Deval Yag

Papers

Total Citations

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About

Deval Yag is a robotics researcher whose work centers on motion planning and control for multi-link robotic systems. His most-cited paper, "Motion planning for multi-link robots using Artificial Potential Fields and modified Simulated Annealing" (2010, 22 citations), introduces a hybrid control methodology that integrates Artificial Potential Fields with a modified Simulated Annealing optimization algorithm. This approach, inspired by snake locomotion, enables teams of multi-link snake robots to navigate complex environments with enhanced efficiency and obstacle avoidance. Yag’s contributions are notable for bridging classical control techniques with stochastic optimization, offering a robust framework for autonomous robot coordination. While his citation count reflects a focused niche, his work has influenced subsequent research in bio-inspired robotics and multi-agent path planning. Yag’s achievements demonstrate a commitment to solving real-world challenges in robotic mobility, making his research a valuable reference for students and engineers exploring adaptive motion strategies in constrained or hazardous settings.