Papers
2
Total Citations
3
H-Index
1
About
Ronojit Pal is pioneering research at the intersection of computer vision and human-robot interaction, with a focused expertise in enabling safer, more perceptive mobile robots for human-robot coexisting environments. His primary contribution lies in developing robust algorithms for the visual detection of walking sticks—a critical yet often overlooked challenge in people-following robots. Pal’s work addresses the need for accurate detection under varying lighting and environmental conditions, where standard vision systems fail. His 2024 paper, "Photometric Invariant Visual Walking Stick Detection," introduces a stratified random sampling approach that achieves photometric invariance, ensuring reliable detection regardless of illumination changes. This foundational work has garnered early recognition with 2 citations, signaling its importance to the field. Building on this, his 2025 study employs kernel density estimation-based clustering to further refine detection accuracy, demonstrating a clear trajectory of innovation. Pal’s research directly contributes to the safety and autonomy of assistive robots, particularly in healthcare and eldercare settings. By solving a niche but vital problem, he is shaping the future of seamless human-robot coexistence, making his work essential reading for researchers in robotics, computer vision, and human-robot interaction.
Research Focus
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Top Papers
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