Adaptive Perimeter Intrusion Detection for Cornering Robots
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Solution Overview
Problem
Mobile automation apparatuses face navigation challenges in environments with obstacles like corners and dead ends due to their fixed perimeter intrusion detection systems, which can lead to unnecessary emergency stops and hinder continuous operation.
Innovation Solution
The apparatus dynamically alters its perimeter intrusion detection by selecting and applying different control parameters based on navigational data, allowing it to modify its monitoring perimeter to avoid false intrusions and enable smoother navigation through complex spaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a fixed perimeter intrusion detection system is used, then the apparatus can detect obstacles reliably, but it causes unnecessary emergency stops when navigating through corners and dead ends
Solution Approach 1:
The perimeter intrusion detection system transitions from a fixed configuration to a dynamic one by adjusting control parameters based on navigational context. The system modifies the perimeter size and sensitivity levels according to the apparatus's current maneuver state, allowing it to adapt between high-sensitivity obstacle detection during normal navigation and reduced sensitivity during complex maneuvers like cornering or navigating dead ends.
Solution Approach 2:
The system changes operational parameters of the perimeter intrusion detection based on navigational data. Control parameters such as perimeter radius, detection sensitivity, and threshold values are dynamically adjusted according to the type of maneuver being performed, enabling the system to distinguish between legitimate obstacles and environmental features encountered during navigation.
2Loss of time
If the perimeter intrusion detector uses a large monitoring perimeter, then it can detect obstacles early, but it causes false intrusions during maneuvers like rotating in place
Solution Approach 1:
The monitoring perimeter dynamically adjusts its size and shape based on the apparatus's maneuver state. During normal forward navigation, a larger perimeter provides early obstacle detection. During rotating maneuvers or when navigating tight spaces, the perimeter automatically reduces in size to prevent false intrusions from environmental features that are not actual obstacles.
Solution Approach 2:
Control parameters defining the perimeter geometry and detection thresholds are modified based on navigational context. The system uses navigational data to determine appropriate perimeter parameters, changing them in real-time to match the current maneuver requirements and minimize false detections while maintaining early obstacle warning capability.
3Productivity
If the apparatus uses adaptive perimeter control, then it can navigate smoothly through complex spaces, but it requires processing navigational data to determine maneuver types
Solution Approach 1:
The existing navigational data processing system, already used for path planning and obstacle avoidance, is extended to also control the perimeter intrusion detection parameters. This multi-functional use of the navigation system eliminates the need for separate complex control logic, as the same sensors and processors that guide the apparatus also dynamically adjust the detection perimeter based on maneuver type.
Solution Approach 2:
The perimeter control system is merged with the navigational data processing system. By combining these functions, the apparatus uses a unified control architecture where navigational state determination serves both navigation and perimeter detection purposes, reducing overall system complexity while enabling adaptive perimeter control.
Data Source
AI summary
A method includes: selecting first control parameters for a perimeter intrusion detector of a mobile automation apparatus; controlling the perimeter intrusion detector according to the first control parameters, to monitor a first perimeter surrounding the mobile automation apparatus; determining that navigational data of the mobile automation apparatus defines a maneuver satisfying perimeter modification criteria; in response to determining that a likelihood of intrusion of the first perimeter associated with the maneuver exceeds a threshold, selecting second control parameters for the perimeter intrusion detector; modifying the first perimeter to a second perimeter according to the second control parameters; and controlling the perimeter intrusion detector to monitor the second perimeter.