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Chinese robotics — Dataset and collection discovery·Collected at· 14 days agoSignalEditorial score85

Dual-Arm Embodied Intelligence Teleoperation Platform - Ai Cai Gou Source Bible

双臂具身智能遥操作平台 - 爱采购寻源宝典

Summary

The Cobot Magic platform features a modular, high-precision design with Tracer differential chassis and PiPER six-axis arms, supporting ROS frameworks and open-source algorithms. It integrates multi-modal perception systems and enables data collection for tasks like precision assembly and home care, with a 50% reduction in development time and 30-50% cost savings compared to traditional solutions.

Editorial context

The Cobot Magic platform introduces a modular, high-precision dual-arm teleoperation system with ROS compatibility, multi-modal sensing, and integration with large-scale datasets like JD ManiData. It aims to reduce development time and enhance deployment readiness for industrial and domestic applications.

Source: Chinese robotics — Dataset and collection discovery · Read original article ↗

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What the source reports

Publisher-reported claims, with original evidence. These results have not been independently verified by RoboSignal.

Control
TeleoperatedOpen source S2

Reported numbers

  • repeating positioning accuracy

    2

    View original evidence
    1、模块化高精度设计‌ 采用‌Tracer差速移动底盘+PiPER六轴机械臂+多模态感知系统‌架构,通过EtherCAT总线实现全向移动与双臂协同控制,重复定位精度达‌±2mm‌,动态负载补偿支持0-50kg自适应。
    Open source S8
  • single arm load

    1.5

    View original evidence
    松灵Cobot Magic双臂智能遥操作平台采用模块化高精度设计,集成Tracer差速底盘(±2mm定位)与双PiPER六轴机械臂(单臂负载1.5kg,±0.1mm精度,10ms级响应),搭载多模态感知系统(激光雷达+深度相机),实现全向移动与双臂协同。
    Open source S2
  • repeating positioning accuracy

    0.05

    View original evidence
    PiPER机械臂‌:单臂负载‌1.5kg‌,重复定位精度‌±0.05mm‌,关节响应时间低于‌10ms‌,支持360/s高速运动,适应精密装配与快速分拣任务。
    Open source S9
  • environment perception range

    120

    View original evidence
    2、多模态感知融合‌ 集成‌激光雷达(速腾聚创RS-LiDAR-M1)‌、‌Intel RealSense D435i深度相机‌与‌奥比中光Dabai相机‌,实现120m环境感知与30-60Hz高帧率数据采集,覆盖复杂场景需求。
    Open source S10
  • data collection frame rate

    30–60

    View original evidence
    2、多模态感知融合‌ 集成‌激光雷达(速腾聚创RS-LiDAR-M1)‌、‌Intel RealSense D435i深度相机‌与‌奥比中光Dabai相机‌,实现120m环境感知与30-60Hz高帧率数据采集,覆盖复杂场景需求。
    Open source S10
  • maximum load compensation

    0–50

    View original evidence
    1、模块化高精度设计‌ 采用‌Tracer差速移动底盘+PiPER六轴机械臂+多模态感知系统‌架构,通过EtherCAT总线实现全向移动与双臂协同控制,重复定位精度达‌±2mm‌,动态负载补偿支持0-50kg自适应。
    Open source S8
  • joint response time

    10

    View original evidence
    PiPER机械臂‌:单臂负载‌1.5kg‌,重复定位精度‌±0.05mm‌,关节响应时间低于‌10ms‌,支持360/s高速运动,适应精密装配与快速分拣任务。
    Open source S9
  • error rate in sorting

    0.01

    View original evidence
    5、‌应用场景与灵活性‌ 工业自动化‌:适用于汽车制造、3C电子等领域的精密装配与搬运,分拣误差率降低至‌±0.01mm‌,破损率下降30%。
    Open source S15
  • code: not_reported
  • dataset: not_reported
  • paper: not_reported

What remains unknown

Not established in the collected evidence: Environment, Data origin.

Dataset licensing and commercial-use rights are not established here.

Reported performance applies to the described task. It does not establish general autonomy or deployment readiness.

Source excerpts and review record

Automatically extracted; no manual editorial approval recorded.

松灵Cobot Magic双臂智能遥操作平台采用模块化高精度设计,集成Tracer差速底盘(±2mm定位)与双PiPER六轴机械臂(单臂负载1.5kg,±0.1mm精度,10ms级响应),搭载多模态感知系统(激光雷达+深度相机),实现全向移动与双臂协同。

Open source S2

4、数据集与模型联动‌ 赋能‌JD ManiData‌(国内首个双臂移动机器人操作数据集)与‌ARIO百万级标准化数据集‌,支持物流分拣、家庭护理等场景训练。

Open source S13

1、模块化高精度设计‌ 采用‌Tracer差速移动底盘+PiPER六轴机械臂+多模态感知系统‌架构,通过EtherCAT总线实现全向移动与双臂协同控制,重复定位精度达‌±2mm‌,动态负载补偿支持0-50kg自适应。

Open source S8

PiPER机械臂‌:单臂负载‌1.5kg‌,重复定位精度‌±0.05mm‌,关节响应时间低于‌10ms‌,支持360/s高速运动,适应精密装配与快速分拣任务。

Open source S9

2、多模态感知融合‌ 集成‌激光雷达(速腾聚创RS-LiDAR-M1)‌、‌Intel RealSense D435i深度相机‌与‌奥比中光Dabai相机‌,实现120m环境感知与30-60Hz高帧率数据采集,覆盖复杂场景需求。

Open source S10

5、‌应用场景与灵活性‌ 工业自动化‌:适用于汽车制造、3C电子等领域的精密装配与搬运,分拣误差率降低至‌±0.01mm‌,破损率下降30%。

Open source S15

Implications for data suppliers

RoboSignal interpretation and collection questions, not statements of buyer demand.

  • Confirm the required data type and collection setting with the buyer; this source does not establish a complete collection specification.
  • Compare the reported units and scope before using these quantities in a budget. Recording hours, sensor-hours and trajectories are different measures.
  • Validate demand and acceptance criteria with a buyer before scaling. Publication, popularity and a research result do not establish a purchase commitment.

Source:Chinese robotics — Dataset and collection discovery · b2bwiki.baidu.com

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