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CASELAB Panacea Kit (CPKit)

Our AI and knowledge driven semantic solution makes your robot possible humanlike high-level navigation and manipulation for more efficient manufacturing and better service.

CPKit Core Functions

Semantic Analyzer

Analyze object data and produce its semantic descriptor.
Use cases : model learning, object recognition, etc.

Semantic Localizer

Localization of robot based on semantic understanding of environment.
Use cases : location based service, place recognition, path finding

Semantic Knowledge Description Language(SKDL)

Interpret and inject domain knowledge into semantic model of workspace.
Use cases : verbal or script expression of semantic-episodic domain knowledge for factory, home, office, and outdoors.

Semantic Modeler(SM)

Build the domain specific knowledge based semantic model of environment data from sensors including object, place, occupant, and robot.
Use cases : domain knowledge injected description of environment via image or point cloud data conversion.

Semantic Recognizer

Recognition of environment using semantic descriptor and deep learning.
Use cases : object recognition, place recognition, face recognition, scene understanding, etc.

Semantic Map Builder

Build 2D/3D semantic map by combining semantic model data and scanned odometer data
Use cases : semantic topology map, semantic metric map, semantic object map, etc.

Semantic Autonomous Navigator

Navigation with semantic map and robot sensor data. It includes the core functions of semantic map builder, semantic localizer and recognizer.
Use cases : factory automation robot, logistic robot, home-office service robot, field robot, aerial robot, underwater robot, etc

Semantic Autonomous Manipulator

Manipulation of object based on semantic modeling, analysis, and recognition
Use cases : automation of manufacturing tasks, logistics, delivery robot, product handling robot

Semantic Visual Servo

Semantic visual servo for tracking of object based on learned semantic model and recognition
Use cases : automation of object tracking for personal/public/field robot service and manufacturing.

Behavior Control Framework

Mission planning and execution based on behavior modeling and control of robot under semantic modeling and recognition framework
Use cases : mobile manipulator control, multiple robot control, leader-follower robots, mission execution for personal/public/field frobot service and manufacturing

CPK Training Methods

sensor model-segmentation-classification-detection
-sensor dependent scene grouping (ex. scene graph)-execution map booking-semantic descriptor gen-deep learning
Use cases: semantic DB, semantic map, execution map, perception, place recognition, scene understanding.

Comparison Table

Item Existing approaches CPKit solution
Level of intelligence Sensor data driven Semantic knowledge driven
Grid map Occupancy rectangle grid Semantic triangle –hexagonal grid
Modeling Appearance model Semantic ontological model
Sensor characteristic Sensor independent Sensor dependent
Localization Robot Location Robot Location & Object-place recognition



Business Registration Number : 371-81-01045

Suwon HQ : Corporate Collaboration Center 85761, Seobu-ro 2066, Jangan-gu, Suwon-si, Gyeonggi-do, Repulic of Korea
Kwangju BR : KITECH 2F 1228, Cheomdangwagi-ro 208beon-gil 6, Buk-gu, Gwangju, Repulic of Korea

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