Q1
Quadruped inspection robot
A four-legged platform being developed for mine inspection, combining cameras, LiDAR and inertial sensing with research in autonomous navigation.
Explore Q1
Autonomous robots for mining
Developing navigation, perception and digital twins for underground inspection.
Q1 application concept · Robot in development
01 Robot platforms
Different platforms. A shared focus on inspection.
T1
Tracked inspection robot
Built around a general-purpose tracked chassis, T1 explores terrain adaptation and environmental sensing for mine inspection.
Explore T1
W1
Wheeled inspection robot
A wheeled platform being developed for autonomous navigation and environmental sensing, with site conditions guiding the configuration.
Explore W1
MDA1
Mobile dual-arm robot
A mobile dual-arm platform under development for coordinated navigation, grasping and manipulation.
Explore MDA1
Platform selection
Choose a platform for your task
These are development and configuration directions. Suitability depends on whole-robot testing, site conditions and access requirements.
Q1 · Quadruped
Research into mobility over uneven mine passages and obstacles.
Assess slopes, obstacles, power and task payload.T1 · Tracked
Site adaptation and inspection integration on a tracked platform.
Assess ground traction, passage widths and turning space.W1 · Wheeled
Fixed routes and inspection points in relatively level areas.
Assess surface continuity, routes and observation points.MDA1 · Dual-arm
Grasping and coordinated manipulation after base positioning.
Assess workpieces, end effectors and safe working space.02 Software · OmindOS
Bring OmindOS to your robot.
Connect navigation, manipulation and digital twins. Explore the system in OmindOS Cloud and plan the integration for your platform.
Maps & digital twins
Organize environment maps, robot locations and inspection points.
Tasks & workflows
Connect routes and actions in a defined task sequence.
Data & feedback
Review robot status, task progress and execution records.
Interfaces & integration
Adapt hardware and software, then validate the deployment.
03 About OriginMind
Grounded in field research.
Field experience and laboratory research guide how we develop robots.
From research to robot systems
OriginMind works with ARTS Robotics at Shenzhen Technology University on autonomous navigation, manipulation and embodied intelligence.
The research spans multisensor mapping and localization, motion control, tactile sensing, planning and dual-arm coordination. Algorithms are evaluated through robot experiments and system integration.
The team’s mining inspection robot system received First Prize in the AI+ application track of the 19th Challenge Cup National College Student Academic and Technological Works Competition.
Field records
Link each task to its evidence
These recordings show earlier platforms and underground data capture that inform our development. Current Q1 demonstrations show its design and simulated motion.
Underground driving
- Task
- Record platform movement along a mine passage.
- Available evidence
- Field footage shows the ground, passage and platform in motion.
- Next validation priorities
- Assess route access, communications and continuous task execution on the intended route.
Mapping data capture
- Task
- Collect underground environmental data for localization and mapping research.
- Available evidence
- The recording documents field data capture as a reference for environment modeling.
- Next validation priorities
- Assess localization continuity, map quality and repeated arrival at inspection points along a consistent route.
Tell us about your application.
Start with the task, site conditions and robot platform.