Facility Map Interface for Drag-and-Drop AMR Mission Planning
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Solution Overview
Problem
Existing autonomous mobile robot (AMR) technologies are insufficient in integrating robots safely and efficiently into fast-changing environments like warehouses due to the lack of real-time contextual information, requiring cumbersome navigation and deep background knowledge from human operators.
Innovation Solution
A system that enables real-time or near-real-time understanding of the facility environment by synthesizing sensor information into contextual, semantic, and instance maps, allowing a user interface to generate missions for robots to autonomously transport objects between source and destination areas through drag-and-drop gestures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a traditional menu-based interface is used for robot task assignment, then the system provides comprehensive control options, but the operator must navigate through cumbersome menus and select multiple parameters manually
Solution Approach 1:
The patent creates a visual copy of the facility layout on the user interface, allowing operators to interact with a graphical representation rather than text-based menus. Robots, tasks, and locations are represented as visual elements that can be directly manipulated through drag-and-drop gestures, eliminating the need to navigate through multiple menu layers and manually configure parameters.
Solution Approach 2:
The patent replaces the mechanical interaction of navigating through menu hierarchies with a gesture-based drag-and-drop mechanism. The operator simply drags a robot icon to a destination location on the map, and the system automatically infers the mission parameters, substituting complex mechanical navigation with an intuitive visual gesture.
2Reliability
If detailed contextual information about the facility is provided to the operator, then the operator can make informed decisions, but the interface becomes more complex and requires deeper background knowledge
Solution Approach 1:
The patent segments the facility information into distinct visual layers on the map interface, including static facility layout, dynamic robot positions, task locations, and navigation paths. This segmentation allows the operator to see only the relevant information for the current task without being overwhelmed by the complete system state, reducing perceived complexity while maintaining information accuracy.
Solution Approach 2:
The graphical map serves as an intermediary between the complex underlying system data and the operator. Instead of presenting raw sensor data, system states, or technical parameters directly to the operator, the system translates all this information into an intuitive visual representation where robots, locations, and tasks are depicted as simple graphical elements on a map.
3Manufacturing precision
If the system requires manual selection of robots, tasks, sub-tasks, and locations through menus, then the system ensures precise parameter selection, but the navigation process becomes cumbersome and time-consuming
Solution Approach 1:
The system performs automatic inference of mission parameters based on the drag-and-drop gesture. When the operator drags a robot to a location, the system automatically determines the source area, destination area, task type, and sub-tasks without requiring the operator to manually select each parameter. The system serves itself by inferring the missing information from the visual interaction context.
Solution Approach 2:
The system pre-configures the available robots and their capabilities in the background, so that when the operator performs a drag-and-drop gesture, the system has already prepared the possible mission configurations. This preliminary preparation allows the system to quickly generate accurate mission parameters without requiring the operator to go through lengthy selection processes.
Data Source
AI summary
A system and a method are disclosed that generate for display to a remote operator a user interface comprising a map, the map comprising visual representations of a source area, a plurality of candidate robots, and a plurality of candidate destination areas. The system receives, via the user interface, a selection of a visual representation of a candidate robot of the plurality of candidate robots, and detects a drag-and-drop gesture within the user interface of the visual representation of the candidate robot being dragged-and-dropped to a visual representation of a candidate destination area of the plurality of candidate destination areas. Responsive to detecting the drag-and-drop gesture, the system generates a mission, where the mission causes the candidate robot to autonomously transport an object from the source area to the candidate destination area.