Papers

9

Total Citations

48

H-Index

4

About

Edwar Jacinto is a Colombian researcher whose work sits at the intersection of autonomous robotics, swarm intelligence, and motion planning in unknown environments. His research consistently tackles one of robotics' most demanding challenges: enabling robots to navigate, explore, and make decisions in dynamic, unstructured spaces without prior environmental knowledge. Jacinto's most recognized contribution — his 2012 paper on Brownian motion as an exploration strategy for swarm robots — has accumulated 13 citations and introduced a biologically inspired approach to search-and-rescue robotics in disaster scenarios such as landslides. This work laid a conceptual foundation he continued building upon through subsequent research on stereoscopic obstacle detection using bacterial behavior models, LSTM-based pattern recognition for navigation, and Rapidly Exploring Random Trees (RRT) algorithms implemented on low-cost ESP32-controlled robots. A recurring theme across his portfolio is accessibility and practicality — designing intelligent robotic solutions that are computationally efficient and affordable. His work on underactuated robotic hand control and ART-2 neural networks for motion planning further demonstrates his interdisciplinary reach. Beyond robotics, Jacinto has also contributed to engineering education, exploring inductive and problem-based learning methodologies. With over 40 cumulative citations, his work offers meaningful contributions to the growing field of autonomous systems research.

Research Focus

Key Achievements

4
H-Index
9
Papers
48
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
Brownian motion as exploration strategy for autonomous swarm robots
13 citations · 2012
📈 Most Prolific Year: 2020 (2 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: District University of Bogotá

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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