Multi-Robot Instruction Framework for Diverse Test Environments
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Solution Overview
Problem
Current robotic systems lack an efficient method to operate multiple robots in diverse environments with varying hardware and software components, and environmental conditions, which limits their ability to generate robust and diverse data for training and operation.
Innovation Solution
A system that receives robot instructions and environmental parameters, configures the operating space of each robot based on these parameters, and stores data generated during operation, providing additional data for analysis and training, such as sensor data and updated machine learning models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple robots with different hardware and software components operate in diverse environments, then data diversity and robustness improve, but system complexity and coordination difficulty increase
Solution Approach 1:
The system segments robot operations into standardized instruction sets that can be independently executed by different robots. Each robot receives the same structured instructions but adapts them to its specific hardware capabilities and environmental context, allowing diverse data collection without requiring complex inter-robot coordination.
Solution Approach 2:
A universal instruction framework is implemented that can be applied across multiple robot types with different hardware and software configurations. The system uses standardized command structures and data formats that work universally across the robot fleet, enabling diverse robots to contribute to common training objectives without requiring custom integration for each robot type.
2Reliability
If robots operate in varied environmental conditions, then operational robustness improves, but control and measurement difficulty increase
Solution Approach 1:
Environmental parameters and conditions are pre-configured and documented before robot deployment. The system establishes baseline environmental specifications and prepares instruction sets that account for expected variations, allowing robots to adapt to diverse conditions without requiring real-time environmental control or complex sensing infrastructure.
Solution Approach 2:
The system explicitly models and accommodates environmental parameter variations in robot instructions. By incorporating environmental parameter specifications into the instruction sets and allowing robots to adapt their operations based on detected conditions, the system achieves operational robustness across diverse environments without requiring precise environmental control.
3Reliability
If standardized robot instructions are used across multiple robots, then instruction reliability improves, but adaptability to specific robot configurations decreases
Solution Approach 1:
The instruction system is designed to be dynamic rather than static. Standardized instruction templates include adaptive parameters that robots can modify based on their specific hardware configurations and capabilities. This allows the same core instruction set to reliably guide different robot types while maintaining the ability to adapt to specific configurations.
Solution Approach 2:
Different portions of the instruction set are assigned different levels of standardization. Core navigation and safety instructions maintain high standardization for reliability, while manipulation and interaction instructions allow greater local adaptation to specific robot end-effectors and hardware capabilities. This differentiated approach balances instruction reliability with configuration adaptability.
Data Source
AI summary
Methods and apparatus related to receiving a request that includes robot instructions and/or environmental parameters, operating each of a plurality of robots based on the robot instructions and/or in an environment configured based on the environmental parameters, and storing data generated by the robots during the operating. In some implementations, at least part of the stored data that is generated by the robots is provided in response to the request and/or additional data that is generated based on the stored data is provided in response to the request.