公开(公告)号：US20250036138A1

公开(公告)日：2025-01-30

申请号：US18783703

申请日：2024-07-25

Applicant: Korea Advanced Institute of Science and Technology

Inventor： Hyun Myung ,  Seungwon Song ,  I Made Aswin Nahrendra ,  Junho Choi ,  Duckyu Choi ,  Seunghyun Lee ,  Eungchang Lee

IPC: G05D1/622 ,  B64U30/299 ,  B64U101/30 ,  G05D1/242 ,  G05D1/243 ,  G05D1/245 ,  G05D1/246 ,  G05D105/80 ,  G05D109/25 ,  G06T7/70 ,  G06V20/17

Abstract: Provided is an autonomous flight system of a drone unit including an information acquisition unit configured to acquire first information through a camera mounted to the drone unit, acquire second information through LiDAR, and acquire third information through an inertial measurement unit (IMU); an information processing unit configured to estimate a pose of the drone unit through the second information and the third information, acquire a coordinate value of a target object through the first information and the second information, and construct a 3D map and an unknown area exploration algorithm based on a pose estimation value of the drone unit, the coordinate value of the target object, and the second information; a path planner configured to generate an obstacle avoidance path based on the 3D map and the unknown area exploration algorithm; and a flight controller configured to apply the obstacle avoidance path to the drone unit.

公开(公告)号：US20240001961A1

公开(公告)日：2024-01-04

申请号：US18101169

申请日：2023-01-25

Applicant: Korea Advanced Institute of Science and Technology

Inventor： Hyun Myung ,  Euigon Jung ,  Wonho Song

IPC: B60W60/00

CPC classification number: B60W60/0011 ,  B60W60/0015 ,  B60W2556/40 ,  B60W2554/40 ,  B60W2554/20

Abstract: Disclosed is a high-definition (HD) map-based local path planning method and apparatus for dynamic and static object avoidance. An HD map-based local path planning method for dynamic and static object avoidance performed by a computer device includes verifying a position on a global path by parameterizing the global path using an arc length; generating a path candidate group based on the global path; and selecting an optimal path as a path having a smallest cost function related to a global path following from the path candidate group. The cost function includes a global-path-following cost for selecting a path candidate group having a smallest lateral offset from the global path.