lidarsystem.ai

#Lidar System AI | Artificial Intelligence powered Lidar System

#Ouster | Ouster adds Rev8 OS digital lidar integrations across NVIDIA Jetson Platform | Native color lidar sensing to NVIDIA Robotics ecosystem to power next wave of Physical AI | Rev8 is powered by next-generation L4 Ouster Silicon | Isaac ROS, allowing Rev8 rich, high-density point clouds to be ingested directly into NVIDIA hardware-accelerated perception pipelines | Native support for Rev8 sensors within open NVIDIA Isaac Sim simulation framework | Developers can harness physically accurate 3D lidar models to evaluate range, resolution, color, and intensity to generate accurate synthetic data to train machine learning models and validate full perception pipelines prior to physical deployment | Ouster drivers are tuned to leverage NVIDIA Jetson AGX Orin and Jetson Thor, providing real-time, low-latency processing required for 3D SLAM, obstacle detection, and sensor fusion at edge | NVIDIA NPN partner | Building blocks for Physical AI, enabling machines to sense, think, and act in real world

#Flyability | Drones for industrial inspection and analysis | Confined space inspection | Collision and crash resistant inspection drone | 3D mapping | Volumetric measurement | Inspections of cargo ships, bridges, ports, steel mills cement factories, liquid gas tanks, nuclear facilities, city wide underground sewage systems | Flying mobile scanner | Fits through openings as small as 50x50cm | Creates high resolution scans beyond line of sight | FARO Connect SLAM algorithm | Accurate 3D maps and digital twins of the most inaccessible spaces with centimeter precision | Comprehensive visual representations of challenging indoor spaces | Precise mapping and analysis | 100 m capacity to cover | 1,310,720 pts/sec | 340 m tunnel survey in underground mine | Fixed cage physically protects hardware | Drone recovers flight stability after collision | Survey Software (SS) combines multiple point clouds | SS georeferences point clouds | SS refines 3D models with various filters | SS outputs processed point cloud data to file types LAZ, LAS, PLY, TXT, and E57 | Drone payload: high resolution Ouster OS0-128 Rev 7 LiDAR sensor | Flammable gas sensor | Resume Inspection autonomously guides drone back to the last Return-to-Home (RTH) point via the shortest route | After battery change and successful relocalization, pilot is prompted in Cockpit to return to the spot where Smart RTH was last triggered | Drone then autonomously follows the most efficient path to that point to continue the mission, saving flight time and improving efficiency with every battery change

#Blue White Robotics | Autonomous kit for existing farm tractors | Ultra high-precision navigation | Real-time situational awareness | Ouster 3D digital lidar

#OndoSense | Radar distance sensor | Sensor software: integrated into control system or used for independent quality monitoring | Object detection | Distance measurement | Position control | Agriculture: reliable height control of the field sprayer | Mining industry | Transport & Logistics | Shipping & Offshore | Mechanical and plant engineering | Metal and steel industry | Energy sector | Harsh industrial environments | Dust & smoke: no influence | Rain & snow: no influence | Radar frequency: 122GHz | Opening angle: ±3° | Measuring range: 0.3 – 40 m | Measuring rate: up to 100Hz | Output rate: up to 10 ms / 100 Hz | Measurement accuracy; up to ±1mm | Measurement precision: ±1mm | Communication protocol: RS485; Profinet, other interfaces via gateway | Switching output: 3x push-pull (PNP/NPN) | Analogue output: Current interface (4 – 20 mA) | Protection class: IP67

#Avikus | Autonomous intelligent navigation | Global shipping industry | Fast and secure operations within ports | Automated docking and undocking | Obstacle avoidance | HD Hyundai | Ouster OS sensor

#Optex | LiDAR Perimeter Security | Deploying invisible wall or plane, protecting buildings or assets | Intrusion detection | Accurate outdoor and indoor security sensors with LiDAR technology | Advanced detection capabilities | Long-range customisable detection zones | Enhanced environmental resistance | Creating virtual plane or wall to protect perimeters, buildings, and assets | Analysing size and distance of moving objects | Providing accurate point detection by tracking X & Y coordinates of moving objects | Defining type of intrusion based on object size | Differentiating between people, animals, vehicles, drones and more | Triggering right notifications | Up to 8 detection zones independently configurable allowing for multiple sensitivity scenarios | Integrated camera | -40 using a heated lens | Dynamic event filtering | Detection zone as two parts - judgment and alarm zonen| Intelligent logic to alarm based on detected vehicle size | Customise triggers | Virtual walls and planes | Securing a luxury Villa in Tuscany, Italy | Using sensors capable of creating customisable detection zones within compact footprint, in order to protect narrow and specific areas of the property | 13 REDSCAN mini sensors based on LiDAR technology installed | Seamlessly blending with the villa architecture | Sensors painted in same colour as corresponding walls | HTTP-based network modules

