Avinesh Lal
Papers
1
Total Citations
5
H-Index
1
About
Dr. Avinesh Lal is a researcher at the intersection of robotics and machine learning, with a primary focus on developing intelligent control systems for autonomous navigation. His most-cited work, "Obstacle Avoidance of a Point-Mass Robot using Feedforward Neural Network" (2021, 5 citations), demonstrates a foundational contribution to applying neural network architectures for real-time path planning in constrained environments. This research addresses a critical challenge in robotics—enabling point-mass robots to dynamically avoid obstacles without pre-mapped trajectories, leveraging feedforward networks for efficient decision-making. While his citation count is modest, the work represents a practical step toward integrating machine learning into robotic control for hazardous applications such as manufacturing, healthcare, and landmine detection. Dr. Lal’s research underscores the growing role of AI in automating complex, high-risk tasks, and his approach offers a scalable framework for future studies in autonomous systems. His contributions are particularly relevant for students and researchers exploring neural-network-based solutions for real-world robotic challenges, highlighting the potential of lightweight, data-driven models in constrained operational settings.
Research Focus
Key Achievements
Top Papers
- 1