Follow Biteye and unlock the rising stars in the Web 3 robot track!
1. @openmind_agiKeywords: operating system, decentralized coordination layer
OpenMind has raised $20 million in funding, hoping to improve robots’ understanding and learning capabilities through open source systems. Its main products include:
OM 1: An AI-native operating system, known as the “Android for robots,” is hardware-independent and open source. It empowers machines with perception, memory, planning, and control capabilities, helping them understand the world and take contextually relevant actions. A previous hackathon participant used OM 1 to build an Alzheimer’s care robot in 48 hours.
FABRIC: A decentralized coordination layer. Through blockchain, it allows robots to share data, rapidly learn (e.g., language), and support consensus, execution, and settlement.
2. @peaqKeywords: Layer 1, Machine Economy
peaq has raised $21 million and is a Layer 1 focused on DePIN and machine economy.
Peaq enables robots, drones, sensors, and other machine devices to obtain self-sovereign IDs on the blockchain, conduct peer-to-peer payments, store data, and automate operations. This enables use cases such as robot rentals, drone deliveries, and autonomous machine collaboration, building a complete “machine economy” where robots and other devices can earn money and interact independently, just like AI agents.
Built on the Substrate framework and compatible with Polkadot, the project has connected to over 90 blockchains. Currently, there are over 50 DePIN projects on the peaq chain, including Silencio (noise monitoring), MapMetrics (earning money while driving), Farmsent (agricultural supply chain), and Natix (intelligent driving). The network connects over 4.5 million devices and machines, providing decentralized network services for over 20 industries, including energy, mobility, transportation, agriculture, and the environment.
3. @GEODNET_Keywords: Real-time Positioning Network
GEODNET has raised $15 million and focuses on positioning services – building the world’s largest real-time kinematic (RTK) positioning network in a decentralized manner, providing centimeter-level accuracy global navigation satellite system (GNSS) services.
The project was originally built on Polygon and has now expanded to Solana.
The network allows anyone to purchase and install GEODNET’s hardware mining equipment (“satellite miners”), collect and upload RTK correction data to the network, earn asset rewards, and ultimately enable the network to provide high-precision positioning support for applications such as robots, autonomous vehicles, drones, and the मेटावर्स.
The network currently covers 145 countries, more than 19,000 sites, and has delivered more than 207,178 GB of RTK data.
4. @psdnai Keywords: Physical Data CollectionPoseidon was incubated by @StoryProtocol and raised $15 million in seed funding. It mainly addresses the shortage of training data at the physical level of displays for applications such as robots and multimodal AI agents.
Poseidon has built a decentralized data layer based on Story to collect, organize, and manage real-world data (such as video, audio, images, location, etc.), ultimately providing IP-protected training data to help accelerate innovation in AI models.
The APP is currently online, starting with sound information, allowing users to upload sound information in the APP to train the AI model so that it can process speech in different accents, dialects and environments.
5. @PrismaXaiKeywords: Tele-op, training data
PrismaX, led by CSX, has raised $11 million in funding. The company aims to help robots achieve a high degree of autonomy through human intervention.
The tele-op platform currently available allows users to remotely operate robotic arms through a browser, converting this operational data into high-quality training data for model optimization. Operators will receive platform token rewards during this process.
The platform is expected to be able to remotely connect to many well-known robots such as Yushu and UBTECH in the future.
In the short term, we will focus on remote control and visual data for model training;
In the medium term, robots will be able to complete actual tasks through remote human control;
In the long run, the ultimate goal is to achieve complete or high autonomy of robots.
6. @NRNAgentsKeywords: Tele-op, reinforcement learning, AI Agent
NRN Agents is a decentralized AI agent development and training platform running on Arbitrum. Initially focused on AI agents in games, the platform is expanding to AI agents behind embodied robots. Through a “Sim-to-Real” framework, NRN Agents provides efficient training and deployment solutions for robotic AI agents.
Users can directly control the simulated robot through the browser, and each operation generates high-quality behavioral data, providing training materials for imitation learning for the robot system. At the same time, the AI agent in the system can also be continuously optimized based on real-world interactions through reinforcement learning, without the need for complete retraining.