#Sebino | Lidar Perimeter Volumetric protection | Artificial intelligence and Deep Learning to distinguish humans from animals, vehicles, and drones | Defining area where only maximum number of people can enter | Via Enrico Mattei, 28, 24040 Madone (BG)

#SFA Oxford | Research | Critical minerals in Artificial Intelligence

#Forterra | AutoDrive | Driverless system | Autonomous vehicle system.| Vehicle-platform and payload agnostic | In-Vehicle, Remote or Garrison Oversight | Off-Road/On-Road | GPS-Denied Operation | Single-Vehicle Waypoint Route Navigation | Multi-Vehicle Convoys and Platooning | Static and Dynamic Obstacle Avoidance | Mission Re-Pathing | Retrotraverse and Reverse Platooning, with Trailers | Ouster lidar

#Leddar Tech | LiDARs for mobility, ITS and industrial applications

#Velodyne | Lidar | Vision for autonomous mobile robots

#Ommatidia Lidar | Product: 3D Light Field Sensor | Channels: 128 parallel | Imaging vibrometry functionality | Target accuracy: 10µm | Measurement range: 0.5-50 m | Measurement accuracy (MPE): 20 + 6 µ/m | Angular range 30 x 360 | Vibrometry sampling frequenvy: 40 kHz | Vibrometry max in-band velocity: 15.5 mm/s | Power consumption: 45W | Battery operation time: 240 min | Interface: Ethernet | Format: CSV / VKT / STL / PLY / TXT | Dimension: 150x228x382 mm | Weight: 7,5 kg | Pointer: ~633 nm | Temperature range: 0/40 ºC | Environmental protection class: IP54 | Eye safety: Class 1M | Raw point clouds: over 1 million points | Calibration: metrology-grade with compensation of thermal and atmospheric effects | Geotagging: GPS | Output: 3D profiles of large objects

#Routescene | UAV lidar system

#Motional | Robotaxis | Ouster as the exclusive provider of long-range lidar sensors for its all-electric IONIQ 5-based robotaxis | Real-time 3D data up to 0.1-degree vertical and horizontal resolution with up to 300-meter range and 360° surround view | Over 30 sensors carefully integrated into the IONIQ 5 robotaxi design | IONIQ 5 robotaxis deployed for Motional’s commercial operations in Las Vegas and Los Angeles, and its testing operations in Boston, Pittsburgh, and Singapore

#LASE | Gantry crane outfitted with Ouster digital lidar sensors as part of the LASE solution to automate the handling of containers | Ouster OS1 sensors for precise position measurement and object detection to enable safer autonomous or semi-automated handling of containers | Collision avoidance | Optimal positioning and safe lifting of cargo on trucks | Ouster sensor for zone monitorin | Smart port market ~$2 billion to reach approximately $11 billion by 2030 | Over 800 container terminals around the world | Existing installations can be upgraded with 3D lidar | LASE won contract to supply 15 LaseLCPS-3D-2D (Load Collision Prevention System) systems for three container terminals in Italy | LaseLCPS-3D-2D system combines 3D/2D measuring systems for crane systems | It avoids collisions between containers in container stack in trolley travel direction with containers in operation bay and adjacent bays | Integrated soft-landing function ensures low-noise and wear-reduced container setting down | LASE won contract to supply a LaseBVH (Bulk Volume Heap) system industrial automation company in USA | LaseBVH—Bulk Volume Heap measuring system is high-precision 3D laser measuring system specially designed for measuring volume of bulk material stockpiles | Measurements are taken from stackers and/or reclaimers working in mining area or stockpiles | Depending on stockpile size and machine, one to two 3D laser scanners are installed on stacker/reclaimer | LASE Multifunctional Systems for port in Italy | LASE has been awarded the contract to supply two LaseYC-MF-2 systems | LaseYC-MF-2 is multifunctional laser measurement system based on multilayer laser scanner technology | .System is based on two multilayer laser scanners installed below portal girder above truck lane | Software connects sensors to LASE Control Unit (LCU) | Observing area truck lane makes it possible to cover following functions | Cabin PositionTruck Movement Detection | Truck Positioning | System Area Surveillance | Truck Operation

