Dejan Kaljaca

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About

Dejan Kaljaca is a roboticist whose work sits at the intersection of motion planning, computer vision, and agricultural automation. His primary research focuses on developing intelligent algorithms for robotic manipulation in unstructured, natural environments—specifically, the complex task of automated bush and topiary trimming. Kaljaca’s major contribution is a novel coverage trajectory planning algorithm that balances two traditionally conflicting objectives: the accuracy required for precise surface sweeping and the smoothness needed for efficient robot motion. This work, published in 2019 and cited 49 times, represents a significant advance over prior art by formulating the problem as an optimal route search over a graph. He further demonstrated the practical viability of his approach in a companion paper (10 citations), where he integrated stereo vision with a robotic arm to create a fully automated system capable of trimming boxwood hedges into user-specified shapes. Unlike specialized, single-shape solutions, Kaljaca’s vision-based shape fitting module ensures remarkable flexibility. His research is paving the way for a new generation of autonomous landscaping robots that can handle the nuanced, real-world variability of living plants.