88.2%
RLBench Simulation Manipulation Success Rate
Robots That Understand and Act in the Real World
Spatial coordinates
Keypoint tracking
Predicted action path
Tactile feedback
3–5 Demonstrationsfor typical task adaptation
97% Success Ratein defined real-world base tasks
24/7 Operationwith hot-swap batteries
End-to-End Platformmodels, data, robot and deployment
Designed in Switzerland
Precision & Quality
High-precision engineering and manufacturing designed for reliable, long-term real-world operations.
Engineered for Safety
Safety & Compliance
Compliance deeply engineered into the robot hardware, control system, and deployment workflow.
Seamless Workflows
Enterprise Integration
Open interfaces for ERP, MES and WMS. Robots receive tasks directly from existing operational processes.
Serviced in Europe
Data Sovereignty
Deployment, service and supply capabilities designed for European operations and strict enterprise data privacy.
1Observe
2Understand
3Predict
4Act
5Sense
6Correct
7Learn
Measured under defined conditions
Performance Designed to Be Verifiable
Every product specification and performance claim is linked to configurable test conditions, evidence, evaluation methods and limitations.
97%
Defined Base-Task Success Rate in Complex Real Environments
3–5
Real Demonstrations for Typical Task Adaptation
1%
Data Requirement Compared with Selected Traditional Pipelines
28 DoF
Full-Body Degrees of Freedom
24/7
Continuous Operation with Dual Hot-Swap Batteries
Embodied intelligence system
From Spatial Understanding to Predictive and Continual Intelligence
A unified stack connects vision, language, geometry, touch, force, action and human feedback to real robot behavior.
FAM
Embodied Manipulation Foundation Model
A few-shot, end-to-end foundation model that preserves spatial structure across perception, language and action.
Spatial heatmaps
VLTA
Vision-Language-Tactile-Action Model
A multimodal model for contact-rich manipulation, tactile understanding and real-time physical correction.
Contact intelligence
Anigon
Embodied
Intelligence Core
VisionLanguage3D GeometryTouchForce and TorqueActionEnvironment FeedbackHuman Feedback
BridgeV2W
Embodied World Model
A predictive model that evaluates candidate actions and visualizes likely outcomes before execution.
Predictive control
Human-in-the-Loop RL
Continual Learning and Recovery
A closed-loop approach combining demonstrations, interventions, recovery data and outcome-based reinforcement learning.
Continual improvement
Embodied manipulation foundation model
FAM: A Few-Shot, End-to-End Foundation Model for Embodied Manipulation
Adapt to new tasks, environments and robot platforms with only a small number of real-world demonstrations.
Before
Traditional VLA Representation
- 3D visual information compressed into a one-dimensional latent vector
- Spatial relationships lost during representation compression
- Limited interpretability
- Information bottleneck
After
FAM Spatial Representation
- Two-dimensional and three-dimensional heatmap representation
- Spatial alignment across vision, language and action
- Preserved object relationships
- Interpretable navigation and manipulation cues
Spatial Understanding Pretraining
Learning spatial keypoints, object relationships, interaction patterns and motion trajectories from large-scale human operation videos.
3D Few-Shot Alignment
Aligning visual-language representations and action policies at the spatial heatmap level.
Rapid Real-Robot Adaptation
Adapting typical tasks with only a small number of real-world demonstrations, subject to task complexity, hardware configuration and environmental conditions.
RLBenchPeg InsertionDrawer OpeningLighting VariationBackground InterferenceObstacle Interference
Vision-language-tactile-action
VLTA: Understanding the Physical World Through Contact
Contact becomes a first-class signal for precision insertion, compliant grasping, slip recovery and manipulation when vision is incomplete.
Camera View
Visual context
TRACKING
Occlusion-aware trackingVision-Tactile Fusion
Contact-aware policy
Contact
Slip
Collision
Jamming
Stable Grasp
Release
Tactile Pressure Map
Force feedback curve
Critical feedback under visual occlusion
Improved precision in assembly
Real-time correction during contact
Adaptive compliant grasping
Slip and collision detection
Improved hand-eye coordination
Embodied world model
BridgeV2W: See the Consequences Before Acting
A predictive interface compares candidate actions, visualizes likely outcomes and evaluates risk before the robot commits to execution.
01
Observe
Real-time Perception
Capture live visual feeds and robot sensor data to establish ground truth state.
Frame Rate
60 FPS
Latency
<5ms
- Multi-camera fusion
- Joint state sync
- Depth estimation
02
Imagine
World Model Forward Pass
Generate multiple future trajectories conditioned on candidate actions using the predictive model.
Candidates
5
Horizon
2.0s
- Trajectory sampling
- Physics simulation
- Scene prediction
03
Evaluate
Risk Assessment
Score each candidate against safety constraints, task objectives, and kinematic limits.
