Intention-driven reinforcement learning-based path planning method
US12124282B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 13, 2021 |
| Grant date | Oct 22, 2024 |
| Priority date | — |
| Expiry date | Dec 13, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG05D2109/30
- WIPO fieldControl
- WIPO sectorInstruments
Abstract
The present invention discloses an intention-driven reinforcement learning-based path planning method, including the following steps: 1: acquiring, by a data collector, a state of a monitoring network; 2: selecting a steering angle of the data collector according to positions of surrounding obstacles, sensor nodes, and the data collector; 3: selecting a speed of the data collector, a target node, and a next target node as an action of the data collector according to an ε greedy policy; 4: determining, by the data collector, the next time slot according to the selected steering angle and speed; 5: obtaining rewards and penalties according to intentions of the data collector and the sensor nodes, and updating a Q value; 6: repeating step 1 to step 5 until a termination state or a convergence condition is satisfied; and 7: selecting, by the data collector, an action in each time slot having the maximum Q value as a planning result, and generating an optimal path. The method provided in the present invention can complete the data collection path planning with a higher probability of success and performance closer to the intention.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.