Papers
16
Total Citations
579
H-Index
10
About
Zhiqiang Tian is a prominent researcher at the intersection of computer vision, robotics, and human-robot interaction, with particular expertise in robotic grasping and teleoperation systems. His most influential contributions center on developing neural network architectures for real-time robotic grasp detection, most notably his pioneering work on the Fully Convolutional Grasp Detection Network with Oriented Anchor Box (2018), which has garnered over 226 citations and established a foundational approach for predicting multi-pose grasping using RGB images. Building on this, Tian advanced the field further with REGNet (2021), extending grasp detection into 3D point cloud environments to address unstructured real-world conditions. His Visual Manipulation Relationship Network (2018, 82 citations) tackled the complex challenge of multi-object scene understanding, a critical limitation of earlier CNN-based approaches. Beyond pure robotics, Tian has made noteworthy contributions to space teleoperation research, investigating how individual cognitive characteristics influence remote robotic arm performance—work with significant implications for space exploration missions. With a cumulative citation count exceeding 550 across his top works, Tian's research meaningfully bridges intelligent robot perception and human-centered design in demanding operational environments.
Research Focus
Key Achievements
Top Papers
- 1Fully Convolutional Grasp Detection Network with Oriented Anchor Box226 citations · 2018
- 2Visual Manipulation Relationship Network for Autonomous Robotics82 citations · 2018
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- 4A Real-Time Robotic Grasping Approach With Oriented Anchor Box70 citations · 2019
- 5Visual manipulation relationship recognition in object-stacking scenes22 citations · 2020
- 6Fully Convolutional Grasp Detection Network with Oriented Anchor Box22 citations · 2018
- 7Association of Individual Characteristics with Teleoperation Performance19 citations · 2016
- 8ROI-based Robotic Grasp Detection for Object Overlapping Scenes13 citations · 2019
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