Robotic kitchen systems and methods in an instrumented environment with electronic cooking libraries
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Solution Overview
Problem
Current robotic systems lack the ability to replicate complex human tasks, such as cooking, with precision and adaptability, as they rely on pre-programmed trajectories without deviation, limiting their application in home-consumer spaces and failing to emulate the variability and skill of human chefs.
Innovation Solution
A robotic cooking system that uses multimodal sensing systems and electronic minimanipulation libraries to replicate the precise movements and techniques of a chef, allowing for real-time adjustments and quality checking of food dishes, enabling the preparation of diverse cuisines and personalized meals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If pre-programmed trajectories are used for robotic systems, then automation is achieved, but adaptability and precision in replicating complex human tasks deteriorate
Solution Approach 1:
The system incorporates multimodal sensing systems that continuously monitor the robotic system's performance and the cooking process, providing real-time feedback to adjust trajectories and parameters. This enables the robotic system to adapt to variations in ingredients, equipment, and environmental conditions while maintaining automated operation.
Solution Approach 2:
The patent transforms static pre-programmed trajectories into dynamic, adaptive motion paths. The robotic system uses electronic minimanipulation libraries that can be modified in real-time based on sensor data, allowing the system to adjust its movements dynamically to replicate human chef techniques with greater fidelity and adaptability.
2Stability of the object's composition
If pre-programmed trajectories without deviation are used, then consistency is achieved, but manufacturing precision and quality deteriorate
Solution Approach 1:
Real-time sensing and feedback mechanisms monitor critical parameters such as temperature, timing, and ingredient placement. The system automatically adjusts trajectories and operational parameters to maintain precision while ensuring consistent results across multiple cooking cycles.
Solution Approach 2:
The system dynamically modifies operational parameters including speed, position, force, and timing based on sensor feedback. This allows the robotic system to maintain high precision in replicating human techniques while adapting to variations in the cooking process to ensure consistent quality outcomes.
3Ease of operation
If simple robotics systems are designed for consumer markets, then ease of operation is improved, but capability to replicate complex human tasks deteriorates
Solution Approach 1:
The system uses electronic minimanipulation libraries that capture and store the precise movements, techniques, and procedures of human chefs. These digital copies of human expertise can be executed by the robotic system with high fidelity, enabling complex task replication without requiring complex programming interfaces for end users.
Solution Approach 2:
The robotic system is designed with multi-functional capabilities to perform various cooking tasks using a unified platform. The electronic minimanipulation libraries provide a universal interface that can represent different cooking techniques and recipes, allowing the system to handle diverse culinary tasks while maintaining ease of operation through standardized controls.
4Extent of automation
If robotic systems fail to emulate human variability and skill, then automation is achieved, but adaptability to different cuisines and techniques deteriorates
Solution Approach 1:
Multimodal sensing systems monitor the robotic system's actions and compare them against reference data from human chefs. This feedback loop enables the system to learn and emulate human variability and skill, adjusting its behavior to match different cooking styles and techniques while maintaining automated operation.
Solution Approach 2:
The system transforms static automation into dynamic emulation by using adaptable trajectories and parameters that can be modified in real-time. The electronic minimanipulation libraries are designed to capture the nuances of human performance, allowing the robotic system to emulate human variability and skill across different cuisines and cooking techniques.
Data Source
AI summary
Embodiments of the present disclosure are directed to methods, computer program products, and computer systems of a robotic apparatus with robotic instructions replicating a food preparation recipe. In one embodiment, a robotic control platform, comprises one or more sensors; a mechanical robotic structure including one or more end effectors, and one or more robotic arms; an electronic library database of minimanipulations; a robotic planning module configured for real-time planning and adjustment based at least in part on the sensor data received from the one or more sensors in an electronic multi-stage process file, the electronic multi-stage process recipe file including a sequence of minimanipulations and associated timing data; a robotic interpreter module configured for reading the minimanipulation steps from the minimanipulation library and converting to a machine code; and a robotic execution module configured for executing the minimanipulation steps by the robotic platform to accomplish a functional result.