Simulation on Robot Arm Manipulator Modeling using Dynamic Kinematic

Ramli, Roshahliza M.; Herman, Nurul Aqilah; Adib, Mohd Azrul Hisham Mohd

doi:10.1109/etcce51779.2020.9350907

Cited by 2 publications

(1 citation statement)

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“…To achieve this mathematically, a global coordinate frame must be assigned to the base frame and a local reference frame must be assigned to each joint [62]- [66]. Homogeneous transformation matrices of size 4×4 is then computed for the robot joint axes using a formalism such as D-H (Denavit-Hartenberg) to define and interpret the robot's spatial geometry and end-effector location within a fixed reference system [67]- [70].…”

Section: A Kinematics Of the Robotmentioning

confidence: 99%

The Impact of Simplifications of the Dynamic Model on the Motion of a Six-Jointed Industrial Articulated Robotic Arm Movement

Fazilat,

Zioui

2024

Journal of Robotics and Control

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This research investigates the impact of model simplification on the dynamic performance of an ABB IRB-140 six-jointed industrial robotic arm, concentrating on torque prediction and energy consumption. The entire mathematical model of forward, reverse, differential kinematics, and dynamic model proposed based on the technical specifications of the arm, and to obtain the center of the mass and inertia matrices, which are essential components of the dynamic model, Utilizing Solidworks, we developed three CAD/CAM models representing the manipulator with varying detail levels, such as simplified, semi-detailed, and detailed. Our findings indicate minor differences in the model's torque and energy consumption graphs. The semi-detailed model consumed the most energy, except for joint 1, with the detailed model showing a 0.53% reduction and the simplified model a 6.8% reduction in energy consumption. Despite these variations, all models proved effective in predicting the robot's performance during a standard 30-second task, demonstrating their adequacy for various industrial applications. This research highlights the balance between computational efficiency and accuracy in model selection. While the detailed model offers the highest precision, it demands more computational resources, which is suitable for high-precision tasks. In discrepancy, simplified, less precise models offer computational efficiency, making them adequate for specific scenarios. Our study provides critical insights into selecting dynamic models in industrial robotics. It guides the optimization of performance and energy efficiency based on the required task precision and available computational resources. This comprehensive comparison of dynamic models underscores their applicability and effectiveness in diverse industrial settings.

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Section: A Kinematics Of the Robotmentioning

confidence: 99%