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US 12,758,459 B2Granted
Artificial intelligence enabled rollator
OwnerHua Harry Liinventor
Life of this patent
Estimating the term…
Abstract
The present invention is a battery-powered, remote-controllable rollator with embedded computer systems and computer vision system. The present invention recognizes the user's face by using artificial intelligence technology, namely, the deep convolutional neural networks, and uses that information to localize the rollator's position in relation to the user. An artificial intelligence algorithm computes the motion path and drives the present invention to the user. The present invention can automatically stop once approached to a preset stopping distance from the user. Once stationary, the present invention can then be used by the user.
Claims20
A battery-powered, motorized rollator comprising:
- a rollator frame capable of being folded and collapsed as a whole for storage;
- a plurality of brushless direct current hub motors configured to drive a plurality of motorized wheels;
- a plurality of swivel wheels;
- a plurality of mechanical hand brakes;
- one front color camera;
- one rear color camera;
- a rechargeable battery comprising emergency safety features to prevent combustion or explosion upon impact or damage;
- an emergency battery power switch connected to the rechargeable battery;
- an instrument panel;
- a control module comprising an embedded computer;
- a plurality of software program modules executed by the embedded computer, the plurality of software program modules comprising a computer vision module, a deep learning module comprising deep convolutional neural networks, a path planning module, and a motor controller module;
- a magnetometer,
- an acceleration sensor;
- an impact detection sensor;
- and
- a plurality of laser-based proximity sensors;
- wherein the plurality of laser-based proximity sensors comprises a plurality of point LiDAR sensors;
- wherein the front color camera, the rear color camera, and the plurality of laser-based proximity sensors provide data to the deep learning module;
- wherein the deep learning module processes the data using deep convolutional neural networks to infer depth and absolute distance information for autonomous path planning;
- and
- wherein the embedded computer actuates the plurality of brushless direct current hub motors based on the autonomous path planning to self-drive the rollator.
18 more elements
A battery-powered, motorized rollator comprising:
- a rollator frame capable of being folded and collapsed as a whole for storage;
- a plurality of brushless direct current hub motors configured to drive a plurality of motorized wheels;
- a plurality of swivel wheels;
- a plurality of mechanical hand brakes;
- one front color camera;
- one rear color camera;
- a rechargeable battery comprising emergency safety features to prevent combustion or explosion upon impact or damage;
- an emergency battery power switch connected to the rechargeable battery;
- an instrument panel;
- a control module comprising an embedded computer;
- a plurality of software program modules executed by the embedded computer, the plurality of software program modules comprising a computer vision module, a deep learning module comprising deep convolutional neural networks, a path planning module, and a motor controller module;
- a magnetometer,
- an acceleration sensor;
- an impact detection sensor;
- and
- a plurality of laser-based proximity sensors;
- wherein the plurality of laser-based proximity sensors comprises a plurality of point LiDAR sensors;
- wherein the computer vision module performs image pre-processing on image data from the front color camera and the rear color camera and extracts a plurality of feature vectors for processing by the deep convolutional neural networks;
- wherein the deep convolutional neural networks process the plurality of feature vectors to perform facial recognition of a registered user and define a region of interest comprising a center location, a width parameter, and a height parameter corresponding to the registered user within an image frame;
- wherein the path planning module computes a motion path based on the center location, the width parameter, and the height parameter of the region of interest;
- and
- wherein the embedded computer actuates the plurality of brushless direct current hub motors according to the motion path to autonomously navigate the rollator towards the registered user.
19 more elements
A battery-powered, motorized rollator comprising:
- a rollator frame capable of being folded and collapsed as a whole for storage;
- a plurality of brushless direct current hub motors configured to drive a plurality of motorized wheels;
- a plurality of swivel wheels;
- a plurality of mechanical hand brakes;
- one front color camera;
- one rear color camera;
- a rechargeable battery comprising emergency safety features to prevent combustion or explosion upon impact or damage;
- an emergency battery power switch connected to the rechargeable battery;
- an instrument panel;
- a control module comprising an embedded computer;
- a plurality of software program modules executed by the embedded computer, the plurality of software program modules comprising a computer vision module, a deep learning module comprising deep convolutional neural networks, a path planning module, a motor controller module, and a smartphone interface module;
- a magnetometer;
- an acceleration sensor;
- an impact detection sensor;
- a plurality of laser-based proximity sensors;
- a WiFi module;
- and
- a Bluetooth module;
- wherein the plurality of laser-based proximity sensors comprises a plurality of point LiDAR sensors;
- wherein the WiFi module and the Bluetooth module are each configured to interface with a first smartphone application associated with a user device and a second smartphone application associated with a caregiver device;
- wherein the smartphone interface module is configured to arbitrate control of the rollator among an autonomous self-driving mode, a first manual control mode operated via the first smartphone application, and a second manual control mode operated via the second smartphone application;
- wherein the second smartphone application is authorized to manually control the motion path of the rollator upon receiving a permission signal from the first smartphone application;
- and
- wherein the embedded computer actuates the plurality of brushless direct current hub motors based on the active control mode to drive the rollator.
21 more elements
Dependencies are inferred from the claim text.