Delara Mohtasham
Papers
1
Total Citations
5
H-Index
1
About
Delara Mohtasham is a roboticist whose research lies at the intersection of haptic sensing, dexterous manipulation, and autonomous object estimation. Her work addresses a critical gap in robotics: enabling robots to perceive and interact with objects in environments where vision fails—such as under occlusion, poor lighting, or confined spaces. Her most-cited paper, “Haptic Object Parameter Estimation during Within-Hand Manipulation with a Simple Robot Gripper” (2020), introduces a novel framework that uses tactile feedback from simple grippers to estimate object properties like shape, stiffness, and texture during in-hand manipulation. This approach challenges the field’s heavy reliance on optical sensors, offering a more robust solution for real-world applications like manufacturing, search-and-rescue, and assistive robotics. While her citation count is still growing, Mohtasham’s work is notable for its practical, low-cost approach to haptic estimation—paving the way for more adaptive and resilient robotic systems. Her contributions are especially relevant for researchers exploring sensorimotor control and embodied intelligence in robots.
Research Focus
Key Achievements
Top Papers
- 1