AI-Driven Real-Time Kinematic and Dynamic Analysis of UR5 Robotic Arm for Business Optimization
DOI:
https://doi.org/10.54536/ajsts.v4i1.4563Keywords:
AI-Driven Optimization, Business Productivity, Dynamic Modeling, Real-Time Kinematic Analysis, UR5 Robotic ArmAbstract
This paper offers a novel AI-based approach to perform real-time kinematic and dynamic analysis of the UR5 robotic arm to apply it in the business realm for robotic improvement. The data set used in this study includes accurate time based motion information of elbow, shoulder, wrist and hand joint angles (j1-j6) of the arm, their speeds and accurate time based position information of the tool (X,Y,Z) in different intervals, which is very useful to assess the operational parameters of the arm. The study aims at developing effective predictive models and optimisation algorithms for the robot’s kinematic equations of motion that relation the joint movements and velocities, as well as tool position in the 3-space. These concepts aid in evaluating how efficient the robotic tasks in an environment that simulate reality are. According to the findings of the present study, analyzing the kinematics and dynamics of the robot, there are specific parameters that indicate the efficiency of the robot’s movement, including precise joint angles or synchronism of arm movements. This research explores the extent to which the aforementioned factors affect the business productivity directly and highlights the benefits accrued by improving the robotic performance in regards to decreased amount of time wasted on repairs, improved accuracy and optimal resource utilization. This paper explores how AI models can enhance the supervisory control of robotic systems and allow real-time control of decision-making parameters to increase the efficiency of tasks and profitability in the business. The works provide further essence to elevate the real-time robotic optimization within industrial automation that deploying Artificial Intelligence in the working environments can provide logical, best and can be most suitable for the complex business areas placed in organisms where growing and changing rapidly. This way, it is possible to have higher levels of automation, and increase production processes, and profitability.
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Copyright (c) 2025 Sudipta Sotra Dhar, Shovra Sotra Dhar, Sazib Hossain
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