Papers
4
Total Citations
25
H-Index
3
About
Didit Widiyanto is a robotics and intelligent systems researcher whose work sits at the intersection of autonomous robotics, computer vision, and bio-inspired optimization algorithms. His research makes significant contributions to two principal domains: robotic surveillance systems and odor source localization (OSL). In the surveillance arena, Widiyanto has developed autonomous object detection and tracking systems, including notable work utilizing Parrot AR.Drone unmanned aerial vehicles (UAVs) integrated with OpenCV and the Robot Operating System (ROS), demonstrating practical applications of real-time image processing in autonomous platforms. His most impactful contributions, however, lie in advancing Particle Swarm Optimization (PSO) for odor source localization problems. His 2016 review of PSO algorithms for single and multiple odor source scenarios — his most cited work with 9 citations — provided a comprehensive survey of progress and challenges in the field. He further proposed meaningful algorithmic modifications to the PSO global best term, improving search efficiency in complex odor environments. Collectively, Widiyanto's research bridges theoretical optimization with real-world robotic applications, offering valuable frameworks for researchers working on environmental monitoring, search-and-rescue robotics, and autonomous sensing systems.
Research Focus
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Top Papers
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