EIONI
This video is a part of an AR Drone autonomous landing project. Here the AR Drone is controlling itself so that the landing platform is exactly in the middle so that it can initiate a proper landing. Here AR Drone is also tracking the Tag embedded on the landing platform (Not using the inbuilt tag detection. The tag that is being used here is from the ar_track_alvar package.). This is implemented using Neural Network. (The video is playing at a slightly faster rate.)
This is a demonstration of AR Drone 2.0 simulation under gazebo using tum_simulator on ROS Indigo. This video is a part of an autonomous landing of AR Drone project.
This is an obstacle avoiding robot which I and Sooraj Krishna built in ROS using STDR simulator. The robot is making decision based on a 3 layer Neural Network. The learning algorithm used is back-propagation (which we wrote in python). The network design is shown below.
This is a sample program I wrote to learn ROS. I have used linux joystick api to directly capture values of the analog stick of my joystick (F710 Wireless Gamepad). These data are then directly send to the turtlesim/cmd_velocity as a geometry_msgs/Twist type.
For some time I was thinking of making a simple clap switch for my room. ( Kind of lazy to go and switch off the light and fan every time… :-) ) First get it work on a breadboard.
