPC-UA

Python PID Tuner with an additional PID Simulator and CSV Logger

Investigating Population Diversity, Sex Ratio Dynamics, and Resource Utilization: Insights into Lamprey Species within the Multispecies Ecosystem of the Great Lakes

Autonomous drawing robots with a 3 wheeled holonomic drive, completely run using ROS2.

Python GUI for sending commands to a prototype robotic leg.

Self Balancing Robot for Gazebo Simulation using ROS2

Network Model of the Cortical Basal Ganglia during Parkinson's Disease and Deep Brain Stimulation

Model of Motor Network during Parkinson's Disease and Deep Brain Stimulation. The model simulates LFP, EMG and associated force signals from the motor system. A multivariable adaptive control strategy is implemented in the model to control two biomarkers of Parkinsonian tremor and motor impairment symptoms.