Nemanja Rakicevic
Papers
4
Total Citations
66
H-Index
4
About
Nemanja Rakicevic is a robotics researcher whose work focuses on a critical and underexplored niche: the development of autonomous rescue robots capable of performing physical casualty extraction. His research integrates mechanical design, control systems, and computer vision to create robots that can safely locate, secure, and transport injured individuals in emergency scenarios. Rakicevic’s most cited work, "ResQbot 2.0" (33 citations), introduces an improved mobile rescue robot featuring an innovative inflatable neck securing device, addressing the gap between search and rescue robotics and actual physical intervention. He further advances autonomous operation through "Hierarchical Decomposed-Objective Model Predictive Control" (15 citations), which simplifies casualty extraction by reducing reliance on skilled teleoperation. In perception, his "Sim-to-Real Learning for Casualty Detection" (10 citations) enables robots to detect prone human bodies using point cloud data, a crucial step toward full autonomy. Rakicevic also contributes to robot learning with an active learning framework (8 citations) that efficiently explores movement parameter space for complex task acquisition. His work is notable for tackling the high-stakes challenge of translating robotic capabilities from simulation and lab settings to real-world rescue operations, with direct implications for saving lives in disaster response.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4