#Carbon Robotics | Autonomous LaserWeeder Robot | Deep Learning | Laser | Lidar Sensor | Nvidia | Cumming

#JAKA Robotics | Collaborative Robots for Inspection and Testing | Applications

#Vaisala | Industrial and Wheather Measurement | Lidar

#CHCNAV | Fully-Integrated Drone LIDAR+RGB Mapping System | Accurate 3D data collection | Capturing 3D reality in streamlined workflow | Simultaneous acquisition of point cloud data and high-resolution imagery | Capturing precise ground surfaces | Highly accurate Digital Elevation Models (DEMs) | Digital Surface Models (DSMs)

#Outsight | Transforming Raw 3D data from different manufacturers into actionable information | Software solutions to enable anonymous monitoring of people and vehicle flows in a variety of contexts such as airports and railway stations, shopping centres and sports facilities | Intelligent Transportation Systems benefiting from 3D LiDAR perception | Obtaining operational information: wsiting time in queue, safe distance detection | Autonomous car | Lidar | Object distance, size and volume calculation

#LeddarTech | Environmental sensing solutions for autonomous vehicles and ADAS

#Outrider | Autonomous system on zero-emission electric vehicle platform | Electric Autonomous Vehicles | Improving turnaround times per truck in distribution centers | Helping ease supply chain bottlenecks | Hitching and unhitching trailers | Monitoring trailer locations

#Third Wave | Hybrid autonomous vehicles and intelligent fleet management system | Autonomous vehicles in warehouses | Object detection in warehouse aisles | Automated material handling | Automating forklift | Ouster digital lidar sensor

#Luminar | Lidar technology

#Nissan | Fusion of LiDAR, camera and radar | Perception algorithm | Vehicle-control algorithm | 3D perception of vehicle surroundings | Reproducing space and objects | Recognizing scene context: vehicle category, road structure, traffic signs, characters | Recognizing motion of surrounding objects

#Plus ai | Open Platform for Autonomy (OPA) | Software platform | Converting sensor data from radar, lidar, and cameras into actionable intelligence | Building and updating maps to aid in navigation, perception, planning, and localization | OS: Linux, QNX | Luminar

#Ouster Announces Strategic Partnership with Constellis to Bring Physical AI to Advanced Security Operations | Ouster Gemini to serve as the foundational layer of LEXSO to deliver real-time 3D intelligence across complex security environments | Combining LEXSO AI-driven sensor fusion platform, with Ouster Gemini and digital lidar | Leveraging AI and multiple sensing modalities lidar, radar, thermal imaging, acoustic detection, and video analytics LEXSO fuses data into a single, actionable operating picture in real time | Ouster AI software processes 3D digital lidar data for real-time analytics, threat classification, and automated response protocols | 3D situational awareness | Object tracking across challenging weather and light conditions | Autonomous threat assessment and response coordination | Ouster software-defined approach to lidar

#Hesai Technology | Lidars for autonomous vehicles

#SiLC Technologies | Frequency-modulated continuous wavy (FMCW) lidar.| Detecting vehicles and various obstacles from long distances | Detects tires at 150 m (492.1 ft.) away and a person in dark clothing at 300 m (984.2 ft.) | Fully qualified fabrication process | Proven, highly automated photonics assembly and manufacturing techniques | Full integration of all the photonics functions, including lasers and detectors, into a single chip | Utilizing frequency modulated continuous wave (FMCW) at the 1550nm wavelength | 1550 nanometer wavelength addresses eye safety regulatory concerns | Eyeonic Vision Sensor platform | Suite of development kits | Detailed point cloud visuals streamed over Ethernet | Ultra Long Range (ULR) Eyeonic Vision System

#Neptune Labs | neptune.ai | Tracking foundation model training | Model training | Reproducing experiments | Rolling back to the last working stage of model | Transferring models across domains and teams | Monitoring parallel training jobs | Tracking jobs operating on different compute clusters | Rapidly identifying and resolving model training issues | Workflow set up to handle the most common model training scenarios | Tool to organize deep learning experiments