Check Rate
1000/s
Threshold
0.95
- Collision detection
- Joint limits
- Task alignment
04
Execute
Validated Action
Dispatch the highest-scoring trajectory to the robot controller with confidence bounds.
Confidence
98.7%
Dispatch
42ms
- Safe motion
- Real-time monitor
- Fallback ready
Cross-Modal Fusion
Joint embeddings from RGB, depth, proprioception, and language instructions.
Unified representation
Efficient Inference
Latency-optimized forward passes with adaptive compute allocation.
<50ms end-to-end
Generalization
Zero-shot transfer to novel scenes via pretrained visual priors.
No domain adaptation
Continual learning and recovery
Human-in-the-Loop RL: Humans and Robots Improving Together
The robot learns not only how to succeed, but also how to recover when execution deviates from the intended task.
1
Human Demonstration
2
Imitation Learning
3
Autonomous Execution
4
Human Intervention
5
Error Recovery
6
Reinforcement Learning
7
Continual Improvement
Normal execution
Deviation
Human intervention
Recovery
Policy update
Embodied data technology
Better Embodied Intelligence with Less Data
Data efficiency comes from representing motion, viewpoint, uncertainty and interaction structure around the task the robot must perform.
Robot-Centric Visual Flow
Extract task-relevant hand, object, motion and occlusion relationships from human operation video.
1Human Operation Video
2Hand Trajectory
3Object Motion
4Occlusion Relationship
5Task-Relevant Visual Flow
16.4% Average Task Success ImprovementSelected Complex Tasks Improved from 40% to 100%
Task-Centric 3D Virtual View for VLA
Synthesize a task-relevant virtual camera view from multiple visual inputs without requiring 3D rendering in the interface.
1Multiple Camera Inputs
2Point Cloud Snapshot
3Task-Relevant Virtual View
4Filtered Visual Input
1.5× Faster InferenceUp to 200% Improvement in Selected View-Dependent Tasks
Cross-View Data Augmentation
Expand demonstrations across viewpoints through motion retargeting and generative video completion.
1Single-View Demonstration
2Motion Retargeting
3Generative Video Completion
4Multi-View Training Data
18.3% Improvement in Known Views25.8% Improvement in New ViewsNo Frame-by-Frame Manual Action Annotation
Embodied Visual Information Enhancement
Detect uncertainty, revisit important regions and preserve task-relevant visual evidence over long horizons.
1Uncertainty Detection
2Repeated Attention
3Key Visual Regions
4Long-Horizon Task Support
5Plug-In Training Module
Configurable validation recordEvaluation under defined conditions
ANIGON FA-L series
A Wheeled Humanoid Platform Designed for Real Work
A mobile humanoid platform combining force-controlled arms, integrated sensing, edge computing, hot-swap power and enterprise deployment interfaces.
ANIGON Platform
Reference front viewFA-L Series
ANIGON FA-L Series · Wheeled Humanoid Platform
One Platform, Multiple Scenarios
Precision Force Control
Industrial-Grade Payload
Safety by Design
Plugs into Your ERP
All-Day Runtime · Hot-Swap Battery
- Height
- 189 cm
- Arm Span
- 65 cm
- Full Body
- 28 DoF
- Each Arm
- 7 DoF
- Maximum Speed
- 1.5 m/s
- Battery System
- Dual Hot-Swap Batteries
- Operation Capability
- 24/7
- Mobile Base
- Adaptive Lifting
- Joint Sensing
- Integrated Torque Sensors
- Control
- Full Force-Controlled Compliance
- Holding Brake
- Electromagnetic
- Collision Response
- Sensitive Detection
- Model Stack
- Powered by FAM
Subject to operating mode and site policy.
With battery rotation, maintenance and duty-cycle planning.
Hotspot map
01Vision and Multimodal Perception
027-DoF Humanoid Arms
03Joint Torque Sensors
04Dexterous Hands and End Effectors
05Integrated Compute Backpack
06Dual Hot-Swap Battery System
07Adaptive Lifting Base
08Collision Detection and Electromagnetic Brake
Integrated compute controller
Deploying Embodied Foundation Models On-Robot
A local compute and control architecture keeps multimodal inference close to the robot while separating safety-critical control from model execution.
01
Module
Edge Compute Module
02
Module
Robot Controller
03
Module
Sensor Bus
04
Module
Safety Control Unit
05
Module
Power Management
06
Module
Local Inference Pipeline
01
Low-Latency Local Inference
02
Reduced Cloud Dependency
03
Model-Control Co-Design
04
Real-Time Multimodal Processing
05
Industrial-Grade Stability
06
Safety-Control Separation
Safety-control separation
Model inference proposes actions. A separate safety control layer applies validated limits, site rules and emergency behavior before commands reach actuators.
