Technology peripherals
AI
'Among the top ten important robotics technology development trends, humanoid robots are indispensable'
'Among the top ten important robotics technology development trends, humanoid robots are indispensable'
Emerging robotics technology can meet people's growing needs for industrial automation, digitization, and sustainability. For example, material handling in warehouses can be automated using autonomous mobile robots (AMRs) and automated guided vehicles (AGVs).
The research institution recently conducted an in-depth study of the insights of 8,949 start-ups and large enterprises around the world on the development of robotics technology, and made predictions about the development trends of robotics technology in 2023. Industry experts point out that people need to understand and follow robotics trends that have the potential to transform businesses.
The following are the top ten robot trends and predictions for 2023 derived from the study:
1. Autonomous Mobile Robots (AMR)
In manufacturing, workers often work in hazardous environments such as toxic chemicals, confined spaces, or heavy machinery. Autonomous mobile robots use sensors, artificial intelligence and computer vision technology to observe and understand their surroundings and navigate autonomously. For example, autonomous mobile robots (AMRs) in warehouses use scanners to monitor inventory levels and automate material handling and prevent inventory depletion. To speed up work, autonomous mobile robots can also transport components and parts over long distances within factories.
2. Intelligent robot
Due to the combination of artificial intelligence and robotics, intelligent robots can use real-time information to optimize their work. Large datasets and real-time data are also used to train robots to become more accurate and effective. As a result, they are able to better perceive their surroundings, distinguish objects more quickly, and navigate independently.
3. Collaborative robots
Compared with traditional industrial robots, collaborative robots have advanced sensors and algorithms. They work with workers and must ensure that their surroundings Safety of personnel. To automate production activities such as welding parts and drilling holes, they primarily employ end-of-arm tooling (EOAT) operations. These robots help workers move hazardous items such as metal products, polymers and other materials.
4. Robots as a Service
The development and maintenance of robots is a costly and time-consuming process. Due to these constraints, many businesses, especially small ones, are unable to integrate robotics into their operations and need to use Robots-as-a-Service.
5. Robot Cybersecurity
Due to the integration of IoT and the increase in connectivity requirements, robots have become the main target of cyber attacks. Additionally, due to their widespread use in the defense, manufacturing, healthcare, and aerospace industries, robots must be protected from illegal access and intrusion. Adopting a robotic cybersecurity solution protects endpoints and connectivity stacks to prevent data breaches and asset outages.
6. Drones
Thanks to the development of edge computing, high-performance computing and network technology, startups are now able to build drones with greater range and capabilities. machine. They use drones to deliver goods, collect aerial data, inspect infrastructure, and do a wide variety of operations. Drones used in agriculture can spray pesticides and sow seeds at specific locations while monitoring crop growth and tracking the movement of livestock. The adaptability of drones has accelerated integration in last-mile transportation of things like food and medical supplies.
7. Internet of Things
If robotics focuses on manufacturing, interaction and autonomous behavior, the Internet of Things provides sensing, monitoring and tracking functions. The robot's performance is driven by an edge computing platform, which enables feedback-driven workflows by collecting and sending data. Thanks to recent advances in edge IoT, robot manufacturers are now able to move computing closer to the data source. This allows the robot to use nearly real-time data and maximize work efficiency.
8. Humanoid robots
In the post-epidemic era, humanoid robots are increasingly used for non-contact cleaning and patient care. In addition, they are used in power plant inspections, maintenance and post-disaster recovery operations to rescue workers from hazardous environments. In addition to greeting guests at the front desk, humanoid robots will also look after the sick and elderly. They, like other robots, automate work to reduce expenses and boost production.
9. Automated Guided Vehicles
In warehouses, distribution centers and production facilities, materials are often transported by automated guided vehicles. Their movement is controlled by software and a sensor-based navigation system that follows a predetermined path.
10. Assistive Robots
More and more people will benefit from the independence and higher quality of life provided by assistive robots. To sense, process and communicate with humans, assistive robots use sensors and smart algorithms to allow people to live independently and safely in their own homes.
The above is the detailed content of 'Among the top ten important robotics technology development trends, humanoid robots are indispensable'. For more information, please follow other related articles on the PHP Chinese website!
Hot AI Tools
Undresser.AI Undress
AI-powered app for creating realistic nude photos
AI Clothes Remover
Online AI tool for removing clothes from photos.
Undress AI Tool
Undress images for free
Clothoff.io
AI clothes remover
Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!
