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Results for "robotic grasping"

Co-Modality Active sensing and Perception (C-MAP) in Autonomous Vehicles, Augmented Reality, Remote Environmental Monitoring, and Robotic Grasping

MBZUAI ·

Dezhen Song from Texas A&M University presented a talk on Co-Modality Active sensing and Perception (C-MAP) for robotics, covering sensor fusion for autonomous vehicles, augmented reality, and remote environmental monitoring. The talk highlighted lessons learned in sensor fusion using autonomous motorcycles and NASA Robonaut as examples. Recent works in robotic remote environment monitoring, especially focused on subsurface surface void and pipeline mapping were discussed. Why it matters: This research explores sensor fusion techniques to enhance robot perception, which could improve the robustness and capabilities of autonomous systems developed and deployed in the Middle East, particularly in challenging environments.

Unlocking the Potential of Large Models for Vision Related Tasks

MBZUAI ·

Yanwei Fu from Fudan University will present research on multimodal models, robotic grasping, and fMRI neural decoding. Topics include few-shot learning, object-centered self-supervised learning, image manipulation, and visual-language alignment. The research also covers Transformer compression and applications of large models with MVS 3D modeling in robotic arm grasping. Why it matters: While the talk is not directly about Middle East AI, the topics covered are core to advancing AI research and applications in the region.