autonomoussystem.dev
#Autonomous System Development Meta
#Vector Database
#AI models deployed in embedded systems at edge | Brushless DC motors | Hall effect sensors | Optical encoders | Sensorless motor control | Field-oriented control | Artificial intelligence at edge | Three fundamental modalities: vision, sound, and motion | Using AI models to infer information about device environment | Linear algorithms | Software and hardware combination | Deploying multiple AI models in embedded devices requires edge processors designed to run AI | Embedded systems using AI can be considered open | Sensor fusion utilizes combined data from multiple sensors | AI-based vision systems are more adaptable to natural variations inherent in object inspection | Objects can be identified and inspected more quickly with greater flexibility | Strong multimodal AI, a single model will process multiple types of data | Control algorithms will use inputs generated by AI, inferred from multiple sources of data | AI inferencing in data flow | AI-enabled image sensors are perfect for gesture detection | Event detection based on sound is an active area of development | On device learning in real time
#Robot Operating System (ROS)
#GenerativeAI ecosystem
#Robotics Engineering
#Machine Learning
#Robot Integration
#Robot Comissioming
#Robot Testing
#Control Logic Integration
#Digital Twin Approach
#Robot Structural Analysis
#Robot Arm Analysis
#Robot Joint Analysis
#Robot Accuracy
#Robot Repeatability
#Robot Precision
#Structural Challenges
#Kinematics Challenges
#Thermal Challenges
#Durability Challenges
#Generative AI ecosystem Stack
#Reasoning
#Planning
#Improving Performance Over Time
#Marine Industry
#AI factory | Manufacturing intelligence at scale | Purpose-built AI factory | Pretraining scaling: skilled experts, data curation | Post-training scaling: fine-tuning AI models | Test-time scaling: iterative reasoning | AI factory stack: from silucon to software
#Energy
#Transportation
#Automotive
#Machinery Operating
#DevOps Engineering Linux
#Jenkins
#Docker
#Ansible
#Robot framework
#Autonomous Facility
#Autonomous Bay
#Intelligent autonomy
#Autonomous air vehicle
#Motion capture system
#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
#Learning Management System (LMS)
#Shell-AI | LangChain | LLM
#CLI utility
#Llama
#AI inference technology
#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
#A-list celebrity home protector | Burglaries targeting high-end items | Burglary report on Lime Orchard Road | Burglar had smashed glass door of residence | Ransacked home and fled | Couple were not home at the time | Unknown whether any items were taken | Lime Orchard Road is within Hidden Valley gated community of Los Angeles in Beverly Hills | Penelope Cruz, Cameron Diaz, Jennifer Lawrence, Adele and Katy Perry have purchased homes there, in addition to Kidman and Urban | Kidman and Urban bought their home for $4.7 million in 2008 | 4,100-square-foot, five-bedroom home built in 1965 and sits on 1ΒΌ-acre lot | Property large windows have views of the canyons | Theirs is one of several celebrity properties burglarized in Los Angeles and across country recently | Connected to South American organized-theft rings
#Professional athlete home protector | South American crime rings | Targeting wealthy Southern California neighborhoods for sophisticated home burglaries | Behind burglaries at homes of professional athletes and celebrities | Theft groups conduct extensive research before plotting burglaries | Monitoring target whereabouts and weekly routines via social media | Tracking travel and schedules | Conducting physical surveillance at homes | Attacks staged while targets and their families are away | Robbers aware of where valuables are stored in homes prior to staging break-ins | Burglaries conducted in short amount of time | Bypass alarm systems | Use Wi-Fi jammers to block Wi-Fi connections | Disable devices | Cover security cameras | Obfuscate identities
#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
#ComfyUI | Automation engine that helps accomplish a creative task
#API Nodes | Natively integrated nodes in Comfy that can call paid model API like Veo2 or Flux Ultra
#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
#Embedding differentiable graphics into AI training | Teaching AI how to generate 3D worlds from images | Creating high-quality synthetic datasets | Realistic simulation environments | Training and testing AI for the real world
#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
#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
#Immediate.Measures to Increase American Mineral Production
#Robot offline programming (OLP) | Robot programming outside of production system without stopping production | With offline programming, operator can view product in CAD model, enabling welding of internal, hidden areas with robot | Generating programs fast in virtual robot cells from anywhere in the world | Repeatable quality with accuracy and minimal waste | Software validated and optimized programs | Process knowledge database | Virtual models of the production | Mastering complex welding quality and efficiency | Delivering customized, modular machines faster and with higher quality | Customization makes automation and flexible robot programming critical for maintaining productivity | Offline programming expertise of Delfoi Robotics | Visual Components platform | OLP is utilized not only when introducing new products but also in refining existing programs | Visual Components used as a layout design tool | Modeling digital replica of the welding station with software and testing welding possibilities | Doing all programs before machine itself has arrived in factory | After robot installation calibrate, touch up, and upload them to robot controller | Commissioning, involves calibration of designed robot cell for accuracy, ensuring that programs function accurately for a faster production ramp up | Ponsse: harvesters, robotic welding station | Duun Industrier: Norwegian heavy machinery manufacturer, robotic welding station, database optimizing welding procedures in Welding Procedure Specification (WPS) library making it easy to replicate best practices across different products |.Sandvik Mining: manufactures heavy-duty underground loaders and trucks with complex, multi-pass welds, uses IGM and Yaskawa welding robots | Canatu: develops and manufactures advanced carbon nanotubes, along with related products | Pintos: manufacturing of steel reinforcements | Photocentric: manufacturer specializing in photopolymers | Meconet: high-quality metal components | Valmet: process technology, automation solutions and services for pulp, paper and energy industries | Ouman: building automation and energy efficiency for properties | Casemet: steel enclosure solutions | Koja: air handling and fan solutions for ships and buildings | Mulberry: luxury leather goods | MSK Plast: custom-made plastic parts | Delroi targets manufacturing companies across U.S. and Canada | Delfoi collaborates with Oracle, SAP, and Microsoft
#X Processing Unit (XPU) | AI accelerator purpose-built and customized for specific types of AI processing functions | Driving the next wave of AI infrastructure deployment | Monitoring the health of the AI fabric in real time | Close to 100 different GPU and xPU architectures and variations being released | Hyperscalers and large cloud operators need to deploy many architectures to optimally serve diverse workloads | Vendors need to diversify their platforms with different types of AI computing solutions purpose-built for AI applications | Intelligent connectivity platform specifically based on open standards | Ultra Accelerator Link standard | Products helping extend signal reach | Fabric switches that allow chips to talk to each other | AI Infrastructure 2.0 focused on open connectivity standards | Optical connectivity | Optimized AI infrastructure deployment
#Silicon Photonics | Chip-scale implementation of opto-electronic systems on silicon substrates | Electro-optic transceivers in both the short distance datacom and high-performance coherent optical communications segments | Light detection and ranging, LiDAR | Optical coherence tomography | Material integration | Advanced assembly concepts | Advanced signal processing schemes | Emerging applications in biology | Emerging computation platforms | aiXscale Photonics spin off
#Robotics development platform | Autonomous mobile robots (AMRs) | Robot arms | Manipulators | Humanoids | Simulation | Robot learning frameworks | GPU accelerated libraries | AI models | Reference workflows