Papers
9
Total Citations
84
H-Index
6
About
Abhilasha Singh is a dynamic robotics and computer vision researcher whose work sits at the intersection of intelligent automation, deep learning, and autonomous systems. Her research spans vision-guided robotics, robotic welding, simultaneous localization and mapping (SLAM), and reinforcement learning-based path planning — areas critical to the advancement of Industry 4.0 manufacturing and logistics. Singh's most influential contribution, a comprehensive survey on vision-guided robotic systems with intelligent control strategies (2022, 29 citations), established her as a thoughtful synthesizer of cutting-edge developments in adaptive robotics. Her work on GAN-based image dehazing for weld seam classification (16 citations) tackled a particularly stubborn industrial challenge — improving robotic welding accuracy despite visual noise from arc light and fumes — demonstrating her talent for applying generative AI to real-world constraints. Further contributions examining object detection algorithms for welding applications and multi-sensor fusion for GPS-denied warehouse environments reflect her commitment to practical, deployable robotics solutions. More recently, Singh has explored bio-inspired reinforcement learning for manipulator obstacle avoidance and event-based SLAM optimization for high dynamic range industrial scenarios. With a growing citation record across multiple research threads, she represents an emerging voice in intelligent robotics research with strong implications for manufacturing, warehouse automation, and beyond.
Research Focus
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Top Papers
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