Deep Reinforcement Learning for mobile robot navigation in ROS2 Gazebo simulator. Using DRL (SAC, TD3) neural networks, a robot learns to navigate to a random goal point in a simulated environment ...

Abstract: A flexible active safety motion (FASM) control approach is proposed for collision avoidance in robot manipulators ... allowing for dynamic adaptability during obstacle avoidance. In addition ...

Enables autonomous driving of a 2 or 4 wheel car with an Arduino and a Adafruit Motor Shield V2. To avoid obstacles a HC-SR04 Ultrasonic sensor mounted on a SG90 Servo continuously scans the area.

Since 1999 CCR staff along with UB & Roswell Park Faculty have presented a 2 week intensive workshop for local high school students. The topics vary yearly but all are developed to encourage students ...

However, individual robots often struggle with these intricate tasks, necessitating the collaboration of multi-robot systems. This study proposes a novel deep reinforcement learning (DRL)-based method ...