Adrian Li
19Patents
5h-index
17Co-inventors
55Inventor score
Filing activity: Jul 8, 2016 → Apr 5, 2023
Most-cited inventions
| Patent | Title | Area | Cited by | Status |
|---|---|---|---|---|
| US11188821B1 | Control policies for collective robot learning | Physics | 27 | Active |
| US10058995B1 | Operating multiple testing robots based on robot instructions and/or environmental parameters received in a request | Physics | 19 | Active |
| US10354139B1 | Generating and utilizing spatial affordances for an object in robotics applications | Emerging Cross-Sectional Technologies | 9 | Active |
| US10960539B1 | Control policies for robotic agents | Physics | 9 | Active |
| US10861184B1 | Object pose neural network system | Physics | 8 | Active |
| US10427296B1 | Operating multiple testing robots based on robot instructions and/or environmental parameters received in a request | Physics | 4 | Active |
| US10748057B1 | Neural network modules | Physics | 4 | Active |
| US10981270B1 | Operating multiple testing robots based on robot instructions and/or environmental parameters received in a request | Physics | 3 | Active |
| US11610153B1 | Generating reinforcement learning data that is compatible with reinforcement learning for a robotic task | Physics | 2 | Active |
| US11571809B1 | Robotic control using value distributions | Physics | 2 | Active |
| US11615291B1 | Neural network modules | Physics | 0 | Active |
| US11565401B1 | Operating multiple testing robots based on robot instructions and/or environmental parameters received in a request | Physics | 0 | Active |
| US11325252B2 | Action prediction networks for robotic grasping | Physics | 0 | Active |
| US10853646B1 | Generating and utilizing spatial affordances for an object in robotics applications | Emerging Cross-Sectional Technologies | 0 | Active |
| US12049004B1 | Operating multiple testing robots based on robot instructions and/or environmental parameters received in a request | Physics | 0 | Active |
| US9797168B1 | Tethering device | Fixed Constructions | 0 | Active |
| US12210943B2 | Training a policy model for a robotic task, using reinforcement learning and utilizing data that is based on episodes, of the robotic task, guided by an engineered policy | Physics | 0 | Active |
| US11625852B1 | Object pose neural network system | Physics | 0 | Active |
| US12387346B2 | Object pose neural network system | Physics | 0 | Active |
Source: USPTO / EPO open patent data. Inventor disambiguation is heuristic; counts are objective bibliographic measures.