Amazon Technologies, Inc.

Tianyang Ma

Kah Kuen Fu

Amit Kumar Agrawal

Sharadh Ramaswamy

Ambrish Tyagi

Stephen Vincent Mangiat

Jim Oommen Thomas

Cheng-Hao Kuo

Sisil Sanjeev Mehta

Cheng Kai Chen

Yang Liu

Chong Huang

Yibo Cao

An aerial vehicle is configured to operate within indoor spaces. The aerial vehicle is programmed with positions of waypoints within three-dimensional space, and to calculate a trajectory for traveling through such waypoints in a manner that minimizes snap of the aerial vehicle. Where a distance between a pair of the waypoints is sufficiently long, the aerial vehicle inserts intervening waypoints for planning purposes, and programs the aerial vehicle to travel at a maximum speed between the intervening waypoints. Upon detecting an obstacle with a first range using one or more sensors, the aerial vehicle reduces its speed and monitors a second, shorter range using the sensors, and compensates for motion between such readings.

Indoor navigation and obstacle avoidance for unmanned aerial vehicles

Various embodiments enable a primary user to be identified and tracked using stereo association and multiple tracking algorithms. For example, a face detection algorithm can be run on each image captured by a respective camera independently. Stereo association can be performed to match faces between cameras. If the faces are matched and a primary user is determined, a face pair is created and used as the first data point in memory for initializing object tracking. Further, features of a user's face can be extracted and the change in position of these features between images can determine what tracking method will be used for that particular frame.

Primary user selection for head tracking

Object detection and tracking

Object identification through stereo association

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San Jose, CA, United States of America

Tianyang Ma