Shaped Detection Fields for Warehouse Vehicle Collision Avoidance
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Solution Overview
Problem
Vehicles operating in closed environments, such as warehouses, face challenges in detecting and avoiding collisions with other vehicles, personnel, and objects due to reduced visibility and inefficient object detection systems.
Innovation Solution
A system comprising sensors for detecting vehicle motion and steer angle, combined with a computing device that determines a shaped detection field, monitors for encroaching objects, and adjusts vehicle operation to avoid collisions, using UWB location technology and sensor fusion for precise positioning and vector tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If vision-based sensors are used to improve object detection, then visibility is improved, but the ability to detect and avoid many objects while maintaining operational efficiencies is insufficient
Solution Approach 1:
The detection field is dynamically shaped and adjusted based on real-time vehicle motion data, steer angle, and environmental context. The system continuously adapts the detection field geometry to match the vehicle's movement vector, expanding coverage in directions of motion while reducing coverage in areas of low risk, thereby maintaining high detection accuracy without sacrificing operational speed
Solution Approach 2:
The system performs preliminary detection and risk assessment by analyzing vehicle trajectory, steer angle, and environmental data before collisions occur. By predicting potential collision zones in advance and pre-adjusting the detection field, the system enables proactive collision avoidance while maintaining smooth vehicle operation and productivity
2Productivity
If heavy vehicles with reduced visibility are used to maneuver tight spaces, then productivity is improved, but collision detection capability deteriorates
Solution Approach 1:
The system introduces an intermediary computing device that processes sensor data and generates shaped detection fields, acting as a mediator between the vehicle's motion capabilities and collision detection requirements. This intermediary layer synthesizes multiple sensor inputs (motion sensors, steer angle sensors, vision sensors) to create a comprehensive detection model that compensates for the vehicle's inherent visibility limitations
Solution Approach 2:
The system transitions from traditional 2D sensor-based detection to a 3D shaped detection field that incorporates spatial depth, vehicle trajectory, and temporal prediction. By adding the dimension of predictive trajectory analysis based on steer angle and motion vectors, the system detects potential collision zones before the vehicle physically reaches them, overcoming the limited field of view of heavy vehicles
3Reliability
If a comprehensive detection field is implemented to improve collision avoidance, then safety is improved, but computational complexity and processing requirements increase
Solution Approach 1:
The detection field is segmented into multiple zones based on risk probability, with different detection thresholds and processing priorities for each zone. High-risk areas along the vehicle's movement vector receive intensive monitoring, while low-risk peripheral areas use reduced monitoring, dividing the computational task into manageable segments that maintain high reliability where needed while reducing overall complexity
Solution Approach 2:
The system dynamically changes detection parameters such as field of view angle, detection range, and processing frequency based on vehicle speed, steer angle, and environmental context. By adjusting these parameters in real-time, the system maintains high collision avoidance reliability during critical maneuvers while reducing computational load during steady-state operation, optimizing the balance between safety and complexity
Data Source
AI summary
Embodiments provided herein include systems and methods for location-based field shaping. One embodiment of a system includes a materials handling vehicle and a computing device that are configured to receive location data via at least one of the plurality of transceiver anchors, receive sensor data from at least one sensor related to the characteristic of operation of the materials handling vehicle, and determine a first location of the materials handling vehicle in the covered environment. Some embodiments may be configured to determine a vector of movement of the materials handling vehicle, determine a shaped detection field for the materials handling vehicle from the vector of movement, and detect an object that encroaches on the shaped detection field. Some embodiments may be configured to send information to the materials handling vehicle to alter operation of the materials handling vehicle to reduce a likelihood of collision with the object.