designed for modularity and scalability, supporting various protocols such as EtherCAT and Modbus. TACTUN enables rapid deployment of custom automation solutions through a user-friendly interface, facilitating seamless integration with existing systems. The platform emphasizes flexibility, allowing users to select hardware components and configure software functionalities without extensive programming knowledge, thus optimizing operational efficiency and reducing time-to-market.
RSF defines a common language for robot service capability, lifecycle operations, certification pathways, and service-provider networks.
MoSense, a company specializing in multimodal tactile solutions for robotics, has successfully completed an angel funding round worth several million yuan. Investors include Sequoia China, Hillhouse Capital, and Zhiyuan Robotics. The funds will primarily accelerate research and development, team expansion, computational power investment, and production testing system establishment. Founded in May 2026 and headquartered in Shanghai, with a research center in Shenzhen, MoSense focuses on developing a comprehensive multimodal tactile perception system for robots. The company aims to enhance robots' environmental perception capabilities, which are crucial for their deployment in complex real-world scenarios such as industrial manufacturing and logistics. Looking ahead, MoSense plans to commercialize its multimodal tactile solutions across various industries beyond humanoid robotics. The company is developing a tactile feedback system that integrates multiple sensory modalities, which is essential for improving robots' interaction with their environments. No further timeline was disclosed at the time of publication.
Robbyant, a company specializing in embodied AI under Ant Group, has unveiled the upgraded LingBot-VLA 2.0 model. This next-generation vision-language-action model enhances morphological generalization, degrees of freedom support, and deployment efficiency, addressing a critical gap in the embodied AI industry. The significance of LingBot-VLA 2.0 lies in its extensive pre-training on 60,000 hours of real-world data, which includes interactions from 20 different robot morphologies. This upgrade allows for improved whole-body control and dual-arm manipulation, achieving leading scores on benchmarks, thus demonstrating its effectiveness in industrial-scale deployment. Looking ahead, the introduction of a version optimized for efficient post-training and a threefold increase in inference efficiency positions LingBot-VLA 2.0 as a strong contender for real-time commercial applications. No further timeline was disclosed at the time of publication.
Computing Robot simulation artificial intelligence dual-arm robots embodied ai humanoid robotsWeRide has introduced WITT, a groundbreaking physical AI foundation model designed to enhance multimodal scene understanding. This model utilizes minimal physical fact units, which are crucial for applications in autonomous driving and robotics. The launch of WITT is significant as it aims to streamline the integration of various data types, improving the efficiency and effectiveness of AI systems in interpreting complex environments. This advancement could lead to more reliable autonomous systems that can better navigate real-world scenarios. Looking ahead, the implications of WITT's capabilities in the fields of autonomous driving and robotics will be closely monitored. No further timeline was disclosed at the time of publication.
TechnologyOn July 16, Qianjue Robotics unveiled its first embodied tactile model, X-TouchMind V1, alongside the TacVerse 1k multimodal dataset. This development addresses the limitations of traditional visual models in robotic operations, particularly in precision assembly and handling delicate objects, where failures often occur after contact. The new model integrates visual, linguistic, tactile, and robotic state data to enhance physical interaction capabilities. The significance of this release lies in Qianjue's comprehensive approach, which encompasses tactile perception hardware, self-developed multimodal data collection devices, and the new tactile model. Unlike previous attempts that merely supplemented tactile signals to visual data, the VTLA embodied tactile model establishes a closed-loop system that fundamentally redefines the perception boundaries of robotic models. This innovation allows robots to understand and respond to physical interactions more effectively. Looking ahead, Qianjue Robotics will demonstrate the capabilities of the VTLA model at the WAIC 2026 exhibition, showcasing real-world applications such as autonomous box stacking and precise assembly of headphones. The focus will be on how the model can dynamically adjust actions based on tactile feedback, marking a significant advancement in robotic interaction technology. No further timeline was disclosed at the time of publication.
Tactile Intelligence Robotic Interaction Precision Assembly Multimodal Data AI RoboticsRobotic systems are increasingly capable of perceiving, choosing, and altering their behavior autonomously, without human intervention. This shift towards autonomy enhances adaptability in various environments such as warehouses and labs, but it also raises significant concerns regarding safety and control. Traditional safety measures, including physical barriers and emergency buttons, may no longer suffice as robots undertake more complex tasks. The implications of this autonomy are profound, as organizations must now assess the quality of decisions made by autonomous systems, the reliability of their software, and the protocols for monitoring their actions. Unlike conventional robots that follow fixed commands, autonomous robots can evaluate multiple scenarios and make decisions based on real-time conditions, which complicates safety protocols. Ensuring that these systems operate safely requires a reevaluation of existing safety standards that focus on speed and force. Looking ahead, it is crucial for operators to have adequate information to respond effectively to unexpected robot behavior. Autonomous robots utilize various sensors to interpret their environment, but factors like dust and poor lighting can affect input quality. Organizations should prioritize the definition and testing of triggers for human intervention to maintain a balance between autonomy and safety. No further timeline was disclosed at the time of publication.
