Who can build
+ robot application developers
+ robotics researchers
+ system integrators
+ automation builders
+ education providers
+ physical AI teams
Applications
Build Robot Applications
MINTROBOT platforms are designed as targets for robot applications.
Reference applications are examples, validation tools, and starting points. They demonstrate what can be built on top of MINTROBOT platforms while developers, researchers, integrators, educators, and partners build their own robot applications.
Reference applications
Reference Applications for Robot Instances
Reference applications demonstrate how component and compound robot platforms can support different robot instance directions. They are starting points for deployment paths based on the same architecture, with Librux as one supported path while ROS-based frameworks or custom software stacks can also be used to turn a reference application into a deployable robot instance.
What applications can use
+ manipulation capability
+ smart end-effector capability
+ perception and RGB-D input
+ IO and device configuration
+ real and virtual deployment configuration
+ compound platform coordination
Table-Top Manipulation Reference visual
Reference application
Table-Top Manipulation Reference
01 Best fit
What it demonstrates
Demonstrates how manipulation capability, end-effector control, and workspace deployment can be combined on a compatible platform.
Requires
+ manipulation capability+ end-effector or tool module+ optional camera / IO
Runs on
+ Pal Series+ Pal + Son configuration+ configured platform variants
Deployment config
+ workspace geometry+ tool configuration+ object positions+ camera location+ deployment configuration
Mobile Manipulator Tasks Reference visual
Reference application
Mobile Manipulator Tasks Reference
02 Mobility + Manipulation
What it demonstrates
Demonstrates how mobility, navigation, and manipulation can be combined when a compound robot platform must move through an environment and perform object-level tasks.
Requires
+ mobile base or carrier+ manipulation component+ vision or sensing resource+ workspace localization
Runs on
+ compound platform configurations+ Pal + Son with mobility+ partner mobile platforms
Deployment config
+ base pose or route+ manipulator reach+ sensor calibration+ task workspace+ deployment configuration
Education / AI Training Reference visual
Reference application
Education / AI Training Reference
03 Education / AI
What it demonstrates
Demonstrates how students and research teams can learn AI-integrated robotics through a real platform, embedded vision, SDR interfaces, simulation, and repeatable robot application workflows.
Requires
+ real robot platform+ SDR interface+ embedded vision+ digital twin simulation
Runs on
+ Pal Series+ Son Series+ education platform variants
Deployment config
+ curriculum setup+ safety boundary+ simulation asset+ data collection workflow+ SDK/runtime workflow
Robot instance reference
Service Automation Robot Instance Reference
This reference shows how a service automation robot instance can be formed by combining a platform foundation, application logic, and deployment binding. The focus is not broad SI work, but reducing unnecessary robot complexity and validating the robot instance before real operation.
Robot instance goal
01 Automate a compact service workflow without an over-specified industrial arm structure.
02 Align the robot instance with the real task, workspace, and commercial constraints.
Platform foundation
01 Defined a right-sized manipulation structure for the service workspace.
02 Removed unnecessary degrees of freedom and avoided a generic arm installation.
Application + deployment binding
01 Bound the barista workflow to the platform, controller, sensors, and kiosk environment.
02 Validated operating logic in simulation before connecting it to the real context.
Reference outcome
01 Reduced initial deployment cost to approximately one-fifth.
02 Reduced redesign loops and shortened the path to commercial operation.
Simulation
Real deployment
Robotic barista robot instance
Right-sized robot instance for service automation
Commercial service automation deployment in Daegu, South Korea.
The robot instance was configured around the required service task rather than using an over-specified general industrial robot. SDR-based simulation was used to validate application logic and deployment assumptions before build, reducing avoidable redesign work and improving the path to commercial operation.
Platform review
Need an application target for development?
Share the target application idea, platform assumptions, sensing resources, controller requirements, real environment, and simulation needs. MINTROBOT can help determine whether Pal, Son, or a compound platform foundation is the right target.
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