A complete end-to-end demonstration in which we collect training data in Unity and use that data to train a deep neural network to predict the pose of a cube. This model is then deployed in a simulated robotic pick-and-place task.
I built a lua model and test it with python, its a 3DOF robot arm:
`
print("Lua: Constructing robot_3DOF")
inertiaMatrix = {
{2.0,0. ,0. },
{0. ,2.0,0. },
{0. ,0. ,2.0}
}
print("Lua: Body mass and geometry properties")
bodies = {
base = { mass = 1.,
com = {0.,0.,0.},
inertia = inertiaMatrix},
lin
A generalized inverse kinematics solver that supports closed chains for parallel kinematics systems, dynamic reconfiguration, and arbitrary joint configuration based on damped least squares error minimization techniques
Integration of Motoman CSDA10f dual arm robot with ROS, Moveit and Gazebo, with aims of creating a robotics developing platform for Invite GmbH, pre-configured to be simple to use and learn.
I built a lua model and test it with python, its a 3DOF robot arm:
`
print("Lua: Constructing robot_3DOF")
inertiaMatrix = {
{2.0,0. ,0. },
{0. ,2.0,0. },
{0. ,0. ,2.0}
}
print("Lua: Body mass and geometry properties")
bodies = {
base = { mass = 1.,
com = {0.,0.,0.},
inertia = inertiaMatrix},
lin