Darko Trivun

Papers

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About

Darko Trivun is a robotics researcher whose work centers on autonomous navigation, simultaneous localization and mapping (SLAM), and adaptive locomotion for mobile robots. His most impactful contribution, the 2015 paper "Active SLAM-based algorithm for autonomous exploration with mobile robot" (33 citations), introduces a fully autonomous exploration and mapping algorithm for unknown indoor environments. By integrating active SLAM with a laser sensor-equipped mobile robot, Trivun enables robots to intelligently decide where to move next to build accurate maps while localizing themselves—a critical capability for search-and-rescue, warehouse automation, and service robotics. His research also extends to resilient robotic systems, as demonstrated in his 2017 work on a hexapod robot (2 citations). Here, he employs genetic algorithms to teach a six-legged robot new locomotion patterns after partial system failures, allowing it to adapt and continue functioning despite damage. This work contributes to the growing field of fault-tolerant robotics, where machines must operate reliably in unpredictable environments. Trivun’s combined focus on autonomous exploration and adaptive resilience positions him as a contributor to practical, real-world robotic systems that can navigate and survive in complex, changing settings.