#Genetec | Security Center Platform | Ouster Gemini integrated | Fusing lidar and video surveillance into a single interface | Unifying customer data from lidar, cameras and radar | Physical intrusion detection in real-time | Using 3D data to power automated detection, classification, tracking, and monitoring | Measuring the distance, trajectory or speed of people or vehicles | Quickly identifying and responding to real threats with confidence | Reducing false alarms

#Linux Foundation | LF AI & Data | Fostering open source innovation in artificial intelligence and data | Open Platform for Enterprise AI (OPEA) | Creating flexible, scalable Generative AI systems | Promoting sustainable ecosystem for open source AI solutions | Simplifying the deployment of generative AI (GenAI) systems | Standardization of Retrieval-Augmented Generation (RAG) | Supporting Linux development and open-source software projects | Linux kernel | Linus Torvalds

#outrider.ai | Automating yard operations for logistics hubs | Electric, zero-emission yard trucks | Advanced Testing Facility, which mimics distribution yards

#BrainChip | Ultra-low power, fully digital, event- based, brain-inspired AI | Low power acceleration co-processor | Enabling very compact, ultra-low power, portable and intelligent devices | Accelerates limited use case-specific neural network models | SDK for rapidly developing and deploying AI applications for Edge | Support for models created with TensorFlow/Keras and Pytorch | Event-based compute platform ideal for early detection, low-latency solutions | Development contract from Air Force Research Laboratory (AFRL) on neuromorphic radar signaling processing technologies | Mapping Complex Sensor Signal Processing Algorithms onto Neuromorphic Chips | Improving cognitive communication capabilities on size, weight and power & cost (SWaP-C) constrained platforms such as military, spacecraft and robotics | Embedding sophisticated radar processing solutions in SWaP-C constrained radar platforms | Low-power, high-performance computing in the most mission-critical use cases | Hardware and AI model using Temporal Enabled Neural Network (TENNs) model

#Ouster | BlueCity | Powering Lidar-Enabled Smart Traffic Solution | Traffic management solution in Chattanooga, Tennessee | Improvung roadway safety | Reducing congestion.| BlueCity solution to over 120 intersections | Combining digital lidar sensors and edge AI at each intersection | Managing traffic flow | Detecting and analyzing safety incidents | Providing detection for vehicle-to-everything (V2X) communications | Advanced perception software from Ouster | Lidar-powered smart traffic network | Optimizing traffic signal management on roads and intersections | Providing data to improve pedestrian safety | Intelligent signal actuation at intersections | Generating analytics data stream to traffic operators | Creating real-time 3D digital traffic twin of an intersection or road | Automating data collection in the cloud | Monitoring road events more accurately for vehicles, pedestrians and cyclists | Quick safety interventions | Long-term planning optimizations | Deep learning AI perception | Object classification | Object detection | Traffic actuation | Near-miss detection | Outside of crosswalk events | Red light running | Wrong-way driving | Southern Lighting & Traffic Systems | Center for Urban Informatics & Progress (CUIP) | University of Tennessee Chattanooga Research Institute (UTCRI) | Certified lidar traffic solution with Buy America(n) lidar

#NavVis | Point cloud processing workflow | Surveying | Laser scanning | Process laser scan data captured using NavVis technology from anywhere with internet connection | View and validate every control point | Ensure data privacy with fully automated and integrated blurring functionality | Point cloud presets | Environment-specific point cloud modes | Generate photorealistic point clouds automatically cleaned of dynamic objects while preserving original details and colors | Upload your geo-referenced control points file in global coordinate system | Automatically geo-register your point cloud | View control points exact location on quality map | Locate, verify, select/deselect control points to identify any potential errors before processing begins | Automated image anonymization process | Detecting and blurring individuals’ faces, bodies, and license plates in images and point clouds captured with NavVis devices | Confidently create and share projects that meet strict data confidentiality | Meet compliance standards, including GDPR requirements | Download comprehensive quality report | Detailed information on data accuracy

#Rijkswaterstaat | Dutch Ministry of Infrastructure and Water Management | Harbour Master of Rotterdam | Planning to develop a warning system based on lidar (3-D radar) | Inland vessels collide with Willemsbrug | Collisions receive a great deal of public attention occurring in densely populated urban area | Collisions involving bridges involve a certain level of risk | Royal Dutch Inland Shipping Association | Platform Zero Incidents | Rotterdam-Rijnmond Safety Region | Dutch Ministry of Defence | Dutch National Coordinator for Security and Counterterrorism (NCTV) | FERM Foundation

