Methods and systems for food preparation in a robotic cooking kitchen
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Solution Overview
Problem
Current robotic systems lack the capability to replicate complex culinary tasks with the precision and variability of human chefs, limiting their application in home and consumer markets, as they primarily rely on pre-programmed trajectories without adaptation or deviation.
Innovation Solution
A robotic cooking system equipped with multimodal sensing systems, including cameras, lasers, and human-motion capture technology, records and replicates the precise movements of a chef, allowing for real-time adjustments and quality control of dishes based on sensory data, such as temperature and taste, using robotic arms and hands to prepare gourmet meals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If pre-programmed trajectories are used for robotic cooking, then automation is achieved, but precision and adaptability of culinary tasks are insufficient
Solution Approach 1:
The system employs multiple sensors (cameras, lasers, motion capture) to continuously monitor the cooking process and provide real-time feedback to the control system, enabling dynamic adjustments to trajectory and technique execution, thus achieving both automation and precision
Solution Approach 2:
The robotic system transitions from static pre-programmed trajectories to dynamic adaptive trajectories that can be modified in real-time based on sensory feedback, allowing the robot to adapt its movements and cooking techniques during the cooking process
2Extent of automation
If pre-programmed trajectories are used for robotic cooking, then automation is achieved, but variability and adaptability of human chef techniques are lost
Solution Approach 1:
Real-time sensory feedback from cameras, lasers, and motion capture systems enables the robotic system to detect variations in cooking conditions and adapt its techniques accordingly, replicating the variability and adaptability of human chefs
Solution Approach 2:
The system records and analyzes human chef techniques, then uses this data to enable the robot to autonomously adapt and replicate diverse culinary techniques across different cooking tasks, achieving versatility without constant human intervention
3Manufacturing precision
If multimodal sensing systems are added to capture chef movements, then precision of replication is improved, but device complexity increases
Solution Approach 1:
The sensing system is divided into separate functional modules (cameras for visual tracking, lasers for spatial mapping, motion capture for movement analysis), each handling a specific aspect of chef technique capture, making the complex system more manageable and maintainable
Solution Approach 2:
The multimodal sensing system serves multiple functions: capturing chef movements, monitoring cooking conditions, and providing feedback for trajectory adjustment, thereby justifying the increased complexity through enhanced precision and versatility
Data Source
AI summary
The present disclosure is directed to methods, computer program products, and computer systems for instructing a robot to prepare a food dish by replacing the human chef's movements and actions. Monitoring a human chef is carried out in an instrumented application-specific setting, a standardized robotic kitchen in this instance, and involves using sensors and computers to watch, monitor, record and interpret the motions and actions of the human chef, in order to develop a robot-executable set of commands robust to variations and changes in the environment, capable of allowing a robotic or automated system in a robotic kitchen to prepare the same dish to the standards and quality as the dish prepared by the human chef.