Autonomous Vehicles/UAV_Engineering-SHANGHAI CHINGMU VISION TECHNOLOGY CO., LTD

Business pain points

Insufficient ground-truth accuracy makes algorithm validation unreliable.

Multi-target tracking becomes unstable in dense or high-speed scenarios.

Systems often lose stability outside controlled laboratory environments.

Platform changes require repeated integration and redevelopment.

Our advantages

Sub-millimeter ground truth supports reliable algorithm validation.

Synchronized tracking of hundreds of targets enables large-scale swarm research.

Millisecond-level feedback makes parameter tuning visible in real time.

Air-ground-water support ensures stable operation across complex environments.

Open APIs and SDKs enable seamless integration with ROS and simulation platforms.

lntroduce The Plan

CHINGMU Unmanned Systems Solution provides high-precision ground-truth tracking and real-time verification for drones, UGVs, robotic dogs, USVs, ROVs, AUVs, and other intelligent agents.

With real-time 6DoF pose and trajectory data, the system supports swarm control, SLAM validation, path planning, dynamic obstacle avoidance, and air-ground-water collaborative research.

Data acquisition

Product components

Flagship Camera: K Series

High-end optical mocap cameras built for demanding precision tracking.

Software

CMTracker provides real-time spatial tracking, visualization, and data output for UAVs, vehicles, rigid bodies, and engineering experiments.

Other Camera: MC Series

Flexible optical mocap cameras for large-space, high-precision tracking across diverse production setups.

Advantages of the plan

Provides sub-millimeter positioning accuracy and full-space optical coverage, delivering reliable ground truth for SLAM, path planning, trajectory control, and algorithm validation in high-speed, complex-motion scenarios.Provides sub-millimeter positioning accuracy and full-space optical coverage, delivering reliable ground truth for SLAM, path planning, trajectory control, and algorithm validation in high-speed, complex-motion scenarios.

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Large-Scale Swarm TrackingSupports large-area capture and real-time 6DoF tracking of hundreds of rigid bodies, enabling drone swarms, multi-robot collaboration, and air-ground cooperative experiments.

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Real-Time Control Strategy VerificationReal-time trajectory and pose feedback help researchers validate dynamic obstacle avoidance, path planning, and control strategies, making UAV and vehicle testing more accurate and efficient.

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Ultra-Low Latency FeedbackHigh sampling frequency and real-time processing deliver millisecond-level latency, supporting high-speed drone tracking, multi-agent collaboration, and real-time control optimization.

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Strong Environmental AdaptabilitySupports indoor, outdoor, water-surface, and underwater tracking. Active and passive markers, anti-sunlight capability, and anti-occlusion algorithms ensure stable data output in complex environments.

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Open Integration EcosystemProvides SDKs for C/C++, Python, and C#, and supports VRPN, ROS, MATLAB, Simulink, and common mocap data formats, enabling fast integration, secondary development, and multi-platform data use.

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Customized Research SolutionsProvides customized system integration for drones, vehicles, robots, and multi-agent platforms, covering data acquisition, algorithm validation, and control optimization for universities and research institutions.

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