International Journal of Mechatronics and Automation
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International Journal of Mechatronics and Automation (3 papers in press)
Trajectory tracking of 4-DOF robot manipulator: a bond graph approach by Rajmeet Singh, Manvir Singh Lamba, Tarun Kumar Bera Abstract: This research work presents the design of a position control algorithm for trajectory tracking of a four-degree-of-freedom robotic manipulator. The linkage mechanism of the manipulator is based on a parallelogram mechanism and in this manipulator, three parallelogram mechanisms are used. First, the CAD and the kinematic model of the manipulator are developed. The bond graph (BG) approach is applied to develop the dynamic model of the robotic arm based on kinematic equations. The BG model of parallelogram linkage is then compared with the Simulink model of parallelogram linkage and results are validated. Then, a position control algorithm is proposed to follow a set of trajectory planning applications. A GRBL-Arduino based controller is used to estimate the position of the end-effector as per the users requirements. The simulation and experimentation work are performed for 3D trajectory tracking applications. The robotic arm is used for pick and place operation within the workspace. Keywords: 4-DOF robotic arm; position control; GRBL controller; bond graph approach; Simulink; pick and place. DOI: 10.1504/IJMA.2022.10047206
The effects of crossmodal semantic reliability for audiovisual immersion experience of virtual reality by Hongtao Yu, Qiong Wu, Mengni Zhou, Qi Li, Jiajia Yang, Satoshi Takahashi, Yoshimichi Ejima, Jinglong Wu Abstract: Previous studies have reported that immersion experience can be improved by pairing it with auditory-visual stimuli; however, whether the semantic relationship of auditory-visual stimuli can also modulate visual virtual experience remains unclear. By using the psychophysics method, this study investigates the category performance under three different crossmodal semantic reliability conditions: semantically reliable, semantically unreliable and semantically uncertain. The results revealed a faster category speed for the crossmodal semantically reliable condition regardless of the category, indicating that crossmodal semantic reliability led to sufficient multisensory integration. In particular, under crossmodal semantically unreliable conditions, category speed was faster for non-living stimuli, indicating robust representation for non-living objects. These results indicate that adopting semantically reliable visual and auditory stimuli as multisensory inputs can efficiently improve the multisensory immersion experience. Keywords: audiovisual integration; semantic reliability; semantic category; selective attention; multisensory presence; virtual reality. DOI: 10.1504/IJMA.2022.10047450
Vascular centreline extraction for virtual reality interventional training systems by Peng Shi, Shuxiang Guo, Xiaoliang Jin Abstract: Vascular interventional surgery requires surgeon to be highly skilled at manipulating the surgical tools to avoid damaging blood vessel. Virtual reality (VR) interventional training systems were developed to reduce the training cost and improve training. For virtual interventional radiology, centreline of the vasculature is often used to reconstruct vasculature and detect the contact between surgical tools and blood vessel wall. In this paper, we introduce a centreline extraction method which is suitable for the vasculature mesh. The extraction method assume that the vasculature mesh is a set of continuous cylindrical shapes. The centreline is formed by centre point of the cylindrical shapes, and the centreline is satisfied rotational symmetry. In addition, we propose a pre-processing strategy to convert the mesh representation to point cloud representation. This strategy can merge duplicate vertex and normal vector for vasculature mesh while preserving the integrity of the vasculature. The performance of our method is experimentally validated. Keywords: centreline extraction; rotational symmetry axis; vasculature mesh; virtual interventional radiology; VR interventional training system. DOI: 10.1504/IJMA.2022.10047637