Learning Controller for Robotic Gesture Control
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Solution Overview
Problem
Existing home automation devices often require users to carry smartphones or tablets to operate robotic devices, and their user interfaces are constrained, necessitating programming and button assignments, which can be cumbersome and inconvenient.
Innovation Solution
A robotic system with a learning controller that receives wireless transmissions from sensors and determines context associations, allowing it to autonomously execute actions without continuous user input, using a combination of sensors, computing clouds, and universal controllers to transmit commands wirelessly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users operate robotic devices using existing home automation devices with constrained user interfaces, then control functionality is provided, but user convenience deteriorates due to the requirement to carry smartphones or tablets and perform programming
Solution Approach 1:
The learning controller automatically learns and stores associations between sensory contexts and control instructions through observation of user actions, eliminating the need for users to manually program device behaviors. The system serves itself by autonomously acquiring operational knowledge.
Solution Approach 2:
The learning controller acts as an intermediary between the user and the robotic device, translating observed user actions into automated context-action associations. This intermediary layer handles the complexity of programming internally while presenting a simple interface to users.
2Productivity
If existing home automation devices require programming and button assignments, then control functionality is achieved, but operation time increases due to the cumbersome setup process
Solution Approach 1:
The learning controller performs preliminary learning of context-action associations by observing user actions during normal operation. This preliminary action occurs in the background without requiring dedicated setup time, and the learned associations are ready for immediate use.
Solution Approach 2:
The learning process occurs continuously during normal device operation rather than requiring a separate programming phase. The system learns from ongoing user interactions, maintaining continuous useful action without interruption for setup.
3Adaptability or versatility
If robotic devices use traditional remote control methods, then basic control is provided, but adaptability deteriorates due to lack of context awareness
Solution Approach 1:
The learning controller uses sensory input from sensors to detect contextual information about the environment and user actions. This feedback loop enables the system to adapt its control instructions based on observed contexts, improving adaptability while preserving contextual information.
Solution Approach 2:
The learning controller integrates multiple sensor types and processes various sensory contexts to determine appropriate control instructions. This multi-functional approach enables the system to adapt to diverse situations and maintain contextual awareness across different operating conditions.
Data Source
AI summary
Computerized appliances may be operated by users remotely. 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.