Learning Controller Gesture Recognition for Home Automation
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Solution Overview
Problem
Existing home automation devices often require users to carry smartphones or tablets to operate robotic devices, and they may need programming or button assignment, which can be cumbersome and limit the user interface to a constrained form, especially for complex operations or simultaneous control of multiple devices.
Innovation Solution
A robotic system with a learning controller that associates user gestures or commands with contextual data, allowing for the automation of control instructions without the need for continuous user input, using a combination of sensory inputs and machine learning algorithms to determine appropriate actions based on context, enabling more intuitive and efficient operation of home automation devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users manually program or assign buttons for controlling robotic devices, then the device can perform desired functionality, but the operation becomes cumbersome and the user interface is constrained
Solution Approach 1:
The learning controller automatically observes and learns the association between user gestures and remote control commands without requiring manual programming. The system serves itself by autonomously building the control mapping through observation, eliminating the need for users to perform complex programming tasks while maintaining full functionality.
Solution Approach 2:
The learning controller performs preliminary learning during a training phase before actual operation. By pre-establishing the gesture-command associations through observation during this initial phase, the system prepares the control mapping in advance, so that during normal operation users can simply perform gestures without any programming or button assignment.
2Ease of operation
If users carry smartphones or tablets to operate robotic devices, then control functionality is available, but user convenience is reduced and simultaneous control of multiple devices is limited
Solution Approach 1:
The system replaces the mechanical interaction of carrying and operating a smartphone or tablet with a gesture-based control system. Users perform natural hand gestures that are observed by the learning controller, substituting the need for physical devices and their constrained interfaces with intuitive bodily movements.
Solution Approach 2:
The learning controller is designed to learn and manage associations for multiple remote control commands and multiple robotic devices simultaneously. A single learning controller can observe and learn gestures for controlling different devices, providing universal control capability without requiring separate control interfaces for each device.
3Extent of automation
If the learning controller observes and learns associations between gestures and commands, then automation is achieved, but the system must accurately distinguish between intentional commands and unintentional gestures
Solution Approach 1:
The learning controller incorporates feedback mechanisms where users can provide correction signals when the system misinterprets a gesture or when an unintentional gesture is detected. This feedback allows the system to refine its learning and improve accuracy over time, distinguishing between intentional commands and unintentional movements through continuous adjustment based on user responses.
Data Source
AI summary
Computerized appliances may be operated by users remotely. In one implementation, a learning controller apparatus may be operated to determine association between a user indication and an action by the appliance. The user indications, e.g., gestures, posture changes, audio signals may trigger an event associated with the controller. The event may be linked to a plurality of instructions configured to communicate a command to the appliance. The learning apparatus may receive sensory input conveying information about robot's state and environment (context). The sensory input may be used to determine the user indications. During operation, upon determine the indication using sensory input, the controller may cause execution of the respective instructions in order to trigger action by the appliance. Device animation methodology may enable users to operate computerized appliances using gestures, voice commands, posture changes, and/or other customized control elements.