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About

Nikhil Kakodkar is a roboticist whose research bridges autonomous navigation, environmental monitoring, and human-robot interaction. His work centers on three key areas: visual mapping for marine ecology, model-based pursuit for robotic cinematography, and leveraging large language models (LLMs) for semantically intelligent robot planning. Kakodkar’s most impactful contribution is an efficient Gaussian process-driven method for terrain-adaptive coral reef coverage, enabling mosaic synthesis for environmental assays (28 citations). He further advanced multi-robot systems by demonstrating heterogeneous aquatic robots that correlate sensor data over coral reefs (14 citations). In pursuit robotics, he developed a probabilistic inverse reinforcement learning framework that allows a follower robot to re-establish visual contact with a moving target (12 citations). More recently, Kakodkar has pioneered the integration of LLMs into robotic planning, creating the ANSEL Photobot—a robot event photographer with semantic intelligence (7 citations)—and the CARTIER system for cartographic language reasoning in navigation (4 citations). His latest work explores constrained navigation on preferred terrains using speech instructions and adverbs (1 citation). With a total of 66 citations across his six most-cited papers, Kakodkar’s trajectory from marine robotics to language-guided autonomous systems marks him as an innovator in making robots both environmentally aware and intuitively communicative.