Distributed Robot Anomaly Detection Using Expected vs Actual Kinematics
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Autonomous robots face errors due to deviations in sensors, actuators, and environment elements, leading to misalignment and cascade of errors, making it difficult to determine whether the issue is internal or environmental, affecting their movement and operation accuracy.
Innovation Solution
A distributed set of robots autonomously detects and differentiates between individualized anomalies and environmental anomalies by tracking expected and actual kinematics, allowing self-correction of sensors and actuators or adjustment of environment elements to maintain operation accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If robots rely on calibrated sensors and actuators for movement control, then operation accuracy is maintained, but deviations in sensors or actuators cause misalignment and cascade of errors
Solution Approach 1:
The system continuously monitors actual kinematics of robots and compares them with expected kinematics to detect deviations. This feedback mechanism allows the system to identify when sensors or actuators drift from calibration, enabling corrective actions to maintain operation reliability despite component deviations.
Solution Approach 2:
The system performs self-diagnosis by autonomously detecting whether deviations originate from individual robot components (sensors/actuators) or environmental factors. This self-service capability eliminates the need for external troubleshooting and enables automatic correction or compensation strategies.
2Productivity
If robots operate autonomously without human intervention, then productivity increases, but it becomes difficult to determine the source of errors (internal vs environmental)
Solution Approach 1:
The autonomous system performs self-diagnosis by comparing deviation patterns across multiple robots. When multiple robots exhibit similar deviations, the system identifies environmental causes; when only one robot is affected, it identifies internal component issues. This self-service error source identification maintains high automation efficiency.
Solution Approach 2:
The system segments error sources into two distinct categories: individual robot anomalies (internal to sensors/actuators) and environmental anomalies (affecting multiple robots). This segmentation enables targeted troubleshooting and correction strategies while maintaining autonomous operation.
3Adaptability or versatility
If environment elements are used as reference points for robot navigation, then operation flexibility is improved, but changes in environment elements cause errors and misalignment
Solution Approach 1:
The system uses feedback from actual robot positioning data to detect when environment reference points have shifted. By comparing expected positions (based on calibrated coordinates) with actual positions, the system identifies environmental changes and can either correct the reference data or adjust robot navigation to maintain positioning accuracy.
Data Source
AI summary
Provided are robots that autonomously detect and correct individualized anomalies resulting from deviations in the sensors and/or actuators of individual robots, and environmental anomalies resulting from deviations in the environment elements that the robots rely on or use in the execution of different tasks. To do so, a robot may receive a task, may determine expected kinematics that include expected activations of a set of sensors and actuators by which the robot executes the task, may activate the set of sensors and actuators according to the expected kinematics, may track the actual kinematics resulting from activating the set of sensors and actuators according to the expected kinematics and continuing the activations until detecting one or more environment elements signaling completion of the task, and may adjust one or more sensors, actuators, or environment elements in response to the actual kinematics deviating from the expected kinematics.