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Palitha Dassanayake is a robotics researcher whose work centers on intelligent motion planning and control for robotic manipulators, with a particular emphasis on fuzzy behavior-based systems. His major contributions lie in developing novel control architectures that enable multi-link robot arms to perform complex tasks—such as reaching targets while avoiding obstacles—using online sensory information. By adapting subsumption-style behavior control, originally designed for mobile robots, to the domain of stationary manipulators, Dassanayake pioneered a flexible, modular approach to trajectory generation in Cartesian space. His most-cited paper, "Fuzzy behavior-based motion planning for the PUMA robot" (2002, 7 citations), demonstrates a fuzzy planning system for a six-degree-of-freedom PUMA arm, while his earlier work on three-link manipulators (1999, 2003) established the foundational methodology. Across his publications, Dassanayake’s research has garnered over 25 citations, reflecting its niche but sustained influence in the field of intelligent robotics. Notably, he integrated genetic algorithms to train fuzzy behavior elements, showcasing an early commitment to learning-based optimization in control systems. His work remains a valuable reference for researchers exploring behavior-based control in structured industrial environments.