Ceiling-Facing Camera Localization for Mobile Automation
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Solution Overview
Problem
Mobile automation apparatuses in retail environments face challenges with inaccurate navigation due to changes in the environment, such as obstacles or structural changes, which affect the reliability of near-ground planar lidar systems.
Innovation Solution
A mobile automation apparatus equipped with a ceiling-facing image device, proprioceptive sensors, and a controller that associates images with movement data to navigate and map the environment, using a combination of cameras, depth sensors, and proprioceptive data to determine its position and generate accurate maps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If near-ground planar lidar is used for localization and mapping, then navigation capability is provided, but accuracy deteriorates when environmental changes occur
Solution Approach 1:
The patent transitions from using near-ground planar lidar (2D ground-level sensing) to ceiling-facing image devices (3D overhead sensing). This dimensional change allows the system to map and localize using ceiling features that remain stable even when ground-level obstacles or structures change position, thereby maintaining localization precision despite environmental modifications.
Solution Approach 2:
The patent introduces ceiling features as an intermediary reference framework. Instead of relying directly on ground-level obstacles for localization, the system uses ceiling features as stable intermediaries to establish a consistent reference frame, which then enables accurate localization even when ground conditions change.
2Measurement precision
If multiple sensors and modalities are integrated for localization and mapping, then accuracy and adaptability improve, but device complexity increases
Solution Approach 1:
The patent employs ceiling-facing image devices that serve multiple functions: they capture images for mapping, provide localization data, and enable recognition of environmental features. This multi-functionality reduces the need for separate dedicated sensors for each task, thereby managing system complexity while maintaining high precision.
Solution Approach 2:
The patent combines multiple data modalities (images from ceiling-facing cameras, depth information, and proprioceptive sensor data) into a unified localization and mapping system. By merging these data sources at the processing level, the system achieves improved accuracy without proportionally increasing hardware complexity.
Data Source
AI summary
A device and method for multimodal localization and mapping for a mobile automation apparatus is provided. Features are extracted from images acquired by a ceiling-facing image device of the mobile automation apparatus in an environment, and stored in association with estimated positions of the mobile automation apparatus in the environment as determined from one or more sensors, as well as in association with features extracted from depth data acquired from a depth-sensing device, for example as map data. The map data is later used by the mobile automation apparatus to navigate the environment based, at least in part, on further images acquired by the ceiling-facing image device.