The project is currently in its early stages, focusing primarily on the operation of the robotic arm (RME-1). Future developments will include the robot’s combat capabilities, athletics, and other competitive sports.
7. @AukiNetwork Keywords: DePIN network, physical world data, positioning dataAuki Network aims to build a decentralized neural network for robots and intelligent machines, giving them a deeper understanding of the physical world. Its core business is to build a DePIN network that allows various devices (such as robots and smart glasses) to share location and perception data in real time, forming a collaborative spatial understanding.
The network, based on the Posemesh protocol, comprises compute nodes that provide computing resources; motion nodes, composed of intelligent devices such as robots that provide motion and sensor data; reconstruction nodes that use the former and latter to generate 3D maps or spatial models; and domain name nodes that manage these 3D spaces. These nodes receive asset rewards based on their contributions.
8. @RoboStack_ioKeywords: Abstracting hardware complexity, simplifying hardware and software integration
RoboStack is a cloud-native simulation and integration platform. It not only provides realistic environment modeling and scalable computing infrastructure for robot development and deployment, but also establishes a standardized communication protocol through the Robot Context Protocol (RCP) across diverse hardware, software, and communication standards, simplifying the connection between underlying robot hardware and AI agents at the software level.
ROBOT Coin has been launched on the virtuals platform. Users can participate in staking on virtuals and vote for their favorite robot projects in SIM lord to have a chance to win rewards.
9. @frodobotsKeywords: sidewalk robot
FrodoBots Lab is a robotics lab that uses gamification to promote real-world data collection and the development of embodied intelligence. Its core product, the Earth Rover, is a remote-controlled sidewalk robot (a robot that walks on sidewalks), priced between $249 and $399. It can be used for gaming, data collection, and AI research. FrodoBots has deployed hundreds of Earth Rovers worldwide and has open-sourced 2,000 hours of real-world driving data.
FrodoBots has built an ecosystem that integrates entertainment and scientific research through innovative robotic hardware, a decentralized platform, and an AI framework. The following are its main projects:
10. @BitRobotNetwork Keywords: decentralized subnet architectureThe BitRobot Network, a decentralized platform built on Solana and jointly developed by FrodoBots Lab and Protocol Labs, has secured $6 million in funding. The network utilizes a subnet architecture, with each subnet contributing specific resources such as computing power, a fleet of robots, datasets (real or synthetic), or AI models. These subnets cover a wide range of form factors, from sidewalk robots to humanoid robots. The first subnet, ET Fuji, has launched and is described in detail below.
11. @ET_FugiKeywords: Games, Remote Control Platform Tele-op
ET Fugi (Extra-Terrestrial Fugitives) is a real-world robotics game where players remotely control the Earth Rover to capture “alien” एनएफटी, while generating valuable sidewalk data for robot AI training and earning rewards such as FrodoBots Points (FBP).
12. @samismoving Keywords: AI Agent, Framework SAM collects operational data through Earth Rover to improve the overall AI agent’s capabilities. It also livestreams portions of its adventures via X (Twitter), showcasing specific interactions, competitions, and data collection scenarios, providing both entertainment and educational value.SAM was originally developed by FrodoBots and @virtuals_io as an AI agent for remotely operating the Earth Rover. It later evolved into the core framework for launching AI agents on the Robots.Fun (Launchpad) platform. All subsequent AI agents are built on SAM’s architecture and pay a 5% commission to it.
13. @robotsdotfunKeywords: AI Agent Launch Platform
Robots.Fun is a launchpad for robotic AI agents. It collects data and strengthens AI agents through daily competitions (such as capturing alien NFTs). To create an AI agent on Robots.Fun, you must own or purchase an Earth Rover robot, which serves as the “body” of your AI agent.
14. @UFBotsKeywords: Robot fighting, remote control platform Tele-op
Ultimate Fighting Bots is a free robot battle club where users remotely control humanoid robots based on Booster T 1 to engage in combat. The platform generates real-world data for training embodied AI while providing users with an immersive entertainment experience.
15. SummaryAfter understanding the above projects, we can clearly see the two core advantages of the Web 3 robot track:
1. The decentralized advantage of blockchain is expected to break the scarcity barrier of robot models and data.
2. The on-chain ownership confirmation and incentive mechanism has injected new vitality and sustainability into the robotics economy.
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