#Robotics & AI Institute | Collaborates with Boston Dynamics | Developed jointly Reinforcement Learning Researcher Kit for Spot quadruped robot | Developing sim-to-real for mobility | Transferring simulation results to real robotic hardware | Bridging sim-to-reality gap | Training policies generating a variety of agile behavior on physical hardware | Trying to achieve novel, robust, and practical locomotion behavior | Improving whole body loco-manipulation | Developing robot capability to manipulate objects and fixtures, such as doors and levers, in conjunction with locomotion significantly enhancing its utility | Exploring new policies to improve robustness in scenarios | Exploring full-body contact strategies | Exploring high-performance, whole-body locomotion and tasks that require full-body contact strategies, such as dynamic running and full-body manipulation of heavy objects, necessitating close coordination between arms and legs | Aiming to utilize reinforcement learning to generate behavior during complex contact events without imposing strict requirements | Develop technology that enables future generations of intelligent machines | Streamlining processes for robots to achieve new skills | Developing perception, situational understanding, reasoning, cognitive functions underpinning robot abilities and combining them with advances in their physical capabilities | Conducting research in four core areas: cognitive AI, athletic AI, organic hardware design, and ethics related to robotics

#UC Berkeley, CA, USA | Professor Trevor Darrell | Advancing machine intelligence | Methods for training vision models | Enabling robots to determine appropriate actions in novel situations | Approaches to make VLMs smaller and more efficient while retaining accuracy | How LLMs can be used as visual reasoning coordinators, overseeing the use of multiple task-specific models | Utilizing visual intelligence at home while preserving privacy | Focused on advancements in object detection, semantic segmentation and feature extraction techniques | Researched advanced unsupervised learning techniques and adaptive models | Researched cross-modal methods that integrate various data types | Advised SafelyYou, Nexar, SuperAnnotate. Pinterest, Tyzx, IQ Engines, Koozoo, BotSquare/Flutter, MetaMind, Trendage, Center Stage, KiwiBot, WaveOne, DeepScale, Grabango | Co-founder and President of Prompt AI

#Thinking Machines Lab | thinkingmachines.ai | Building artificial intelligence models and products | Competing on high end of large language models | Human-AI collaboration | Building AI that can adapt to full spectrum of human expertise | Multimodal systems that work with people collaboratively | AI models that can work across text, audio, video | AI models designed to excel in science and programming | Publishing technical blog posts, papers, program code | Mira Murati: CEO | John Schulman: Chief Scientist | Barret Zoph: CTO | Alexander Kirillov: Multimodal Research Head | John Lachman: Head of Special Projects | Alex Gartrell: Linux kernel, networking, and containerization | Andrew Tulloch: ML systems research and engineering | Brydon Eastman: Human and synthetic data, model alignment and RL | Christian Gibson: Supercomputers used in training frontier models | Devendra Chaplot: VLMs, RL, & Robotics | Ian O Connell: Infrastructure engineering | Jacob Menick: ML researcher | Joshua Gross: Products and research | Kurt Shuster: Reasoning | Kyle Luther: ML researcher | Lilian Weng: Research | Luke Metz: Research scientist and engineer | Mario Saltarelli: IT and Security leader | Myle Ott: AI researcher | Nikki Sommer: HRBP | Noah Shpak: ML Engineer, GPUs | Pia Santos: Executive Operations Leader | Randall Lin: Algorithms | Rowan Zellers: Realtime multimodal posttraining | Sam Schoenholz: Scaling, optimization | Sam Shleifer: Inference | Stephen Chen: Infrastructure engineer | Stephen Roller: Full-stack pre-training | Yinghai Lu: ML system engineer

#Cerebras | AI inference and training platform | Specialized AI chips | Wafer-scale engine (WSE) | 900,000 cores deliver high levels of parallelism required to train large-scale models faster and more efficiently | On-chip memory integration provides high-bandwidth access to data | Processing speeds exceeding 2,500 tokens per second | Real-time processing capabilities for autonomous systems, vehicles, devices

#NVidia | Dexterous robot development | Manipulating objects with precision, adaptability, and efficiency | Fine motor control, coordination, ability to handle a wide range of tasks, often in unstructured environments | Key aspects of robot dexterity include grip, manipulation, tactile sensitivity, agility, and coordination | Robot dexterity development for manufacturing, healthcare, logistics | Dexterity enabling automation in tasks that traditionally require human-like precision

