Distributed Robot Anomaly Detection for Sensor and Environment Drift
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Autonomous robots face challenges in accurately navigating and performing tasks due to deviations in sensors, actuators, and environmental elements, leading to misalignment and errors, which can be difficult to troubleshoot as they may result from internal malfunctions or changes in the environment.
Innovation Solution
A distributed set of robots is used to autonomously detect and differentiate between individualized anomalies affecting specific robots and environmental anomalies affecting multiple robots, allowing for self-correction of sensors and actuators or adjustment of environment elements to maintain accurate operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a robot operates autonomously using calibrated sensors and actuators, then it can perform tasks with expected precision, but deviations in sensors or actuators over time cause misalignment and errors
Solution Approach 1:
The system performs preliminary anomaly detection by comparing expected kinematics (based on calibrated sensors and actuators) with actual kinematics before tasks are significantly impacted. This allows the robot to identify deviations in sensors or actuators early and correct them proactively, maintaining positioning precision and operational reliability
Solution Approach 2:
The system continuously monitors the relationship between sensor inputs, actuator outputs, and actual robot kinematics. By comparing expected versus actual kinematic behavior, the system provides feedback that enables real-time detection of sensor or actuator deviations and triggers corrective actions to maintain operational reliability and positioning accuracy
2Ease of operation
If the robot relies on environment elements as reference points, then it can navigate and perform tasks accurately, but changes in environment elements cause errors that are difficult to distinguish from internal malfunctions
Solution Approach 1:
The system segments anomaly detection into two distinct categories: individualized anomalies (affecting only one robot) and environmental anomalies (affecting multiple robots). By analyzing whether detected kinematic deviations are consistent across multiple robots, the system can identify whether the error source is internal to a specific robot or external in the environment, making error source identification straightforward
Solution Approach 2:
The system uses other robots as intermediary reference points for error detection. By comparing its own kinematic deviations with those of other robots operating in the same environment, a robot can determine whether deviations are caused by environmental changes (if other robots show similar deviations) or internal malfunctions (if only this robot shows deviations), thereby simplifying error source identification
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.