Robot demonstration
Observe the Full Perception-to-Action Loop
Demonstration media can be linked directly to task definitions, robot configuration, test conditions and limitations.
Task execution and visual flow validation
Video demonstration 1: Humanoid platform performs high-precision tactile manipulation tasks.
Industry deployment
From Foundation Models to Operational Results
Structured case studies connect business context, robot configuration, workflow, measured value, deployment conditions and supporting evidence.
Power Grid
Power Grid Inspection and Operation
A wheeled humanoid workflow for navigation, target recognition, area alignment and compliant manipulation in selected power-grid environments.
FAMSpatial KeypointsForce Control
Industrial Material Handling
Autonomous Material Handling in Open Environments
Mobile manipulation for picking, cross-area transport, precision placement, retrieval and return-to-origin workflows.
FAMMobile ManipulationObject Detection
Manufacturing and Service
Production Line Handling and Counter Delivery
A shared robot platform for industrial loading, container transport, beverage delivery and language-directed mobile manipulation.
Language UnderstandingSLAMFAM
Logistics
Teleoperated Parcel Sorting
A data pipeline that combines VR teleoperation, motion mapping, simulation, world-model-generated data and few-shot deployment.
Teleoperation DataBridgeV2WCross-View Augmentation
Energy Services and Retail
Integrated Energy Station and Unmanned Retail Services
A multi-service workflow covering vehicle guidance, charging support, shelf inspection, replenishment and store assistance.
FAMEnterprise IntegrationObject Recognition
Appliance Manufacturing
Appliance Manufacturing Line Inspection
A coordinated inspection cell for model recognition, door opening, water injection, activation, turntable inspection and leakage scanning.
Visual RecognitionForce ControlWorkflow Coordination
Platform architecture
End-to-End Embodied Intelligence Architecture
Hardware, data, perception, models and applications form a closed loop in which execution results continuously return as new evidence.
Applications
Power GridAutomotive ManufacturingAppliance ManufacturingLogisticsIndustrial Material HandlingSmart RetailEnergy Services
Models
FAMVLTABridgeV2WVLAWorld ModelsHuman-in-the-Loop RL
Perception
Visual Understanding3D Point CloudsTactile FeedbackLanguage and SpeechSpatial KeypointsMotion Trajectories
Embodied Data
Human Operation VideoReal-Robot DataTeleoperation DataSimulation DataGenerated Cross-View DataMultimodal Feedback
Robot Hardware
Wheeled Humanoid RobotRobot ArmsDexterous HandsMobile BaseCamerasTorque SensorsTactile SensorsEdge Compute Controller
Research and validation
Research Built for Deployment
Benchmark results, real-robot comparisons, heatmaps, world-model outputs and recovery analysis are organized around reproducible validation records.
Research Paper
Spatial Heatmap Representations for Few-Shot Manipulation
A technical validation record for preserving spatial structure across vision, language and action in FAM.
FAMSpatial RepresentationFew-Shot Learning
Research Preview
Contact Intelligence Under Visual Occlusion
A research preview for tactile pressure, force feedback and vision-tactile fusion in contact-rich manipulation.
VLTATactile PerceptionContact-Rich Manipulation
Benchmark Results
Action-Conditioned Visual Prediction for Robot Control
A world-model validation record for predicting visual consequences, comparing candidate actions and identifying possible collision risk.
BridgeV2WWorld ModelPredictive Control
Service, compliance and data sovereignty
Engineered for Enterprise Deployment
Deployment readiness combines safety architecture, integration pathways, local inference, auditability, configurable data policies and lifecycle support.
Safety by Design
Safety control separated from model inference.
Compliance Engineering
Rule-based constraints for critical actions.
Enterprise Integration
ERP, MES and WMS integration readiness.
Local Edge Inference
Local or customer-specified deployment environments.
Data Isolation
Configurable data policies and deployment boundaries.
Deployment Auditability
Task logs and execution replay.
European Service Capability
Service coverage designed for European operations.
Lifecycle Maintenance
Planned updates, inspection and support workflows.
Compliance depends on product configuration, intended use, deployment environment, integration scope and applicable local requirements. Assessment records, test evidence and legal review should be linked before external claims are published.
Platform value
More Than a Robot. A Deployment Platform.
ANIGON connects research depth with industrial engineering, enterprise integration and the operating discipline required for real-world deployment.
Few-Shot Deployment
Adapt typical tasks with significantly reduced real-world demonstration requirements.
Spatial Intelligence
Preserve spatial structure through two-dimensional and three-dimensional representations.
Multimodal Closed Loop
Combine vision, language, touch, force, action and environmental feedback.
Industrial-Grade Integration
Integrate models, robotic hardware, edge computing, safety control and enterprise systems.
Deploy in the real world
Deploy Embodied Intelligence in Your Real-World Operations
From task assessment and data collection to model adaptation, robot deployment, system integration and continuous optimization.