Papers
11
Total Citations
35
H-Index
4
About
Ronnier Frates Rohrich is a robotics researcher whose work spans autonomous and collaborative robotic systems, human-machine interaction, and industrial inspection technologies. His research consistently bridges theoretical innovation with practical application, particularly in environments hazardous to humans. Among his most recognized contributions is his 2019 work on gesture-based robot control using deep learning and RGB cameras, which proposed an accessible, cost-effective alternative to conventional control interfaces for mobile robots. Rohrich has also made significant strides in multi-robot systems, exploring bio-inspired swarm behaviors for smart factory environments and deploying distributed sensor networks to detect and map gas leaks, enabling safer industrial navigation. His collaborative robotics work—including quadrocopter-ground robot coordination using ArUco markers—demonstrates a strong interest in hybrid aerial-terrestrial sensing systems. More recently, he has advanced predictive inspection of power lines through autonomous line-crawling robots equipped with multimodal sensors, alongside developments in digital twin modeling using the SyncLMKD framework. With over 30 cumulative citations across his published works, Rohrich's portfolio reflects a dedicated focus on making robotic systems smarter, safer, and more collaborative in complex real-world settings.
Research Focus
Key Achievements
Top Papers
- 1
- 2A novel method for Multi-Modal Predictive Inspection of Power Lines4 citations · 2024
- 3Bio-inspired Distributed Sensors to Autonomous Search of Gas Leak Source4 citations · 2020
- 4A Bio-Inspired Approach for Robot Swarm in Smart Factories4 citations · 2019
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- 10A Robotic Cable-Gripper for Reliable Inspection of Transmission Lines1 citations · 2024