Destra Andika
Papers
1
Total Citations
3
H-Index
1
About
Destra Andika is a researcher at the forefront of embedded robotics and real-time object detection, with a focus on deploying lightweight deep learning models for disaster response applications. His most cited work introduces a novel integration of the YOLO V3-Tiny algorithm with a confusion matrix framework on a quadruped robot powered by a Raspberry Pi 3B+. This contribution enables the robot to accurately detect and classify human figures—both stationary and deceased—in challenging post-disaster environments, directly addressing critical needs in search-and-rescue operations. By optimizing computer vision for low-power, single-board computers, Andika’s research bridges the gap between advanced AI and practical, field-deployable robotics. His work has already garnered attention, with his flagship paper accumulating citations that underscore its relevance to the growing field of autonomous emergency response systems. Andika’s achievements demonstrate a commitment to creating accessible, real-time solutions that can save lives, making him a notable figure in the intersection of robotics, embedded systems, and humanitarian technology.
Research Focus
Key Achievements
Top Papers
- 1