Rebeca Curtis

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About

Rebeca Curtis is a roboticist specializing in dexterous manipulation and tactile sensing for autonomous systems. Her research focuses on enhancing robotic grasp performance through innovative sensor integration, particularly by combining in-hand proximity and contact sensing to improve object handling in unstructured environments. Her most-cited work, "Improving Grasp Performance Using In-Hand Proximity and Contact Sensing" (2018), has garnered 9 citations and represents a foundational contribution to the field, demonstrating how pre-contact proximity data can complement traditional tactile feedback to reduce grasp failures and enable more adaptive, real-time control. This work has implications for applications ranging from industrial automation to assistive robotics, where reliable manipulation is critical. Curtis’s research bridges the gap between sensing hardware and algorithmic control, advancing the state of the art in robotic dexterity. Her findings are particularly valued by researchers working on sensor-rich grippers and learning-based manipulation strategies. As a rising voice in robotics, Curtis continues to explore how multimodal sensing can unlock more human-like grasping capabilities in robots.