RESUMO
This paper introduces a Hexa parallel robot and obstacle collision detection method based on dynamic modeling and a computer vision system. The processes to deal with the collision issues refer to collision detection, collision isolation, and collision identification applied to the Hexa robot, respectively, in this paper. Initially, the configuration, kinematic and dynamic characteristics during movement trajectories of the Hexa parallel robot are analyzed to perform the knowledge extraction for the method. Next, a virtual force sensor is presented to estimate the collision detection signal created as a combination of the solution to the inverse dynamics and a low-pass filter. Then, a vision system consisting of dual-depth cameras is designed for obstacle isolation and determining the contact point location at the end-effector, an arm, and a rod of the Hexa robot. Finally, a recursive Newton-Euler algorithm is applied to compute contact forces caused by collision cases with the real-Hexa robot. Based on the experimental results, the force identification is compared to sensor forces for the performance evaluation of the proposed collision detection method.
Assuntos
Robótica , Algoritmos , Inteligência Artificial , Fenômenos Biomecânicos , Hexosaminidase A , Robótica/métodosRESUMO
This paper presents the chaotic analysis of the single-walled carbon nanotubes on elastic medium. Due to small scales of the nanotubes, the nonlocal elastic theory is applied. Besides, due to large-amplitude vibrations of the nanotubes, the geometrical nonlinearity is taken into account, so the von Kármán strain is incorporated. The results show that the period-three oscillation, the chaos and the period-one oscillation are excited by the different excitation amplitudes. In addition, the excitation amplitude of the chaos increases as the nonlocal parameter increases. These results are also validated by the steady-state time responses, the FFT spectrums, the phase portraits, and the Poincaré sections.