Robot Work Primitives and Percepts for Autonomous State Evaluation
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Solution Overview
Problem
Current robot systems require complex and elaborate tele-operation interfaces, limiting accessibility and autonomy, as they rely on sophisticated sensors and equipment that demand full pilot attention, making it difficult to evaluate state representations and control robot actions effectively.
Innovation Solution
A robot system comprising a processor, sensors, and a storage medium that executes instructions to access reusable work primitives and percepts, determining state representations and applying metrics to evaluate satisfaction, allowing for autonomous operation and transition towards goal states.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If complex tele-operation interfaces with sophisticated sensors and equipment are used, then robot control capability is improved, but system complexity and accessibility deteriorate
Solution Approach 1:
The patent segments the robot control system into modular components: reusable work primitives (basic actions), percepts (sensor data interpretations), and metrics (evaluation criteria). This segmentation allows complex robot operations to be broken down into manageable, evaluable units that can be independently developed and tested, reducing overall system complexity while maintaining control capability.
Solution Approach 2:
The patent introduces an evaluation framework as an intermediary layer between the robot controller and the tele-operation interface. This framework uses percepts to interpret sensor data and metrics to evaluate whether the robot's state representation satisfies task requirements, mediating between raw sensor data and control decisions to simplify the interface while preserving control capability.
2Measurement precision
If full pilot attention is required for tele-operation, then robot control precision is improved, but operator accessibility and ease of operation deteriorate
Solution Approach 1:
The patent implements a feedback mechanism where metrics continuously evaluate the robot's state representation against task requirements. This automated evaluation provides feedback to the system about whether control objectives are being met, reducing the need for constant pilot attention while maintaining control precision through objective, data-driven assessment.
Solution Approach 2:
The evaluation framework enables the robot system to self-assess its own state and performance through automated metric evaluation. The system independently determines whether its state representation satisfies task requirements, reducing the cognitive burden on operators and improving ease of operation while maintaining control precision through systematic evaluation.
3Measurement precision
If elaborate sensor equipment is used, then state representation accuracy is improved, but system complexity and cost deteriorate
Solution Approach 1:
The patent extracts and isolates the essential evaluation logic from the sensor system itself. Rather than relying on complex sensor hardware to provide all necessary information, the system extracts key state representations from sensor data and evaluates them separately using metrics. This separation allows simpler sensor equipment to be used while maintaining state representation accuracy through sophisticated evaluation.
Solution Approach 2:
The patent changes the parameters of evaluation from raw sensor data to processed state representations. By transforming complex sensor inputs into meaningful state descriptors and evaluating those using metrics, the system achieves accurate state assessment without requiring equally complex sensor hardware, effectively decoupling measurement precision from device complexity.
Data Source
AI summary
Robots, systems, methods, and computer program products for completing work objectives and evaluating states of robots are described. A robot accesses a library of reusable work primitives, each reusable work primitive corresponding to a respective basic sub-action that the robot is trained to autonomously perform. Each reusable work primitive is paired with an associated percept, which is used to evaluate a state representation of a robot to determine whether a desired outcome for the reusable work primitive is achieved.