
Technology Strengths of MOEBOTICS
Moebotics is a technology-centric company that invests 80% of the revenue into the development and innovation of autonomous service robot solutions. Backed by Gausium’s all-round strengths in robotics technologies, the Moebotics robots share the attributes of industry-leading navigation, cloud-based management and maintenance, user-friendly application and fully unmanned operation.

Technology Strengths of MOEBOTICS
Moebotics is a technology-centric company that invests 80% of the revenue into the development and innovation of autonomous service robot solutions. Backed by Gausium’s all-round strengths in robotics technologies, the Moebotics robots share the attributes of industry-leading navigation, cloud-based management and maintenance, user-friendly application and fully unmanned operation.
1. Industry-leading Navigation Algorithms

Mapping & Localization

Environmental Perception

Path Planning

Motion Control

Unlimited Mapping & Dynamic Localization
Upon initial deployment, Gausium robots will start navigate the landscape and create a semantic map of the site. No location tag, laptop connection or professional engineer is needed for mapping the site. Supported by high-precision LiDARs and cameras, Gausium robots offer industry-leading capability of mapping and localization, in terms of accuracy and robustness, and efficiency. In a dynamic environment, Gausium robots will locate themselves and update the map in real time.
. Precise localization (±2cm) using LiDAR
. Super-fast mapping : 30 minutes to map a 2,000m² site
. Unlimited mapping area up to 1,000,000m²
. Real-time map updates in dynamic environments


3D Perception with AI
Moebotics service robots can understand the surrounding environment with deep-learning-based perception algorithms. They constantly learn the landscape of an environment and make advanced behavior decisions. Trained with millions of real-world pictures, they can identify different types of obstacles and garbage with 99% accuracy, and make corresponding behavior decisions. For instance, when dealing with low obstacles, they would move around electric wires, but drive over speed bumps.Under the Auto Spot Cleaning mode, the robot will clean those it could clean, and send messages to operators via the App when encountering wastes that are too large for it to clean.

Flexible Path Planning
Path planning for cleaning robots is most challenging because the path should fully cover the operation area while adapting environmental changes and dynamic obstacles. Moebotics provides industry-leading planning algorithms with 5 modes: Teach & Follow, Sketch, Auto Cover, Real-time Auto Cover, and Auto Spot Cleaning. This provides users with the freedom to customize their cleaning plans. They can also divide an environment into smaller regions and select the most suitable path planning mode for each region according to the situation.
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Teach & Follow
Path planning for cleaning robots is most challenging because the path should fully cover the operation area while adapting environmental changes and dynamic obstacles. Moebotics provides industry-leading planning algorithms with 5 modes: Teach & Follow, Sketch, Auto Cover, Real-time Auto Cover, and Auto Spot Cleaning. This provides users with the freedom to customize their cleaning plans. They can also divide an environment into smaller regions and select the most suitable path planning mode for each region according to the situation.
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Real-time AutoCover
Backtracking spiral filling: Like Auto Cover, but the operator does not have to drive the robot for deployment. Instead, they draw a box on the map to specify the cleaning region and the robot will automatically clean all the passable areas inside the region in each operation.
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Auto Spot Cleaning
Auto point to point: The robot constantly scans the cleanliness of the nearby floor and automatically performs spot cleaning whenever detecting wastes or stains. By cleaning only where it is needed, it brings up to 4X efficiency improvement and significantly reduces water and power consumption.
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AutoCover
Fill-in mode: The operator manually drives the robot around the border of the area for cleaning, and then the robot will automatically generate a zigzag path to fully cover this area in the most efficient way.
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Sketch
Point to point: The operator draws a path by setting a bunch of waypoints on the map, and the robot will move along it.