Robotic end effector interface systems
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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 settings and failing to capture the variability and creativity of human chefs.
Innovation Solution
A robotic cooking system that uses multimodal sensing systems, including cameras, lasers, and human motion-capture technology, to record and replicate the precise movements and actions of a chef, allowing for real-time adjustments and quality control, enabling the preparation of dishes with identical taste and appearance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If pre-programmed trajectories are used for robotic systems, then automation and repeatability are improved, but adaptability and precision in complex tasks deteriorate
Solution Approach 1:
The robotic system transitions from static pre-programmed trajectories to dynamic motion capture that records real-time human movements. The system captures temporal variations, forces, and nuanced motions that adapt to task requirements, enabling the robot to replicate complex human skills with variability and creativity rather than rigid repetition.
Solution Approach 2:
The system changes multiple parameters simultaneously including position, velocity, acceleration, and applied forces during task execution. By capturing the full spectrum of motion parameters and their temporal relationships, the system preserves the subtleties of human performance that single-parameter control cannot capture, enabling faithful replication of complex tasks.
2Stability of the object's composition
If pre-programmed trajectories without deviation are used, then consistency is improved, but manufacturing precision and quality in complex tasks deteriorate
Solution Approach 1:
The motion capture system provides feedback about actual human performance variations, allowing the robotic system to learn and replicate not just average trajectories but also intentional deviations and corrections. This feedback loop captures the relationship between sensor data and task outcomes, enabling precision through understanding rather than rigid adherence to fixed paths.
Solution Approach 2:
The system performs preliminary motion capture and analysis to establish baseline trajectories, then uses this information to guide subsequent robotic execution with appropriate variations. By pre-capturing human expertise and intentional deviations, the system prepares a rich dataset that enables precise replication without requiring rigid adherence to single fixed trajectories.
3Ease of operation
If simple robotics systems are designed for consumer markets, then ease of operation is improved, but capability to perform complex tasks deteriorates
Solution Approach 1:
The system copies human motion patterns directly through motion capture technology, transferring human skills and capabilities to the robotic system. By recording and replicating human movements, forces, and temporal patterns, the robot gains access to complex task capabilities without requiring complex programming, making sophisticated systems accessible through simple human demonstration.
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.