Robot Teleoperation and Real-Robot Data Collection Solution
DPVRRoboPilot is an integrated solution developed by DPVR for scenarios involving robot teleoperation, motion teaching, and real-robot training data collection.
Robot Teleoperation and Real-Robot Data Collection Solution
DPVRRoboPilot is an integrated solution developed by DPVR for scenarios involving robot teleoperation, motion teaching, and real-robot training data collection.
CUSTOMER PAIN POINTS
Problems faced by customers
High data acquisition costs
Robotic arms, dexterous hands and other devices require a large amount of real operational data. Traditional solutions are complex to deploy and difficult to quickly replicate to multiple workstations and scenarios.
Unstable remote operation link
Robot teleoperation places extremely high demands on low latency and stability; data latency, drift, or interruptions can compromise the effectiveness of motion teaching and the quality of the collected data.
Motion data is difficult to access in a unified manner
Different robot platforms, control systems, and training tasks impose varying requirements on data formats, interfaces, and mapping logic, making it difficult to reuse and integrate motion data across different systems.
The system integration and debugging cycle is long
Customers typically need to manage the integration of sensing devices, PC-based software, data interfaces, control systems, and robot platforms simultaneously, resulting in high costs for system-wide integration and testing, as well as lengthy verification cycles.
High data acquisition costs
Robotic arms, dexterous hands and other devices require a large amount of real operational data. Traditional solutions are complex to deploy and difficult to quickly replicate to multiple workstations and scenarios.
Unstable remote operation link
Robot teleoperation places extremely high demands on low latency and stability; data latency, drift, or interruptions can compromise the effectiveness of motion teaching and the quality of the collected data.
Motion data is difficult to access in a unified manner
Different robot platforms, control systems, and training tasks impose varying requirements on data formats, interfaces, and mapping logic, making it difficult to reuse and integrate motion data across different systems.
The system integration and debugging cycle is long
Customers typically need to manage the integration of sensing devices, PC-based software, data interfaces, control systems, and robot platforms simultaneously, resulting in high costs for system-wide integration and testing, as well as lengthy verification cycles.
WHAT ROBOPILOT PROVIDES
What can RoboPilot offer?
Human motion capture
It captures the operator’s head and hand 6DoF pose data using the DPVR E4 Embodied Edition, supporting input methods such as the headset and controllers.
PC data processing
The PC-based program processes the head and hand pose data in real time, improving the stability of acquisition and motion mapping.
Motion data output
It outputs motion-related data such as pose, trajectory, and button events, providing callable data inputs for robot teleoperation, motion teaching, and real-machine motion data acquisition.
Access verification support
It supports integration with various robot platforms, control systems, and experimental task requirements to conduct robotic arm teleoperation, dexterous hand training, motion teaching, and real-machine data acquisition verification.
Human motion capture
It captures the operator’s head and hand 6DoF pose data using the DPVR E4 Embodied Edition, supporting input methods such as the headset and controllers.
PC data processing
The PC-based program processes the head and hand pose data in real time, improving the stability of acquisition and motion mapping.
Motion data output
It outputs motion-related data such as pose, trajectory, and button events, providing callable data inputs for robot teleoperation, motion teaching, and real-machine motion data acquisition.
Access verification support
It supports integration with various robot platforms, control systems, and experimental task requirements to conduct robotic arm teleoperation, dexterous hand training, motion teaching, and real-machine data acquisition verification.
DPVR RoboPilot Embossed Robot Remote Control Solution
DPVR E4 Embossed Version × Hypersensory Data Glove × Robot Control Architecture
DPVR E4 Embossed Version
- PC Direct Connection with Ultra-Low Latency
- High-Precision 6DoF Positioning
- Lightweight Ergonomics
Head / Controller Pose
- 6DoF Pose Data
Ultra-Sensitive Data Gloves (Optional)
- Finger Joint/Gesture Hand Pose
Finger Joint Data
Input
- VR headset pose data
- Finger joint data
Human Motion Mapping
Trajectory Planning Engine (Collision Detection/Path Optimization)
Real-time Control Layer
Driver Layer
Output
- Robotic Arm Control Commands
- Dexterous Hand Control Commands
Robotic arm control
- End-effector pose mapping
- Motion planning
- Robotic arm teaching
Dexterous hand control (optional)
- Finger joint mapping
- Grasping motion synchronization
- Embossible data acquisition
DPVR E4 Embossed Version
- PC Direct Connection with Ultra-Low Latency
- High-Precision 6DoF Positioning
- Lightweight Ergonomics
Head / Controller Pose
- 6DoF Pose Data
Ultra-Sensitive Data Gloves (Optional)
- Finger Joint/Gesture Hand Pose
- Finger Joint Data
Human Motion Mapping
Trajectory Planning Engine (Collision Detection/Path Optimization)
Real-time Control Layer
Driver Layer
Input
- VR headset pose data
- Finger joint data
Output
- Robotic Arm Control Commands
- Dexterous Hand Control Commands
Robotic arm control
- End-effector pose mapping
- Motion planning
- Robotic arm teaching
Dexterous hand control (optional)
- Finger joint mapping
- Grasping motion synchronization
- Embossible data acquisition
CORE CAPABILITIES
Core Competencies
High-Precision 6DOF Pose Acquisition
Real-time acquisition of operator head and hand spatial pose data, providing stable input for robotic arm teleoperation, motion teaching, and real-machine motion data acquisition.
Direct PC Connection with Low Latency
Utilizing a PCVR direct connection architecture, it reduces uncertainties caused by wireless transmission and streaming encoding / decoding, making it more suitable for long-term integration, training verification, and teleoperation tasks.
