Autonomous Mobile Collision Detection Using IMU and Acoustic Sensing
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Solution Overview
Problem
Traditional collision detection systems for autonomous mobile devices (AMDs) are costly and unreliable, often failing to accurately detect collisions due to their mechanical complexity and inability to sense collisions without bumper switches, leading to improper stoppages or slowdowns during task execution.
Innovation Solution
The use of inertial measurement units (IMUs) and microphones on AMDs to detect collisions by analyzing changes in motion and audio data, determining shock events and acoustic signatures associated with collisions, and characterizing collision types based on motion and audio profiles, without the need for additional hardware.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If bumper switches are used for collision detection, then collision detection capability is provided, but device complexity and cost increase
Solution Approach 1:
The patent replaces mechanical bumper switches with an acoustic field-based detection system using microphones and signal processing algorithms. The collision detection is achieved by analyzing acoustic emissions and vibrations generated during impact events, substituting mechanical contact sensors with acoustic sensing and computational analysis.
Solution Approach 2:
The patent introduces acoustic emissions and vibrations as intermediary physical phenomena that mediate between the collision event and the detection system. Instead of direct mechanical contact, the collision generates acoustic signals that are captured by microphones and processed to infer collision occurrence, using the acoustic field as an intermediary carrier of collision information.
2Reliability
If bumper switches are used for collision detection, then collision detection is possible, but measurement precision deteriorates
Solution Approach 1:
The patent segments the collision detection task into multiple independent acoustic analysis channels, including impact sound detection, vibration analysis, and acoustic emission monitoring. By dividing the detection problem into separate acoustic features that can be independently analyzed and combined, the system achieves more precise and reliable collision detection without mechanical complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables quick and accurate collision detection, reducing false positives and allowing the AMD to react swiftly, improving safety and usability by differentiating between various collision types and responding appropriately.
Implementation Method 1
sensors on the autonomous mobile device may include an inertial measurement unit (IMU) that provides information about motion of the autonomous mobile device
Implementation Method 2
The microphone may comprise a single microphone or an array, that provides information about the ambient environment as well as sounds transferred through the structure of the autonomous mobile device
Data Source
AI summary
An autonomous mobile device (AMD) moves through a physical space without human intervention. Data from sensors on the AMD is used to determine if the AMD has collided with an obstacle. In one implementation the sensors may include a microphone. A collision may produce in the structure of the AMD a characteristic sound that is detected by the microphone and recognized as indicative of a collision. In another implementation information about velocity of the AMD and output from an inertial measurement unit (IMU) may be used to determine a characteristic change in motion that is indicative of a collision. Data from the microphone and the IMU may be combined to improve the reliability of collision detection.