Akanshu Mahajan

University of Delhi, Sri Venkateswara University

Papers

Total Citations

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About

Akanshu Mahajan’s research lies at the intersection of robotics, neural networks, and autonomous mapping, with a focus on enabling intelligent manipulation and environmental perception. His most impactful work, an unsupervised learning-based neural network approach for robotic manipulators (2017, 38 citations), introduced a novel framework that allows robotic arms to learn and adapt without labeled data, significantly reducing the need for manual programming in dynamic settings. This contribution has been foundational for researchers exploring adaptive control in unstructured environments. Mahajan also advanced spatial intelligence through his work on constructing 3D maps of indoor environments (2018, 5 citations), where he leveraged the Microsoft Kinect V2.0 RGB-D camera to develop a cost-effective method for real-time localization and mapping—a critical step for autonomous navigation in confined spaces. Additionally, his virtual experimental analysis of redundant robot manipulators using neural networks (2017, 2 citations) demonstrated how simulation-based training can optimize complex kinematic chains. Though early in his career, Mahajan’s integration of unsupervised learning with robotics has already shaped discussions on efficient, scalable automation, marking him as a promising voice in intelligent systems research.