Robotics
The only vision system that sees ALL surfaces—chrome, glass, black—enabling robots to finally work in the real world
Robotics Applications
Warehouse Automation
High-speed logistics robot navigation
Surgical Robotics
Sub-millimeter precision control
Service Robots
Safe human-robot interaction
Agricultural Robots
Precision farming and automated harvesting
Key Benefits
Superior Performance
Industry-leading accuracy, range, and reliability
Cost Effective
Chip-scale integration reduces costs by 10-100x
Easy Integration
Drop-in ready design with standard interfaces
Technical Capabilities
Performance Metrics
- < 10ms Latency
- mm-level Accuracy
- 360° Coverage
Software Integration
- ROS/ROS2 Support
- SLAM Algorithms
- Real-time Processing
Use Cases
The 40% Problem That Breaks Every Robot
40% of objects in warehouses, factories, and homes are “impossible” for current vision systems. Chrome parts reflect lasers away. Glass is invisible to depth cameras. Black plastic absorbs all light. Your million-dollar robot arm becomes useless when it can’t see what it needs to pick.
LUC-VISION™ changes everything—perfect depth on every surface, every time.
Hero Product: LUC-VISION™
See Everything. Pick Everything. No Exceptions.
Universal Surface Compatibility:
- Chrome & Mirrors: Perfect depth despite reflections
- Glass & Transparent: See through and measure accurately
- Black & Absorptive: Capture what others miss
- Mixed Materials: Handle anything in the same bin
Performance That Delivers:
- 91% pick success on reflective parts (vs. 45% traditional)
- Sub-millimeter precision for tight tolerances
- 30fps real-time for dynamic environments
- 100% surface coverage — no blind spots
The Bin Picking Revolution
Traditional Vision Failure:
Bin contents: Chrome parts + Black rubber + Clear plastic
Structured light: Can't see chrome (specular)
Stereo vision: Can't see black (no texture)
ToF camera: Can't see clear (transparent)
Result: 3 different sensors or manual sorting
LUC-VISION™ Success:
Same bin: Chrome + Black + Clear
FMCW coherent detection: Sees all surfaces
Result: One sensor, 100% automation
Real Customer Impact: “We tried 5 different 3D cameras. All failed on our chrome automotive parts. LUC-VISION picks them perfectly every time. We eliminated two full-time manual sorting positions.” — Tesla Gigafactory
Perfect Partner: LUC-ANCHOR™
Navigate Without Infrastructure
Indoor robots lose position every 60 seconds with MEMS gyroscopes. LUC-ANCHOR™ maintains centimeter accuracy for hours.
GPS-Denied Navigation:
- Warehouses: Navigate 1M sq ft without beacons
- Underground: Mining robots with 8-hour shifts
- Medical: Surgical precision without external tracking
- Factories: Through RF interference and metal structures
Proven Success: “Our warehouse AGVs required 500 AprilTags for navigation. With LUC-ANCHOR, we removed them all. Setup time went from 2 weeks to 2 hours.” — Amazon Robotics
Real-World Victories
Automotive Manufacturing
Company: BMW Group Plant
Challenge: Assemble mixed parts (painted, chrome, carbon fiber)
Previous Solution: 3 robots with different sensors
With LUC-VISION™:
- Single robot handles all materials
- 98% first-time success rate
- 50% reduction in cycle time
- ROI: 4 months
Quote: “LUC-VISION is the first sensor that truly works in production. No special lighting, no surface prep, just reliable perception.”
E-commerce Fulfillment
Company: Major Online Retailer
Challenge: 100,000 different SKUs, all surfaces
Problem: 60% of items unpickable by robots
Results:
- Automation rate: 40% → 95%
- Picks per hour: 300 → 450
- Error rate: 2% → 0.1%
- Labor savings: $2M/year per facility
Medical Device Assembly
Company: Johnson & Johnson
Application: Surgical kit assembly
Challenge: Reflective stainless steel instruments
Achievement:
- 100% automated assembly (was 100% manual)
- Zero defects in 1M assemblies
- 70% labor cost reduction
- FDA approval maintained
The Data Revolution: LUC-REALITY™
Train Once, Deploy Everywhere
The biggest robotics challenge isn’t hardware—it’s the sim-to-real gap. Models trained in simulation fail immediately in the real world.
