autonomousvehicle.dev

#Autonomous Vehicle Development Meta

#Artficial Intelligence

#Feedback Relaying From City

#Feedback From Other Sensors

#Connected Trasportation Ecosystem

#Learning Digital Twins

#Consistency Ensuring

#Leveragig Real World Measurements

#Correlating Virtual World Scenarios

#Sensor Fusion

#Collaboration Between Cities

#Moving Vehicle To Different City

#Route Planning

#Traffic Management

#Portfolios For Autonoous Vehicles

#Refreshing Vehicle Software

#Training Algoritms

#Data Labelling

#New Logistics Possibiities

#New Mobility

#Delivery Trucks

#Self Driving Taxi Drives

#Data Fusion Fro Mutiple Sensors

#High Definition Mapping

#AI Enabled Sensors

#Machine Learning

#3D Printing

#Robotics

#Low Cost Sensors To Generate Data

#Hydrogen Fuel Cell

#Liquid Hydrogen

#Electric Vehicle

#Patrol Boat Autonomy

#Autonomous Vessel

#Vision for Off-Road Autonomy (VORA)

#Vehicle-platform agnostic technology

#Intelligent autonomous behavior

#Throttle Control

#Brake Control

#Perceive

#Predict

#Obstacle Avoidance

#Hitching

#Docking

#Convoy Operations

#Remote Operations

#Precision agriculture

#Multi-orbit internet access

#Voltage

#Current

#Sealing

#Vibration

#Temperature

#Emectromagnetic radiation

#Electromagnetic interference (EMI)

#1550nm LiDAR | Advantages: safety, range, and performance in various environmental conditions | Enhanced Eye Safety: absorbed more efficiently by cornea and lens of eye, preventing light from reaching sensitive retina | Longer Detection Range | Improved Performance in Adverse Weather Conditions such as as fog, rain, or dust | Reduced Interference from Sunlight and Other Light Sources | More expensive due to complexity and lower production volumes of their components

#SLAM | Simultaneous Localization and Mapping

#ADAS | Advanced Driver-Assistance Systems

#Vector database

#Electric trailer

#E-axle

#Emissions

#Sustainability

#Emission standard

#Heavy-duty vehicle

#Vehicle Energy Consumption Calculation Tool (VECTO)

#Resistive RAM (ReRAM) technology | onsemi Treo platform to provide embedded non-volatile memory | ReRAM integration into Bipolar CMOS DMOS (BCD) process | Potential alternative to flash memory | Demand for faster, more efficient, and scalable memory solutions increasing | Lower power consumption | Less vulnerable to common hacking tactics | ReRAM can be integrated easily into chip designs without interfering with power analog components

#Figma variables

#Off-highway truck

#Autonomous machines in construction

#Off-highway truck technology

#360-degree surround cameras with object detection

#Electronic powertrain controls

#Automatically detecting hazards within critical areas around vehicle

#Ability to access and analyse accurate real-time data from vehicle

#Access to the latest software updates

#Vehicle software updates scheduled and executed at a time that does not interrupt the production schedule

#Remote Troubleshoot enabling dealer to perform diagnostics remotely while vehicle is still in operation

#ROS 2 | The second version of the Robot Operating System | Communication, compatibility with other operating systems | Authentication and encryption mechanisms | Works natively on Linux, Windows, and macOS | Fast RTPS based on DDS (Data Distribution Service) | Programming languages: C++, Python, Rust

#Dexterous robot | Manipulate objects with precision, adaptability, and efficiency | Dexterity involves 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 is crucial in: manufacturing, healthcare, logistics | Dexterity enables automation in tasks that traditionally require human-like precision

#Agentic AI | Artificial intelligence systems with a degree of autonomy, enabling them to make decisions, take actions, and learn from experiences to achieve specific goals, often with minimal human intervention | Agentic AI systems are designed to operate independently, unlike traditional AI models that rely on predefined instructions or prompts | Reinforcement learning (RL) | Deep neural network (DNN) | Multi-agent system (MAS) | Goal-setting algorithm | Adaptive learning algorithm | Agentic agents focus on autonomy and real-time decision-making in complex scenarios | Ability to determine intent and outcome of processes | Planning and adapting to changes | Ability to self-refine and update instructions without outside intervention | Full autonomy requires creativity and ability to anticipate changing needs before they occur proactively | Agentic AI benefits Industry 4.0 facilities monitoring machinery in real time, predicting failures, scheduling maintenance, reducing downtime, and optimizing asset availability, enabling continuous process optimization, minimizing waste, and enhancing operational efficiency

#Field Foundation Model (FFMs) | Physical world model using sensor data as an input | Field AI robots can understand how to move in world, rather than just where to move | Very heavy probabilistic modeling | World modeling becomes by-product of Field AI.robots operating in the world rather than prerequisite for that operation | Aim is to just deploy robot, with no training time needed | Autonomous robotic systems applucations | Field AI is software company making sensor payloads that integrate with their autonomy software | Autonomous humanoid Field AI can do | Focus on platforms that are more affordable | Integrating mobility with high-level planning, decision making, and mission execution | Potential to take advantage of relatively inexpensive robots is what is going to make the biggest difference toward Field AI commercial success

#Precision robotics | Autonomous farming | Retrofitting onto existing machines | Vision-based autonomy software | Automotive-grade sensors and compute | Over-the-air software updates

#Large Language Model (LLM) | Foundational LLM: ex Wikipedia in all its languages fed to LLM one word at a time | LLM is trained to predict the next word most likely to appear in that context | LLM intellugence is based on its ability to predict what comes next in a sentence | LLMs are amazing artifacts, containing a model of all of language, on a scale no human could conceive or visualize | LLMs do not apply any value to information, or truthfulness of sentences and paragraphs they have learned to produce | LLMs are powerful pattern-matching machines but lack human-like understanding, common sense, or ethical reasoning | LLMs produce merely a statistically probable sequence of words based on their training | LLMs are very good at summarizing | Inappropriate use of LLMs as search engines has produced lots of unhappy results | LLM output follows path of most likely words and assembles them into sentences | Pathological liars as a source for information | Incredibly good at turning pre-existing information into words | Give them facts and let them explain or impart them

#Retrieval Augmented Generation. (RAG LLM) | Designed for answering queries in a specific subject, for example, how to operate a particular appliance, tool, or type of machinery | LLM takes as much textual information about subject, user manuals and then pre-process it into small chunks containing few specific facts | When user asks question, software system identifies chunk of text which is most likely to contain answer | Question and answer are then fed to LLM, which generates human-language answer in response to query | Enforcing factualness on LLMs

#Smart electric vehicle technology | XPENG | AI-driven mobility company | Designs, develops, manufactures, and markets Smart EVs | Catering to tech-savvy consumers | Develops Full-stack advanced driver-assistance system (ADAS) technology | Intelligent in-car operating system | Xmart OS: from driving cockpit to intelligent space | XPILOT ASSIST: Intelligent driving assistance-Easy to drive, easy to park | Over the air software update (OTA) | AI-powered production car equipped with an L3-grade computing platform | Effective computing power exceeding 2000 TOPS | Onboard deployment of VLA (Vision-Language Action) + VLM (Vision-Language Motion) models | Autonomous driving research | Large-scale fleets | Vast real-world data | Data-driven era |

#Vision-language model (VLM) | Training vision models when labeled data unavailable | Techniques enabling robots to determine appropriate actions in novel situations | LLMs used as visual reasoning coordinators | Using multiple task-specific models