Vyomkesh Kumar Jha

Papers

Total Citations

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About

Vyomkesh Kumar Jha is a robotics researcher whose work centers on motion planning, perception tuning, and the optimization of robotic frameworks for real-world manipulation tasks. His most cited study, "Tuning Perception and Motion Planning Parameters for MoveIt! Framework" (2020), systematically benchmarks the key parameters within the widely-used MoveIt! motion planning ecosystem, identifying those that most critically influence system performance. By conducting initial experiments on a simulated UR3 robot workspace, Jha provided a foundational methodology for practitioners to fine-tune perception and planning pipelines, directly impacting the efficiency and reliability of robotic arm operations. This contribution is particularly valuable for researchers and engineers working with collaborative robots, as it demystifies the often opaque parameter selection process in complex frameworks. While his citation count is still growing, Jha’s work represents an important step toward more transparent and performant robotic system design, bridging the gap between theoretical planning algorithms and practical deployment in industrial and research settings.