Autonomous Vehicle Route Locking for Device-Zone Navigation
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Solution Overview
Problem
Existing autonomous vehicle management systems in complex warehouse environments with multiple devices and heterogeneous robots face challenges in navigating through passageways without deadlocks or collisions, as they need to enter and exit device zones efficiently while managing locks and routes effectively.
Innovation Solution
A processor-implemented method and system for autonomous vehicles management that categorizes route plans into path segments, determines the type of path segments, and annotates nodes with preconditions such as hard or soft lock actions to ensure efficient navigation and collision-free routes, using a multi-robot route planner and device controller to manage locks and device access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a single autonomous vehicle uses a single rack for picking and dropping objects, then the system is simple to manage, but the system lacks scalability and efficiency when multiple devices and heterogeneous vehicles are introduced
Solution Approach 1:
The patent segments the operating environment into distinct device zones with defined boundaries and categorizes path segments into first path segments (inside device zones) and second path segments (outside device zones). This segmentation allows the system to manage multiple devices and heterogeneous vehicles by breaking down complex navigation into manageable segments with specific rules for each zone type.
Solution Approach 2:
The patent creates a universal route planning framework that handles multiple device types (mobile racks, vertical conveyors, sheet shutters, temporary spaces, charging stations) and heterogeneous autonomous vehicles through a common architecture. The system uses unified concepts like device zones, path segments, and lock actions that apply across all device-vehicle interactions, enabling scalable management without requiring device-specific or vehicle-specific planning logic.
2Adaptability or versatility
If multiple devices and heterogeneous autonomous vehicles operate in the same environment, then the system becomes more versatile and productive, but navigation becomes more complex and prone to deadlocks and collisions
Solution Approach 1:
The patent implements preliminary actions by annotating nodes with preconditions before navigation occurs. The system determines lock actions (soft locks and hard locks) and enters them into the route plan in advance, allowing the autonomous vehicle to acquire necessary permissions before reaching critical sections. This preliminary locking prevents deadlocks and collisions by ensuring proper coordination is established before vehicles enter device zones or interact with multiple devices.
Solution Approach 2:
The patent introduces lock actions (soft locks and hard locks) as intermediary mechanisms that mediate between multiple autonomous vehicles and devices. These lock actions serve as a coordination layer that manages access to device zones and critical sections, ensuring that vehicles navigate safely through complex environments with multiple devices without direct vehicle-to-vehicle conflict.
3Reliability
If the system implements comprehensive route planning with lock actions and path segmentation, then navigation safety improves, but the computational complexity and processing time increase
Solution Approach 1:
The patent segments routes into first path segments (inside device zones) and second path segments (outside device zones), allowing the system to apply different processing and lock strategies to different segments. This segmentation reduces computational complexity by focusing detailed lock management only where necessary (inside device zones) while using simpler approaches for external paths.
Solution Approach 2:
The patent applies different quality levels of lock management to different locations: hard locks are applied at critical nodes where devices are accessed, while soft locks are used for less critical sections. This local differentiation optimizes safety where needed while reducing unnecessary computational overhead in less critical areas, balancing reliability with processing efficiency.
Data Source
AI summary
The disclosure generally relates to method and system for autonomous vehicles management in an operating environment. The method may include sending a route plan in response to a request received by an autonomous vehicle from amongst a plurality of autonomous vehicles in an operating environment including one or more devices, wherein the one or more device comprises device or device space. The method may further include categorizing the route plan into path segments, the path segments including a first path segment including one or more nodes from the plurality of nodes being inside a device zone of the one or more devices and a second path segment including one or more nodes from the plurality of nodes being outside the device zone of the one or more devices. The method may further include determining a type of path segment from the categorized path segments for each of the node in the navigation segment and annotating the first node of the first path segment with a second precondition based on determination of a destination node from the one or more nodes and the second precondition includes performing a hard lock action of the first device for the autonomous vehicle traversing the first path segment to the destination node.