#Untether AI | Accelerating AI inference | PCI-Express form factor and power envelope | Over 2 PetaOps per card | Accelerator card | AI chip | Intel backed | Toronto, Canada

#Field AI | Autonomous systems for machines deployed to fields | Off-road autonomy

#Komatsu | Manufacturer of construction, mining, forestry and industrial heavy equipment | Ouster lidar supplier for Komatsu suite of autonomous mining equipment offerings | Komatsu equipment with advanced 3D digital lidar sensors | Ouster sensors benefits: zone monitoring routine firmware updates | Autonomy stack to replace legacy 2D lidar systems with 3D lidar

#Unitree | Go2 robot | Self-developed 4D LIDAR L1 | 360°x90°hemispherical ultra-wide recognition | Super small blind spot | Minimum detection distance 0.05m | All-terrain recognizing | With L1 LiDAR and dedicated App, you can construct point cloud map within certain area, specify path for Go2 to move autonomously | Intelligent side-follow system: utilizing wireless vector positioning and control technology, positioning accuracy is technically upgraded by 50%, remote control distance is over 30m, combined with optimised obstacle avoidance strategy | Robot automatically connects to cloud-based OTA service upgrading its programs to continuously improve user experience | Wi-Fi6/Bluetooth/4G | 2h—4h battery endurance | 5m/s max running speed

#ARM | Advanced RISC Machines | RISC instruction set architectures (ISAs) for computers | ARM processors for portable, battery-powered devices, smartphones, embedded systems | SoftBank Group | AI ecosystem | Renesas | ResCon Technologies, LLC | GitLab | Embedl | Mapbox | Roofline | ENERZAi | 221e | AnchorZ Inc | Excelfore | ax Inc | weeteq | Eeasy Tech | Cerence AI | u-blox | SECO | Klepsydra Technologies | Ampere Computing | Senary Technology Limited | Ceva | Sensory | GitHub | Raspberry Pi Ltd | Untether AI | Eyeris | AiM Future, Inc | Dori AI | DeGirum Corp | OmniSpeech | ADLINK | Yobe | SLAMcore | Elliptic Labs AS | alwaysAI | Edge Impulse | SoundHound AI | Cyberon Corporation | Qeexo AutoML | Fortifyedge | TERAKI | NVIDIA | Neuton.AI | Aizip Inc | BrainChip | Roviero | RelaJet | Visidon

#NVIDIA | GPU Deep Learning | GPU acting as the brain of computing | Robots and self driving cars can perceive and unferstand the world | Accelerating the entire AI workflow | AI agents designed to reason, plan, and act | Conversational AI: multilingual speech and translation AI | Vision AI: multimodal real-time insights | AI factories: manufacturing intelligence at scale | Purpose-built AI factories | AI life-cycle | Humanoid robotics research and development platform | Machine Learning | Neural networks | Natural language processing | Speech recognition | Recommender systems | Biomedical image segmentation | Object detection | Image classification | Reinforcement learning

#John Deere | Deere Reports Net Income of $1.065 Billion for Fourth Quarter, $5.027 Billion for Fiscal Year | $3.93 per share | Outlook for small ag and construction and forestry improves | Worldwide net sales and revenues increased 11%, to $12.394 billion, for the fourth quarter of 2025 | Diverse customer segments and geographies | Continued commitment to delivering customer value | Focusing on operational efficiency | Remaining resilient | Demonstratung the strength of business | Commitment to inventory management and cost control | Expectung growth in small agriculture & turf and construction & forestry | Mowers | Tractors | Utility vehicles | Electric Equipment

#Aurora | Aurora Driver self-driving system designed to operate multiple vehicle types | Driver as a service products for trucking and ride-hailing | Self-driving stack into trucks from major OEM partners to operate around the clock on freight corridors | Proprietary lidar | Verifiable AI | Initial focus hub-to-hub long-haul freight trucks running between logistics hubs on repeatable highway routes | Partners: Detmar Logistics, Aumovio , FedEx , Hirschbach , NVIDIA , PACCAR , Ryder , Schneider ,Toyota ,Uber ,Uber Freight ,Volvo Trucks ,Volvo Autonomous Solutions, Werner