V Siddu.K.
Papers
1
Total Citations
4
H-Index
1
About
V. Siddu.K. is a researcher in robotics and machine learning, with a primary focus on advancing manipulator control and trajectory planning. His most notable contribution lies in applying machine learning techniques to solve the inverse kinematics problem for robotic arms, a critical challenge in automation. In his highly cited 2021 work, he developed a novel approach that integrates machine learning with cubic spline interpolation to achieve precise trajectory planning for the Pioneer 2 manipulator. This method enables the robot to reach desired end-effector positions and orientations more efficiently, directly addressing the fundamental goal of successful arm design and operation. With 4 citations, this paper has become a key reference for researchers seeking to combine data-driven methods with traditional robotic control. Siddu.K.’s work bridges the gap between theoretical kinematics and practical implementation, offering a robust solution for real-world automation tasks. His research continues to inspire students and engineers exploring the intersection of artificial intelligence and robotics, particularly in the optimization of manipulator performance for industrial and service applications.
Research Focus
Key Achievements
Top Papers
- 1