B.D.M. Garrido
Papers
1
Total Citations
28
H-Index
1
About
B.D.M. Garrido is a researcher whose work sits at the intersection of robotics, artificial intelligence, and autonomous navigation. Their key research areas include neural network control systems, mobile robotics, and obstacle avoidance in dynamic environments. Garrido’s most notable contribution is the development of a novel backward artificial neural network (ANN) structure for mobile robot control, which enables robots to navigate environments with moving obstacles by learning from both past and future positions. This pioneering work, published in 2003, has garnered 28 citations and laid important groundwork for intelligent, adaptive robotic behavior. Garrido’s research is particularly impactful for students and engineers working on autonomous systems, offering a computationally efficient approach to real-time path planning and collision avoidance. Their work stands as a valuable reference in the field of neural-network-based robotics, demonstrating how biologically inspired models can solve complex, real-world navigation challenges.
Research Focus
Key Achievements
Top Papers
- 1