P-01
Locomotion / Motion Capture
Whole-body human motion from monocular and multi-view video. Robot joint angles, SMPL-X parameters, time-aligned 3D skeletons.
SMPL-XJoint angles3D skeleton
Humanoid walking · RL · imitation learning
RUDRA / 003 - EMBODIED INTELLIGENCE STACK
Sensory intelligence
for machines that
move like living beings.
We capture the full human signal - sight, motion, touch, intent - across egocentric, wrist, body, and tactile sensors. The most exhaustive multi-modal stack feeding the most advanced VLA datasets in production.
6+
Synchronized sensor streams
1280²
Fisheye + wrist RGB
500Hz
9-axis IMU + mocap
VLA
Training-aware curation
EGOCENTRIC + WRIST CAPTURE◆VLA FOUNDATION MODELS◆MOTION CAPTURE + TACTILE◆ROBOT-READY DATASETS◆MULTI-MODAL SENSOR FUSION◆BENGALURU · GLOBAL◆EGOCENTRIC + WRIST CAPTURE◆VLA FOUNDATION MODELS◆MOTION CAPTURE + TACTILE◆ROBOT-READY DATASETS◆MULTI-MODAL SENSOR FUSION◆BENGALURU · GLOBAL◆
/ 01 - STACK
From human perception to robot intelligence.
003 PILLARS
01
Capture
A full-body sensor stack on every operator. Egocentric fisheye RGB, wrist-mounted cameras, 4-camera SLAM array, 9-axis IMU at 500Hz, motion-capture markers, and hand-mounted tactile sensors - all hardware-synchronized.
02
Curate
We run our own VLA models internally. We know what training pipelines actually need, and we shape multi-modal datasets to that signal - aligned vision, proprioception, and contact at frame-accurate timing.
03
Deliver
The most advanced VLA-ready datasets shipping today. Structured, labelled, multi-sensor, and verified by humans. Drop straight into partner training loops.
/ 02 - HARDWARE
Wearables that see the way humans see.
Six-plus synchronized sensor streams on a single operator. Egocentric and wrist cameras, SLAM array, 9-axis IMU, motion-capture markers, and hand tactile sensors. Sub-millisecond timing. Every frame tagged with pose, gaze, and contact - ready to train the next generation of vision-language-action models.
- Fisheye RGB
- 1280×1280 @ 60fps
- Wrist cameras
- Stereo bi-manual
- SLAM array
- 4 × 640×480 @ 30fps
- IMU
- 9-axis @ 500Hz
- Motion capture
- Full-body markers
- Tactile
- Hand contact sensors
/ 03 - PIPELINE
Raw human perception → foundation-model fuel.
- 00Human
Operator wears the rig and performs a real-world task.
- 01Capture
Egocentric, wrist, SLAM, IMU, mocap, and tactile - all fused.
- 02Annotate
Human-in-the-loop labelling of intent, contact, and trajectory.
- 03Curate
Our internal VLA loop scores and selects what actually trains.
- 04Deliver
Drop-in datasets for partner foundation-model pipelines.
/ 04 - DATA PRODUCTS
A full catalogue of VLA-ready datasets.
Six product lines covering the full surface of embodied learning, from human locomotion to humanoid whole-body manipulation. Standardized schema, cross- embodiment compatible, validated on partner training loops.
006 PRODUCT LINES
P-02
Single / Dual-Arm Manipulation
Bi-manual demonstration data from human operators and teleop rigs. End-effector trajectories with frame-accurate sync.
TCP trajectoryBi-manualTeleop
Policy learning · behavior cloning
P-03
Humanoid Whole-Body Manipulation
Upper-limb and torso coordination for full humanoid embodiments. Captured with motion-capture markers and multi-DoF rigs.
Whole-bodyTorso poseMulti-DoF
Humanoid upper-limb · WBC policy
P-04
Egocentric Video
First-person streams from our head-mounted rigs. 180° fisheye RGB + wrist cameras + SLAM, temporally aligned with action.
Fisheye 1280²Wrist RGBSLAM
VLA pretraining · VLM grounding
P-05
Human-Object Interaction (HOI)
Structured contact, hand-object 6-DoF pose, and object state transitions. The signal models actually need to learn manipulation.
6-DoF objectHand-objectContact state
Manipulation prediction · VLM training
P-06
Synthetic & Augmented Data
Sim and generative augmentation for long-tail and high-risk scenarios. Same schema as real capture, drop-in compatible.
Sim2realLong-tailAugmentation
Coverage expansion · safety scenarios
/ 05 - SPECIFICATIONS
Every dataset, fully specified.
Cross-embodiment, multi-modal, temporally aligned. We standardize the schema so partners can drop our data straight into the training pipelines they already run - no glue code, no format conversions, no surprises.
- Data modalities
- TCP trajectory · object trajectory · pointcloud · tactile · 6-DoF pose · IMU · gaze
- Temporal alignment
- Hardware-synchronized multi-modal capture · sub-millisecond accuracy
- Sensor stack
- Fisheye 1280² · wrist RGB stereo · 4× SLAM · 9-axis IMU 500Hz · mocap · hand tactile
- Scenario coverage
- Industrial · logistics · warehousing · retail · kitchen · service · in-the-wild
- Robot embodiments
- Cross-embodiment: Unitree G1, Tien Kung, Fourier, Galbot, custom arms
- End-effector support
- Inspire · Xhand · Allegro · Shadow · parallel grippers
- Delivery format
- LeRobot · RLDS · HDF5 · custom partner schemas
- Quality control
- Human-in-the-loop verification · VLA-scored curation · traceable versioning
µs
Sync accuracy
6+
Sensor modalities
8+
Robot embodiments
100%
Human-verified
“The robots of today are blind. They move without understanding, act without perception, and fail the moment the world stops cooperating. We are here to change that.”
- RUDRA / FOUNDING DOCTRINE
/ 06 - PARTNER