Trained human-intention classifier for safe and efficient robot navigation
US9776323B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 6, 2016 |
| Grant date | Oct 3, 2017 |
| Priority date | — |
| Expiry date | Feb 17, 2036 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY10S901/49
- WIPO fieldHandling
- WIPO sectorMechanical engineering
Abstract
A trained classifier to be used with a navigation algorithm for use with mobile robots to compute safe and efficient trajectories. An offline learning process is used to train a classifier for the navigation algorithm (or motion planner), and the classifier functions, after training is complete, to accurately detect intentions of humans within a space shared with the robot to block the robot from traveling along its current trajectory. At runtime, the trained classifier can be used with regression based on past trajectories of humans (or other tracked, mobile entities) to predict where the humans will move in the future and whether the humans are likely to be blockers. The planning algorithm or motion planner generates trajectories based on predictions of human behavior that allow the robot to navigate amongst crowds of people more safely and efficiently.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.