Hot Article
Hot Tools
Notepad++7.3.1
Easy-to-use and free code editor
SublimeText3 Chinese version
Chinese version, very easy to use
Zend Studio 13.0.1
Powerful PHP integrated development environment
Dreamweaver CS6
Visual web development tools
SublimeText3 Mac version
God-level code editing software (SublimeText3)
Hot Topics
Bytedance Cutting launches SVIP super membership: 499 yuan for continuous annual subscription, providing a variety of AI functions
Jun 28, 2024 am 03:51 AM
This site reported on June 27 that Jianying is a video editing software developed by FaceMeng Technology, a subsidiary of ByteDance. It relies on the Douyin platform and basically produces short video content for users of the platform. It is compatible with iOS, Android, and Windows. , MacOS and other operating systems. Jianying officially announced the upgrade of its membership system and launched a new SVIP, which includes a variety of AI black technologies, such as intelligent translation, intelligent highlighting, intelligent packaging, digital human synthesis, etc. In terms of price, the monthly fee for clipping SVIP is 79 yuan, the annual fee is 599 yuan (note on this site: equivalent to 49.9 yuan per month), the continuous monthly subscription is 59 yuan per month, and the continuous annual subscription is 499 yuan per year (equivalent to 41.6 yuan per month) . In addition, the cut official also stated that in order to improve the user experience, those who have subscribed to the original VIP
Context-augmented AI coding assistant using Rag and Sem-Rag
Jun 10, 2024 am 11:08 AM
Improve developer productivity, efficiency, and accuracy by incorporating retrieval-enhanced generation and semantic memory into AI coding assistants. Translated from EnhancingAICodingAssistantswithContextUsingRAGandSEM-RAG, author JanakiramMSV. While basic AI programming assistants are naturally helpful, they often fail to provide the most relevant and correct code suggestions because they rely on a general understanding of the software language and the most common patterns of writing software. The code generated by these coding assistants is suitable for solving the problems they are responsible for solving, but often does not conform to the coding standards, conventions and styles of the individual teams. This often results in suggestions that need to be modified or refined in order for the code to be accepted into the application
Seven Cool GenAI & LLM Technical Interview Questions
Jun 07, 2024 am 10:06 AM
To learn more about AIGC, please visit: 51CTOAI.x Community https://www.51cto.com/aigc/Translator|Jingyan Reviewer|Chonglou is different from the traditional question bank that can be seen everywhere on the Internet. These questions It requires thinking outside the box. Large Language Models (LLMs) are increasingly important in the fields of data science, generative artificial intelligence (GenAI), and artificial intelligence. These complex algorithms enhance human skills and drive efficiency and innovation in many industries, becoming the key for companies to remain competitive. LLM has a wide range of applications. It can be used in fields such as natural language processing, text generation, speech recognition and recommendation systems. By learning from large amounts of data, LLM is able to generate text
Can fine-tuning really allow LLM to learn new things: introducing new knowledge may make the model produce more hallucinations
Jun 11, 2024 pm 03:57 PM
Large Language Models (LLMs) are trained on huge text databases, where they acquire large amounts of real-world knowledge. This knowledge is embedded into their parameters and can then be used when needed. The knowledge of these models is "reified" at the end of training. At the end of pre-training, the model actually stops learning. Align or fine-tune the model to learn how to leverage this knowledge and respond more naturally to user questions. But sometimes model knowledge is not enough, and although the model can access external content through RAG, it is considered beneficial to adapt the model to new domains through fine-tuning. This fine-tuning is performed using input from human annotators or other LLM creations, where the model encounters additional real-world knowledge and integrates it
Five schools of machine learning you don't know about
Jun 05, 2024 pm 08:51 PM
Machine learning is an important branch of artificial intelligence that gives computers the ability to learn from data and improve their capabilities without being explicitly programmed. Machine learning has a wide range of applications in various fields, from image recognition and natural language processing to recommendation systems and fraud detection, and it is changing the way we live. There are many different methods and theories in the field of machine learning, among which the five most influential methods are called the "Five Schools of Machine Learning". The five major schools are the symbolic school, the connectionist school, the evolutionary school, the Bayesian school and the analogy school. 1. Symbolism, also known as symbolism, emphasizes the use of symbols for logical reasoning and expression of knowledge. This school of thought believes that learning is a process of reverse deduction, through existing
To provide a new scientific and complex question answering benchmark and evaluation system for large models, UNSW, Argonne, University of Chicago and other institutions jointly launched the SciQAG framework
Jul 25, 2024 am 06:42 AM
Editor |ScienceAI Question Answering (QA) data set plays a vital role in promoting natural language processing (NLP) research. High-quality QA data sets can not only be used to fine-tune models, but also effectively evaluate the capabilities of large language models (LLM), especially the ability to understand and reason about scientific knowledge. Although there are currently many scientific QA data sets covering medicine, chemistry, biology and other fields, these data sets still have some shortcomings. First, the data form is relatively simple, most of which are multiple-choice questions. They are easy to evaluate, but limit the model's answer selection range and cannot fully test the model's ability to answer scientific questions. In contrast, open-ended Q&A
SK Hynix will display new AI-related products on August 6: 12-layer HBM3E, 321-high NAND, etc.
Aug 01, 2024 pm 09:40 PM
According to news from this site on August 1, SK Hynix released a blog post today (August 1), announcing that it will attend the Global Semiconductor Memory Summit FMS2024 to be held in Santa Clara, California, USA from August 6 to 8, showcasing many new technologies. generation product. Introduction to the Future Memory and Storage Summit (FutureMemoryandStorage), formerly the Flash Memory Summit (FlashMemorySummit) mainly for NAND suppliers, in the context of increasing attention to artificial intelligence technology, this year was renamed the Future Memory and Storage Summit (FutureMemoryandStorage) to invite DRAM and storage vendors and many more players. New product SK hynix launched last year
SOTA performance, Xiamen multi-modal protein-ligand affinity prediction AI method, combines molecular surface information for the first time
Jul 17, 2024 pm 06:37 PM
Editor | KX In the field of drug research and development, accurately and effectively predicting the binding affinity of proteins and ligands is crucial for drug screening and optimization. However, current studies do not take into account the important role of molecular surface information in protein-ligand interactions. Based on this, researchers from Xiamen University proposed a novel multi-modal feature extraction (MFE) framework, which for the first time combines information on protein surface, 3D structure and sequence, and uses a cross-attention mechanism to compare different modalities. feature alignment. Experimental results demonstrate that this method achieves state-of-the-art performance in predicting protein-ligand binding affinities. Furthermore, ablation studies demonstrate the effectiveness and necessity of protein surface information and multimodal feature alignment within this framework. Related research begins with "S
