Warehouse Transport Robot Navigation for Adaptive Route Automation
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Solution Overview
Problem
Existing automation solutions for unit load transport in intralogistics are hindered by high investment costs, increased space requirements, and limited flexibility, as they often require predefined transport routes and significant personnel intervention for commissioning and adaptation.
Innovation Solution
A transport robot system that includes a communication interface to receive environmental and capability models, allowing it to autonomously navigate and perform tasks within a warehouse by learning from manual operations and adapting to changes in the warehouse layout.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If automated guided vehicles (AGVs) are used for automation, then automation extent is improved, but adaptability deteriorates due to predefined transport routes requiring redesign for layout changes
Solution Approach 1:
The patent applies dynamics by implementing adaptive speed profiles that automatically adjust velocity parameters based on real-time environmental conditions and task requirements. The control unit dynamically modifies motion characteristics without requiring system redesign, enabling both automation and adaptability to changing warehouse layouts.
Solution Approach 2:
The system changes parameters by adjusting speed profiles, acceleration rates, and navigation parameters based on environmental models and capability models. These parameter modifications allow the AGV to adapt to different warehouse configurations while maintaining automated operation, resolving the contradiction between automation extent and adaptability.
2Productivity
If complex digital technologies are introduced for automation, then productivity is improved, but ease of operation deteriorates due to requirement for highly qualified employees
Solution Approach 1:
The control unit performs self-service by autonomously generating speed profiles and navigation paths based on environmental and capability models without requiring highly qualified personnel for each operation. The system self-adjusts parameters and makes decisions, improving ease of operation while maintaining high productivity through automated control.
Solution Approach 2:
The patent replaces manual operation with an automated control system that uses sensor-motor techniques and environmental modeling. This substitution eliminates the need for highly qualified employees to manually operate complex systems, thereby improving ease of operation while preserving productivity gains from automation.
3Adaptability or versatility
If autonomous mobile robots (AMRs) are deployed for flexibility, then adaptability is improved, but device complexity increases due to requirement for explicit deliberative capabilities
Solution Approach 1:
The patent segments the complex deliberative capabilities into modular components: environmental model generation, capability model integration, speed profile generation, and navigation control. This segmentation reduces device complexity by organizing functions into manageable modules while maintaining the flexibility and adaptability of autonomous operation.
Solution Approach 2:
The control unit serves multiple functions by integrating environmental modeling, capability assessment, path planning, and speed control in a single system. This multi-functionality reduces overall device complexity compared to having separate systems for each capability, while preserving the flexibility and adaptability of autonomous mobile robots.
Data Source
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Figure 3a~3b
AI summary
The invention relates to a transport robot (120a) which can be operated in an automated, semi-automated, and/or manual manner in order to carry out transport orders for transporting goods (140) in a warehouse having a plurality of transport robots (120a,b). The transport robot (120a) comprises a communication interface which is designed to receive an environmental model (200) of the warehouse and a capability model of the plurality of industrial trucks (120a,b) in the warehouse. The environmental model (200) defines a plurality of key locations (210a-c) of the warehouse and, for each key location, at least one neighboring key location. The capability model defines movement sequence information (220a-c) for each of the key locations (210a-c) of the environmental model, in particular at least one trajectory (220a-c), for an automated movement to the at least one neighboring key location.The transport robot (120a) comprises a control unit which is designed to carry out a transport order from a starting key point (210a) to a target key point (210c) of the plurality of key points (210a-c), to automatically control the movement of the transport robot (120a) on the basis of the environment model (200) and first movement sequence information (220a), in particular a first trajectory (220a), and at least second movement sequence information (220b), in particular at least a second trajectory (220b), of the capability model.