Antonio Zea
Papers
8
Total Citations
60
H-Index
4
About
Antonio Zea is a robotics researcher whose work centers on human-robot interaction, haptic feedback, and intuitive control for robotic systems. His key contributions lie at the intersection of teleoperation, manipulation, and sensor-based state estimation, with a strong emphasis on making robots more accessible and effective in real-world, unstructured environments. His most cited work, “Affordance-Based Grasping and Manipulation in Real World Applications” (24 citations), addresses the challenge of enabling robots to autonomously identify interaction possibilities in cluttered scenes, a critical step toward practical deployment. Zea has also pioneered novel approaches to haptic-guided path generation for remote vehicles (18 citations) and haptic rendering for robot programming, reducing the need for specialized input devices and expertise. More recently, he has advanced calibration-free inertial sensor methods for kinematic state estimation, improving control accuracy without cumbersome setup. His research extends into mixed reality and augmented reality, where he explores intention estimation using recurrent neural networks and robot tracking with mobile depth cameras. Through these contributions, Zea is shaping a future where robots are not only more autonomous but also more seamlessly integrated into human-centered tasks, from manufacturing to hazardous environment decontamination.
Research Focus
Key Achievements
Top Papers
- 1Affordance-Based Grasping and Manipulation in Real World Applications24 citations · 2020
- 2Haptic-Guided Path Generation for Remote Car-Like Vehicles18 citations · 2021
- 3Haptic Rendering of Arbitrary Serial Manipulators for Robot Programming5 citations · 2021
- 4
- 5
- 6
- 7
- 8