Publicly available trajectories distributed across official repositories for open research and benchmarking.
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The Fuel of the Physical AI Era
Embodied Manipulation Systems
Embodied Data Collection Units
Multimodal Data Output
Industry Enablement
The RealMan Darwin Teleoperation Platform is an immersive remote-control client purpose-built for frontline teleoperators. Using a teleoperation-arm controller together with multi-channel live video streams and SLAM localization maps, operators carry out precise, safe remote operation of robots at the far end.
Designed around clear field of view, precise control, closed-loop tasks, and adjustable parameters, the platform lets operators complete complex industrial tasks from thousands of miles away—as if on-site.
Dual-arm views, an expanded forward view, and 360° BEV are presented simultaneously in full-screen immersion—remote operation as if on-site.
The robot's position and path are rendered in real time for full spatial awareness, with waypoint auto-navigation and obstacle avoidance.
From task assignment and execution to submission and acceptance, every operation is fully traceable.
Switch freely between remote-operation mode and data-collection mode to match different business needs.
Switch freely between controller and keyboard input to suit different operating habits and scenarios.
Customizable parameters including arm / gripper force-feedback intensity and chassis speed.
The RealMan Darwin Device Management Platform is an all-in-one SaaS platform built for robot remote-operation scenarios, covering the full lifecycle from device onboarding and task dispatch to compliance control and multi-tenant operations.
Built on the principles of manageable devices, controllable tasks, auditable compliance, and tenant isolation, the platform helps enterprises operate efficiently and reduce operational risk—forming a solid foundation for a robot remote-operation service business.
Unified management of robots and master-control devices, with real-time online-status monitoring and traceable versions and locations.
Task creation, status tracking, and device binding, with full task-flow visualization.
Timeout alerts, submission and acceptance, and flexible task restrictions reduce operational and compliance risk.
Authorization binding across master controllers, robots, and tenants, managed granularly by tenant and user.
Isolated tenant operations and independent organizational structures, supporting the B2B2C business model.
One-stop configuration of users, roles, menus, data dictionaries, and whitelists, with fine-grained permission control.
The central control hub for embodied-intelligence data production. Collection, quality inspection, format conversion, annotation, review, and delivery all converge into a single system.
Scenes, materials, collection items, plans, robots, operators, and shifts are all managed in a structured way—a 30-person project can be coordinated by a single project manager. Multimodal raw data captured by robots—dual-arm joints, binocular + head RGB-D, torque, and timestamps—is stored with strong alignment, then passes automated quality inspection and format conversion to become training-ready. Annotation is underpinned by AI pre-labeling, supplemented by human input, and backed by arbitration-based review—every annotation graded, owned, and versioned.
RealMan's in-house dual-arm robots are the platform's target hardware. From joint torque to data format, from hardware synchronization to timestamps, the hardware design itself accounts for downstream data usability—something software-only platforms integrating third-party robots can hardly achieve, as they cannot require third-party firmware to output a specified timestamp format.
MCAP inspection, format conversion, and LeRobot inspection are chained between collection and annotation, intercepting anomalous data before it reaches annotation. Compared with manual spot-checks after collection, issues are caught earlier and handling costs are lower.
Data, menus, permissions, and storage buckets are isolated end-to-end—not pseudo-isolation based merely on a tenant_id. Multiple clients can run data production in parallel, fully isolated and invisible to one another.
2–5 minutes per data item, a 95% cross-scenario pass rate, validated across four scenario types.
Public network for everyday collaboration, private network for sensitive scenarios. The UI can be re-released with the client's brand colors, logo, and naming.
The platform grew out of the daily practice of RealMan's data-production team, with every field and state transition validated by real-world operations.
The RealMan Darwin Data Dashboard is a global visualization command center designed for executives and operational decision-makers. It integrates multidimensional real-time operational data, bringing robot operation footage, a global deployment map, core metrics, growth trends, and robot work-hour rankings together in a single view.
Its core value lies in aggregating, dynamically rendering, and structurally presenting globally distributed robot remote-operation data in real time—giving managers a clear grasp of cross-border, cross-time-zone "robot remote-operation service" operations and driving faster, more accurate decisions with data.
Four dimensions—total robot work hours, robot count, cross-time-zone workforce, and geographic coverage—comprehensively gauge business scale.
An at-a-glance view of the global robot remote-operation service footprint, illustrating the platform's intercontinental strategic layout.
Donut charts reveal business structure and supply–demand dynamics across remote-operation robot allocation and workforce allocation.
Review business fluctuations, inform strategic planning, and demonstrate investment value.
Dual video windows showing both the robot's worksite and the operator's workstation for direct on-site awareness.
Monitor operations, quantify performance, and troubleshoot anomalies—covering scheduling, evaluation, and quality control.
Tightly aligned multi-view visual streams give models a consistent temporal foundation for perception, fusion, and action learning.
RealSource pairs dense robot proprioception with large-scale visual demonstrations to support both learning and evaluation workflows.
Each robot and sensor undergoes rigorous factory calibration, with complete camera calibration parameters provided, enabling users to deploy the system directly without additional calibration.
For the same task, large-scale demonstrations are performed across diverse variables, including object attributes, environmental context, motion trajectories, and viewpoints, to support broader generalization.
An optimized transmission, caching, and processing pipeline helps preserve complete and continuous demonstrations even under demanding recording conditions.
Exoskeleton-based teleoperation preserves natural dual-arm coordination and expert motion intent, creating trajectories that are more transferable to real embodied tasks.
RealMan leads the formulation of 3 CR standards for humanoid robot data systems.
Supports MCAP, HDF5, and LeRobot for easier integration with mainstream research toolchains.
Designed for reinforcement learning validation, model development, and real-world deployment.
Set target tasks, scenarios, data scope, and success criteria.
Confirm robot configuration, sensors, environments, and collection strategy.
Run parallel teleoperation sessions for scalable real-world data collection.
Apply automated checks and expert review to ensure consistency and usability.
Prepare the dataset in target formats such as MCAP, HDF5, or LeRobot.
Add semantic labels, metadata, and task structure for downstream training use.
Deliver packaged datasets for easier use in research, training, and deployment workflows.
When building a data collection site in-house, customers commonly face three pain points: long build cycles, fragmented hardware selection, and limited operational experience. REALMAN provides an end-to-end solution from 0 to 1, and has successfully delivered China's first humanoid robot data training center.
China's first humanoid robot data training center is already delivered and operational.
Standardized across the full chain — from planning, fit-out, hardware, software, and data, to operations and sales.
Complete delivery from 0 to 1, ready for rapid operation.
Site planning, functional zoning, task-scenario design, equipment lists, implementation plan.
Collection, calibration, maintenance, office, storage, showcase, and safety zones.
RealBot-S2 / L2 / 01, teleoperation rigs, sensors, servers, and networking equipment.
Edge collection system, task planning, data production, data QA, and data storage platforms.
Collection, annotation, QA, format, and time-synchronization standards.
Staffing, training systems, equipment maintenance, collection scheduling, data review, and exception handling.
Standard data packages, custom datasets, scenario task libraries, format conversion, and model-validation data.
Data subscriptions, custom data packages, platform services, testing & certification, training & competitions, and ecosystem partnerships.
Standard dataset licensing plus custom dataset service fees.
Technical certification reports and tiered safety assessments.
Competitions and training, technical memberships, and training bases.
Scenario validation, training and inference, billed by task complexity.
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