MOTION MAPPING (Motion Mapping)
Supports the conversion of specific human operation signals into system-retrievable data input, helping customers complete end-effector pose mapping, motion teaching, and end-effector verification more quickly.
Data Interface / SDK Support
Provides the ability to output motion-related data such as pose, trajectory, and button events, facilitating integration with robot control systems, data platforms, or experimental environments.
Supports Verification in Multiple Scenarios
Targeting robotic arms, dexterous hands, and other embodied intelligent devices, supporting applications such as teleoperation, motion teaching, task training verification, and real-machine motion data acquisition verification.
High-Precision 6DOF Pose Acquisition
Real-time acquisition of operator head and hand spatial pose data, providing stable input for robotic arm teleoperation, motion teaching, and real-machine motion data acquisition.
Direct PC Connection with Low Latency
Utilizing a PCVR direct connection architecture, it reduces uncertainties caused by wireless transmission and streaming encoding/decoding, making it more suitable for long-term integration, training verification, and teleoperation tasks.
MOTION MAPPING (Motion Mapping)
Supports the conversion of specific human operation signals into system-retrievable data input, helping customers complete end-effector pose mapping, motion teaching, and end-effector verification more quickly.
Data Interface/SDK Support
Provides the ability to output motion-related data such as pose, trajectory, and button events, facilitating integration with robot control systems, data platforms, or experimental environments.
Supports Verification in Multiple Scenarios
Targeting robotic arms, dexterous hands, and other embodied intelligent devices, supporting applications such as teleoperation, motion teaching, task training verification, and real-machine motion data acquisition verification.
USE CASES
Typical application scenarios
Teleoperation of Robotic Arms
Provides teleoperation data support for robotic arm systems via handle or spatial pose data input, suitable for verifying tasks such as grasping, handling, delivery, assembly, and sorting.
University Research Experimental Platform
Provides a deployable, scalable, and customizable teleoperation and motion data acquisition verification environment for robotics labs, A-level labs, and automation and control engineering teams.
Dexterous Hand Motion Data Acquisition
Combined with input devices such as data gloves, it can be used for finger joint data acquisition, synchronized grasping movements, fine manipulation teaching, and high-fidelity hand motion training.
Motion Teaching and Task Training
Collects head and hand motion data during operator task completion, providing a data foundation for robotic arm motion teaching, complex task reproduction, and robot skill training.
Teleoperation of Robotic Arms
Provides teleoperation data support for robotic arm systems via handle or spatial pose data input, suitable for verifying tasks such as grasping, handling, delivery, assembly, and sorting.
University Research Experimental Platform
Provides a deployable, scalable, and customizable teleoperation and motion data acquisition verification environment for robotics labs, A-level labs, and automation and control engineering teams.
Dexterous Hand Motion Data Acquisition
Combined with input devices such as data gloves, it can be used for finger joint data acquisition, synchronized grasping movements, fine manipulation teaching, and high-fidelity hand motion training.
Motion Teaching and Task Training
Collects head and hand motion data during operator task completion, providing a data foundation for robotic arm motion teaching, complex task reproduction, and robot skill training.
PRODUCT COMPONENTS
Product Components Display
DPVRE4 Embossed Version/PCVR Device
Designed for robot teleoperation and data acquisition scenarios, providing stable 6DOF head and hand pose acquisition capabilities.
- Direct PC connection reduces wireless link uncertainty.
- High-precision 6DOF spatial positioning.
- Supports head-mounted display and controller pose data output.
- Suitable for long-term training, debugging, and validation.
Data Gloves/Other Input Devices
Data gloves, controllers, and other input devices can be combined according to task requirements for dexterous hand control, hand motion acquisition, and complex operation teaching.
- Finger joint data acquisition
- Gesture and grasping motion recognition
- Dexterous hand motion teaching
- High-precision hand data acquisition
DPVRE4 Embossed Version/PCVR Device
Designed for robot teleoperation and data acquisition scenarios, providing stable 6DOF head and hand pose acquisition capabilities.
- Direct PC connection reduces wireless link uncertainty.
- High-precision 6DOF spatial positioning.
- Supports head-mounted display and controller pose data output.
- Suitable for long-term training, debugging, and validation.
Data Gloves/Other Input Devices
Data gloves, controllers, and other input devices can be combined according to task requirements for dexterous hand control, hand motion acquisition, and complex operation teaching.
- Finger joint data acquisition
- Gesture and grasping motion recognition
- Dexterous hand motion teaching
- High-precision hand data acquisition
ECOSYSTEM
Collaborating with Industry Partners to Advance Scenario Validation
DPVR is continuously advancing joint validation with partners across the embodied intelligence industry chain, exploring more application scenarios for robot teleoperation, motion teaching, and real-machine motion data acquisition and validation, focusing on combinations of PCVR spatial interaction, data gloves, robotic arms, and dexterous hands.
Yudie Technology
Advancing joint validation around data gloves, finger joint data, grasping motion synchronization, and high-fidelity data acquisition.
DISCVER Robotics
Exploring the practical value of RoboPilot in scientific research validation and application scenarios around remote robotic arm control, end-effector pose mapping, motion teaching, and complex task training.
Yudie Technology
Advancing joint validation around data gloves, finger joint data, grasping motion synchronization, and high-fidelity data acquisition.
DISCVER Robotics
Exploring the practical value of RoboPilot in scientific research validation and application scenarios around remote robotic arm control, end-effector pose mapping, motion teaching, and complex task training.