Papers
11
Total Citations
313
H-Index
6
About
Branden Romero is a robotics researcher specializing in tactile sensing, robot manipulation, and dexterous robotic hand design. His work sits at the intersection of hardware innovation and machine learning, with a particular focus on enabling robots to perceive and interact with the physical world through touch. Romero is perhaps best known for his contributions to the GelSight Wedge sensor (2021, 128 citations), a compact vision-based tactile sensor capable of measuring high-resolution 3D contact geometry — a critical capability for manipulation in visually occluded environments. His SwingBot system (2020, 109 citations) demonstrated that robots could learn physical properties such as mass and center of mass through in-hand tactile exploration, enabling dynamic, gravity-driven manipulation tasks. Beyond individual sensors, Romero has advanced the design of fully integrated robotic hands, including the multi-GelSight gripper (2020) and the EyeSight Hand (2024), a 7-DoF humanoid hand combining vision-based tactile sensing with compliant quasi-direct drive actuation. His earlier work on proximity and contact sensing for grasp improvement further underscores a career-long commitment to richer robot perception. Across his publications, Romero's research consistently pushes toward robots that can feel, adapt, and manipulate with human-like dexterity.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5Improving Grasp Performance Using In-Hand Proximity and Contact Sensing9 citations · 2018
- 6
- 7
- 8
- 9
- 10Improving grasp performance using in-hand proximity and contact sensing3 citations · 2017