Trajectory reconstruction for robot programming by demonstration

Abstract

The reproduction of hand movements by a robot remains difficult and conventional learning methods do not allow us to faithfully recreate these movements because it is very difficult when the number of crossing points is very large. Programming by Demonstration gives a better opportunity for solving this problem by tracking the user’s movements with a motion capture system and creating a robotic program to reproduce the performed tasks. This paper presents a Programming by Demonstration system in a trajectory level for the reproduction of hand/tool movement by a manipulator robot; this was realized by tracking the user’s movement with the ArToolkit and reconstructing the trajectories by using the constrained cubic spline. The results obtained with the constrained cubic spline were compared with cubic spline interpolation. Finally the obtained trajectories have been simulated in a virtual environment on the Puma 600 robot.

Virtual reality's effects on air crash accident investigation learning interaction

“…In a similar vein, Chae et al [31] proposed a VR based hand gesture identification system that used a density based CNN. The visualisation connected with trajectory reconstruction has been demonstrated in Amar et al [32], and lastly, nature grasping has been revealed in Tian et al [33]. of this, the current study has it with due consideration on the job of marking the position of every piece of what had been a human being, from any angle, and having them from different resolutions had to be very difficult for everyone who was involved.…”

A simulated risk assessment of human-robot interaction in the domestic environment

“…4, December 2020 : 300 -310 302 using previous research and its findings with various parameters, such as optimality, completeness, stability, memory utilization, effective time and computer time etc. The programming by demonstration system was presented by Amar et al [20] on a trajectory level to reproduce hand/tool movement with a robot manipulator, which was achieved with the ArToolkit, tracking user movement and the trajectories with the limited cubic spine reworked. Attamimi et al [21] provided in a free play scenario a way to estimate the concentration of an infant, one of the most critical mental states.…”