[T-ITS'23] Sim-to-real goal-oriented mapless autonomous navigation (DRL navigation).
This repository provides an OpenAI Gym-compatible environment for production scheduling tasks, designed to benchmark reinforcement learning agents in job shop and flow shop settings.
A reinforcement learing environment for robotic mobile fulfilment system (RMFS)
This repository contains Python scripts that demonstrate how to use Plant Simulation as a learning environment for Reinforcement Learning (RL) algorithms to tackle deadlock situations in Automated Guided Vehicle (AGV) systems. The code is compatible with the Gymnasium and Ray libraries.
Mobile robot data were analyzed with Apache-Spark to extract five different statistical result such as travel time, waiting time, average speed, occupancy and density were produced.
Simulating multiple AGVs (Automated Guided Vehicles) with VDA 5050 protocol, sending them orders, and visualizing their movement and status via MQTT.
This repository contains a simulation of an AGV using ros2, rviz2, gazebo and ros2 control.
This repository collects reference implementations for training and evaluating reinforcement learning agents on multi-agent pathfinding problems. The environments explicitly support deadlocks so that agents must cooperate to resolve them.
This project is aiming to solve multiple vehicle routing problems.
🔍 Build an ultrasonic radar using an embedded Linux SoC, enabling remote viewing and real-time measurements through a simple Python script.
This project is an AGV (Automated Guided Vehicle) path planning simulator using Pygame. Users can click on a location to set different path types (Turning, Idle, Normal, Charging), place an AGV, and move it along selected paths. The simulation runs on a clean map instead of a grid.
We proposed a new approach to detect anomalies of mobile robot data. We investigate each data seperately with two clustering method hierarchical and k-means. There are two sub-method that we used for produce an anomaly score. Then, we merge these two score and produce merged anomaly score as a result.
Benchmarking of Navigationalgorithms with Gazebo
A PyQt6-based user interface system designed for controlling an autonomous AGV developed by KOU Rover, fully integrated with ROS 2. Includes real-time sensor tracking, emergency handling, QR code localization, and scenario-based automation. Originally built for TEKNOFEST 2024.
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