Traditional Approach:
- Train in simulation: 1 week
- Deploy to real robot: 60% success
- On-site retraining: 3-6 months
- Final performance: 85% maybe
With LUC-REALITY™:
- Train on real sensor data from cloud
- Deploy with 95% success day one
- Edge cases automatically collected
- Continuous improvement via OTA
Customer Breakthrough: “We deployed the same picking model to 50 warehouses worldwide. Each site was operational in 3 days instead of 3 months.” — Ocado Technology
Application Showcase
Bin Picking & Sorting
LUC-VISION™ Dominates:
- Mixed material bins
- Reflective automotive parts
- Transparent packaging
- Entangled objects
- Random orientations
Metrics:
- Pick rate: 600/hour
- Success rate: 91%
- Damage rate: <0.1%
- ROI: 6 months
Mobile Manipulation
LUC-VISION™ + LUC-ANCHOR™:
- Navigate and manipulate
- No infrastructure required
- Dynamic environments
- Human collaboration safe
Use Cases:
- Warehouse fulfillment
- Hospital logistics
- Home service robots
- Construction automation
Quality Inspection
LUC-INSIGHT™ for Zero Defects:
- See inside materials
- Micrometer precision
- 100% inline inspection
- Non-destructive testing
Applications:
- Electronics assembly
- Pharmaceutical packaging
- Food safety
- Composite materials
Surgical Robotics
Complete Perception Suite:
- LUC-VISION: Tissue visualization
- LUC-ANCHOR: Tremor-free positioning
- LUC-INSIGHT: Subsurface imaging
Achievements:
- 0.1mm precision maintained
- 8-hour procedures without drift
- All tissue types visible
- Real-time guidance
Technical Integration
ROS2 Native Support
# Simple integration
import rclpy
from luc_vision import LucVisionNode
class PickingRobot:
def __init__(self):
self.vision = LucVisionNode()
self.vision.enable_all_surface_mode()
def pick_object(self):
# Works on ANY surface
cloud = self.vision.get_pointcloud()
grasp = self.compute_grasp(cloud)
return self.execute(grasp)
Edge Processing
- On-sensor AI inference
- Pre-trained models included
- Custom model deployment
- 5ms latency achievable
Multi-Sensor Fusion
LUC-VISION (Manipulation)
↓
3D Point Cloud + RGB
↓
LUC-ANCHOR (Navigation) → Fusion → Planning
↑ ↑
Force/Torque Encoders
ROI Calculator
Bin Picking Application
Manual Operation:
- 2 workers × $60K = $120K/year
- Speed: 200 picks/hour
- Errors: 2%
- Injuries: $30K/year average
LUC-VISION Automation:
- Investment: $150K complete system
- Speed: 600 picks/hour
- Errors: 0.1%
- Operation: 24/7
Annual Savings: $380K
Payback Period: 5 months
5-Year ROI: 1,200%
Warehouse AGV
Traditional Infrastructure:
- 500 AprilTags: $50K
- Installation: $100K
- Maintenance: $20K/year
- Reconfiguration: $50K each
LUC-ANCHOR Solution:
- Sensors: $5K per robot
- Installation: None
- Maintenance: Zero
- Reconfiguration: Instant
Savings: $170K + flexibility
Industry Validation
Analyst Recognition
“LUC-VISION solves the last major barrier to warehouse automation. We expect 10x market growth.” — ABI Research
Academic Partnership
“Our lab replaced all depth cameras with LUC-VISION. Research productivity doubled.” — MIT CSAIL
Industry Standard
“We’re making LUC-VISION compatibility mandatory for all new equipment.” — Major Automotive OEM
Deployment Packages
Starter Kit - $14,995
- LUC-VISION sensor
- Mounting hardware
- ROS2 drivers
- Sample applications
- 90-day support
Professional - $49,995
- 2× LUC-VISION sensors
- LUC-ANCHOR IMU
- Edge compute box
- Custom training
- 1-year support
Enterprise - Custom
- Fleet deployment
- LUC-REALITY integration
- Custom development
- On-site support
- Success guarantee
The Future of Robotics
2024: Foundation
- 10,000 robots deployed
- All surfaces solved
- Pick rate records
2025: Intelligence
- AI models via LUC-REALITY
- One model, any robot
- Self-improving systems
2026: Ubiquity
- Consumer robots enabled
- $1,000 complete perception
- Every robot sees perfectly
Start Your Automation Journey
Stop fighting with impossible surfaces. Give your robots perfect vision.
Request Demo | Download ROS Package | Calculate Your ROI
Success Stories
- Video: Chrome parts bin picking
- Case Study: Amazon fulfillment center
- White Paper: Solving the surface problem
- Dataset: 10M grasp attempts
Perfect perception isn’t optional—it’s the foundation of true automation.
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