Ander Iriondo
Papers
6
Total Citations
147
H-Index
4
About
Ander Iriondo is a leading researcher in intelligent robotic manipulation, with a focus on automating complex logistics and industrial tasks. His work centers on integrating deep reinforcement learning (DRL) and advanced computer vision to enable mobile manipulators and bin-picking systems to operate with unprecedented autonomy. Iriondo’s major contributions include developing DRL-based policies for mobile manipulator positioning and pick-and-place operations, as demonstrated in his highly cited 2019 paper (81 citations), which addresses the high cost of programming complex robotic tasks. He has also advanced grasp detection using graph convolutional networks for industrial bin-picking (37 citations), significantly improving generalization under uncertainty. His recent work on dynamic mosaic planning, part of the European PICKPLACE project, showcases a flexible system capable of packing diverse objects without manual adjustments. With a growing body of work that bridges simulation and real-world application—including synthetic data generation for segmentation models—Iriondo’s research is pivotal in making robotics more adaptable, efficient, and cost-effective for modern distribution centers and manufacturing environments.
Research Focus
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Top Papers
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