Zendi Iklima
Papers
6
Total Citations
29
H-Index
3
About
Zendi Iklima is a robotics researcher whose work bridges intelligent control, collision avoidance, and human-robot interaction. Their primary research areas include parallel-link (Delta) robots, arm manipulators, and mobile robotics, with a strong focus on integrating machine learning and deep neural networks for autonomous operation. Iklima’s major contributions include pioneering a self-learning framework for Delta robots using inverse kinematics and artificial neural networks (10 citations), and developing a novel self-collision avoidance system for arm robots by combining Generative Adversarial Networks with Particle Swarm Optimization (7 citations). They have also advanced mobile robot navigation using AlexNet on edge computing hardware like the NVIDIA Jetson Nano (4 citations), and explored sentiment classification for trajectory control using word embeddings and convolutional neural networks (3 citations). Their work on microservices-based distributed deep neural networks for robot control (3 citations) demonstrates a commitment to scalable, cloud-integrated systems. Iklima’s research is notable for its practical applications in manufacturing and education, consistently leveraging state-of-the-art AI techniques to solve real-world robotic challenges.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6