Arunachalam Sundaram

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About

Arunachalam Sundaram is a leading researcher in robotics and trajectory optimization, with a core focus on developing computationally efficient methods for smooth motion planning under kinematic constraints. His most-cited work introduces a novel approach using multiquadric radial basis functions (MQ-RBFs) to generate optimal trajectories for robotic manipulators. By minimizing a multi-objective function that balances time and jerk, Sundaram’s method addresses critical challenges in industrial and service robotics—enabling smoother, safer, and more precise movements while respecting real-world kinematic limits. This contribution has already garnered early citations, signaling its growing influence in the field. Sundaram’s research bridges the gap between advanced numerical techniques and practical robotic control, offering scalable solutions for tasks ranging from assembly lines to collaborative robots. His work is particularly notable for its rigorous mathematical foundation and direct applicability to systems requiring high-speed, low-vibration motion. As a rising voice in robotics, Sundaram continues to push the boundaries of trajectory planning, with his MQ-RBF framework poised to become a standard tool for researchers and engineers seeking to enhance robotic performance in constrained environments.