Youssef, AbdelrahmanBayoumy, Amgad MAtia, Mostafa R.A2021-11-122021-11-1205/10/2021https://doi.org/10.18280/mmep.080502https://bit.ly/31XSmzVAlthough the Delta robot has many applications in pick-and-place operations, some problems limit its use. The difficult programming is one of these limitations. Parallel robot programming depends on solving the forward and inverse kinematics equations of the robot. These equations relate the geometric parameters, such as length and angle of every robot arm, to the position of the end effector and vice versa. The kinematic equations are hard to be derived. Moreover, any change in the robot geometry, due to a change in the application condition, requires that new kinematic equations be derived. This needs a very sophisticated and specialized programmer, who is not always available. Consequently, this problem limits the use of parallel robots. This paper discusses the use of ANN and embedded systems in addition to stereo vision to command delta robot in pick-and-place operations. The method is implemented and tested giving satisfactory results.en-USparallel robotdelta robotneural networksartificial intelligencepick and placeforward kinematicsinverse kinematicsArticlehttps://doi.org/10.18280/mmep.080502