autonomousvehicle.app

#Autonomous Vehicle Application Meta

#Autonomous hauler | Mining | Transporting ore and waste material | Sensors for path planning, obstacle avoidance, and GPS tracking | Multiple haulers work together as connected fleet with fleet management systems

#Camshaft position sensor | Monitoring camshaft position and speed | Working alongside crankshaft sensor | Providing engine control unit (ECU) with precise data for controlling ignition timing, fuel injection, and valve operation

#Engine control unit (ECU)

#Crankshaft sensor

#Crankshaft

#Camshaft | Controlling opening and closing of engine valves | Turning open valves at precise times during engine cycle | Timing is synchronized with crankshaft to ensure to ensure optimal engine performance and prevent damage | Regulating air and fuel intake as well as exhaust gas expulsion

#Ignition coil harness detector | Diagnosing issues with ignition coil wiring harness | Common symptoms of faulty ignition wiring harness include engine misfires, inconsistent startups, and voltage spikes in ignition coil

#Sequences Of Maneuvers

#Coordinated Task

#Planning Ahead

#Multi Step Strategy

#Autonomous Operation

#Imaging Potential Outcomes

#Anticipating Potential Problems

#Setting Course Of Action

#Minimizing Dangers

#Maximizing Speed

#Maximizing Reliability

#Electric Excavator

#Stronger Emission Regulation

#Sustainability In Building

#Zero Emissions

#Near Silence

#Fewer Vibrations

#Electric Combat Equipment

#Integrated On Board Charger

#Expected Operation Time Calculation

#Productivity Level

#Noise Sensitive Theater

#Driving Connectedness

#Autonomous Base Returning

#Autonomous Ground Vehicle | AGV | Warehouse Product Handling Tracking And Movement

#Braking Mechanism

#SLAM | Simultaneous Localization and Mapping

#Learning Management System (LMS)

#California Wildfire sensing | Fast moving flames | Smoke filled canyons | Santa Ana winds | Fire map | Firefighters | Evacuation zone | Power shutoff | Death tol | Firefighting personnel | Damage | Economic loss | Evacuation orders | Evacuation warnings | Brush fire | Recycled water irrigation reservoir | Animals relocated | Evacuation alert | Schools closed | Fires fueled by hurricane-force winds | Schools to be inspected and cleaned outside and in, and their filters must be changed | Feeding centers | Hilly areas | Evacuation bag: solar-powered charger, mask, extra clothing | Drone interfering with wildfire response hit plane | Structure: home, multifamily residence, outbuilding, vehicle | Beachfront properties destroyed | Looting | Curfew | Red Cross

#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