AI agents Infrastructure AI agent autonomy ai agents ai safety automationBrainCo, based in Hangzhou, has introduced a groundbreaking robot platform that allows users to control robots using only their thoughts through EEG headsets. This advancement signifies a major step forward in embodied AI technology, where artificial intelligence is integrated into physical machines, enabling them to interact with the real world. The significance of this development lies in its potential to revolutionize human-robot interaction. By utilizing electroencephalogram (EEG) headsets, BrainCo's platform captures brain signals and employs AI algorithms to decode these signals, translating user intentions into robotic actions. This capability could enhance various applications across industries, making robots more intuitive and responsive to human commands. Looking ahead, the platform's compatibility with diverse third-party hardware, including humanoid robots and robotic arms, suggests a wide range of potential use cases. As the competition among global technology firms intensifies in the realm of embodied AI, BrainCo's innovation will be crucial to monitor for its impact on the future of robotics and AI integration. No further timeline was disclosed at the time of publication.
KAIST and Korea University researchers have developed the KAIST HOUND robot, achieving a peak speed of 6m/s while autonomously navigating complex terrains. This advancement showcases the robot's ability to seamlessly switch gaits, such as trotting and bounding, based on environmental conditions without external support. The significance of this achievement lies in the innovative APT-RL framework, which utilizes a simplified 2D dynamics model to generate extensive motion data. This approach allows the robot to learn and adapt its movements in real-world 3D environments, overcoming traditional limitations of motion capture and reinforcement learning strategies. Looking ahead, the research team has demonstrated the robot's capability to handle various scenarios, including jumping and maintaining balance under challenging conditions. Future developments may focus on enhancing the perception system to support high-speed operations, as the current sensing technology has limitations in effective range.
Quadrupedal Robots Robotics Research Reinforcement Learning AI Autonomous SystemsAt the WAIC 2026, an immersive exhibition area titled 'The Era of Modeling: City of Partners' showcased over 20 robots performing various roles in manufacturing, daily life, and entertainment. Additionally, approximately 60 humanoid robots were deployed not as exhibits but as active participants in public service tasks, marking the first large-scale deployment of full-sized humanoid robots at such an event. This transition from being mere exhibits to functioning colleagues highlights the rapid advancements in contextual large models, which integrate multimodal information such as sound, visuals, and environment, significantly enhancing the interaction capabilities of robots. For instance, the tea-serving robot from Zhiyuan Innovation can perform a complete tea service task in six minutes, showcasing its refined operational capabilities. The WAIC 2026 featured an exhibition space exceeding 100,000 square meters, with 1,100 companies participating and over 3,000 exhibits, including more than 300 global product launches. The event signifies a shift in focus from showcasing AI as a technological spectacle to recognizing its role as a productive force in the real world, as noted by a visiting journalist who observed this change in emphasis from last year’s event.
Humanoid Robots AI Public Service Robotics Exhibitions AutomationThe QiYuan T1, a transformable personal robot, made its debut at the 2026 World Artificial Intelligence Conference in Shanghai. This innovative robot can autonomously switch between a humanoid form for indoor use and a quadrupedal 'robot dog' form for outdoor environments, adapting seamlessly to various terrains without manual intervention. This development is significant as it showcases advancements in robotics, particularly in the realm of personal companions. The QiYuan T1's ability to engage in human interaction through flexible force control technology enhances its role beyond mere task completion, allowing it to serve as a companion in daily life. Looking ahead, the QiYuan T1's unique design and capabilities may set new standards for personal robots. With ongoing investments in research and development, including a reported 4585.16 million yuan in Q1 2026, the company is poised to expand its presence with offline experience stores in cities like Shanghai and Shenzhen. No further timeline was disclosed at the time of publication.
Transformable Robots Personal Robotics AI Technology Consumer ElectronicsDuring a media briefing on July 15, Digua Robot's CEO, Wang Cong, stated that there are currently no industry standards for the computing power required for embodied intelligence chips. He emphasized the uncertainty surrounding chip performance, data standards, algorithms, and practical applications in the sector. Wang noted that Digua Robot is among the few companies already delivering products, having partnered with over 20 leading clients, including companies like Shizhi Navigation and UBTECH. Their Sun S600 chip is set to be deployed in various scenarios, including humanoid robots and industrial applications, with significant progress reported in the past six months. Looking ahead, Wang believes that the industry is not yet in a phase of intense competition, as many players have yet to produce viable products. He highlighted the importance of refining product quality and responding to customer needs, while also addressing the challenges of cost-effectiveness and system integration in deployment processes. No further timeline was disclosed at the time of publication.
Embodied Intelligence Chip Technology Robot Partnerships Industrial Automation
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