《商道创投网》2025年8月5日从官方获悉：帕西尼近日完成了由京东战略领投，浦耀信晔、宏兆基金、 张科垚坤、新国都、北京昌平先进能源制造产业直投基金、财鑫资本、复琢投资联合跟投的10亿元A轮 融资；湖南财信产业基金、钧犀资本、TCL创投、毅达资本等老股东持续加码，庚辛资本中国继续担任 独家战略财务顾问。 《商道创投网》创业家会员·单位简介： 《商道创投网》创业家会员·本轮融资用途是什么？ 帕西尼创始人兼CEO许晋诚表示："本轮资金将主要用于三方面：一是继续加大霍尔阵列芯片与触觉传 感器的迭代研发投入，突破更高集成度与更低功耗；二是扩建Super EID Factory，提升数据采集规模与 质量，夯实具身智能数据底座；三是携手京东、比亚迪等产业伙伴，加速在智能物流、汽车制造、医疗 康养等场景的规模化落地，推动触觉感知成为机器人标配。" 《商道创投网》创投家会员·本轮投资原因是什么？ 京东集团副总裁、京东战投负责人胡宁峰表示："京东坚定布局未来实体智能，帕西尼拥有全球领先的 触觉感知技术与稀缺的全模态数据闭环，其传感器已率先在仓储拣选场景验证显著降本增效。团队兼具 芯片、算法与产业落地经验，与京东生态高度协同，我 ...

2025世界机器人大会正式开幕前，具身智能赛道再度吸金，又有深圳初创公司官宣融资成功！ 今日，帕西尼感知科技（深圳）有限公司公众号对外宣称公司完成新一轮A系列融资，这意味着短短4 个月内，帕西尼已狂揽10亿元人民币，而背后投资机构阵容也十分豪华。本轮融资由京东战略领投，浦 耀信晔、宏兆基金、张科垚坤、上市公司新国都（300130）、北京昌平先进能源制造产业直投基金、财 鑫资本、复琢投资跟投，老股东湖南财信产业基金、钧犀资本、TCL创投、毅达资本持续加码，庚辛资 本中国继续担任独家战略财务顾问。 有参与该项目的投资机构向证券时报记者表示，短时间内获得众多机构和产业资本的支持，核心在于公 司的领先技术，帕西尼的核心产品是触觉传感器，而且在搭建触觉数据库，目前触觉感知和具身智能领 域已经到达一个转折点，公司积累了很多国内外头部厂商客户，尤其值得关注的是，帕西尼和科技巨头 英伟达的深入合作绑定，依托英伟达软硬件解决方案，特别是高性能AI加速集群算力技术，实现了海 量触觉数据的高速运算与算法优化，这一技术支撑使帕西尼感知科技在触觉传感技术领域处于行业领先 地位。 构建"具身智能"技术核心生态闭环 目前，帕西尼已经成为国 ...

Core Insights - The article discusses the development of Tactile-VLA, a model that integrates visual, language, action, and tactile perception to enhance robotic capabilities in contact-intensive tasks [2][6][20]. Group 1: Background and Core Issues - Visual-language-action (VLA) models are crucial for general-purpose robotic agents, but they struggle in contact-intensive scenarios due to a lack of tactile perception [2]. - Tactile perception provides essential feedback for physical interactions, which is often missing in existing models [2]. Group 2: Key Innovations and Research Goals - The core finding is that VLA models contain prior knowledge of physical interactions, which can be activated through tactile sensors for zero-shot generalization in contact tasks [6]. - Tactile-VLA framework introduces tactile perception as a primary modality, allowing direct mapping from abstract semantics to physical force control [6]. - The mixed position-force controller innovatively converts force targets into position adjustment commands, addressing the challenge of coordinating position and force control [6][10]. - Tactile-VLA-CoT variant incorporates a chain of thought (CoT) reasoning mechanism, enabling robots to analyze failure causes and autonomously adjust strategies [6][14]. Group 3: Overall Architecture - Tactile-VLA's architecture features four key modules, emphasizing token-level fusion through a non-causal attention mechanism for true semantic representation rooted in physical reality [9]. Group 4: Mixed Position-Force Control Mechanism - The mixed control strategy prioritizes position control while introducing force feedback adjustments when necessary, ensuring precision in movement and force control [10][12]. - The design separates external net force from internal grasping force, allowing for refined force adjustments suitable for contact-intensive tasks [13]. Group 5: Chain of Thought Reasoning Mechanism - Tactile-VLA-CoT enhances adaptive capabilities by transforming the adjustment process into an interpretable reasoning process, improving robustness in complex tasks [14][15]. Group 6: Data Collection Methods - A specialized data collection system was developed to obtain high-quality tactile-language aligned data, addressing the issue of missing force feedback in traditional remote operations [16][19]. Group 7: Experimental Validation and Results Analysis - Three experimental groups were designed to validate Tactile-VLA's capabilities in instruction following, common sense application, and adaptive reasoning [20]. - In the instruction following experiment, Tactile-VLA demonstrated the ability to learn the semantic meaning of force-related language, achieving a success rate of 35% in USB tasks and 90% in charger tasks [23]. - The model effectively utilized common sense knowledge to adjust interaction forces based on object properties, achieving significant performance improvements over baseline models [24][30]. - In the adaptive reasoning experiment, Tactile-VLA-CoT achieved an 80% success rate in a blackboard task, showcasing its ability to diagnose and correct failures autonomously [28][32].

Core Insights - The article discusses the development of Tactile-VLA, a model that integrates visual, language, action, and tactile perception to enhance robotic capabilities in contact-intensive tasks [2][6]. Group 1: Background and Core Issues - Visual-language-action (VLA) models have strong semantic understanding and cross-modal generalization capabilities, but they struggle in contact-intensive scenarios due to a lack of tactile perception [2][6]. - Tactile perception provides critical feedback in physical interactions, such as friction and material properties, which are essential for tasks requiring fine motor control [2][6]. Group 2: Key Innovations and Research Goals - The core finding is that VLA models contain prior knowledge of physical interactions, which can be activated by connecting this knowledge with tactile sensors, enabling zero-shot generalization in contact-intensive tasks [6][7]. - Tactile-VLA framework introduces tactile perception as a primary modality, allowing for direct mapping from abstract semantics to physical force control [7]. - The mixed position-force controller innovatively converts force targets into position adjustment commands, addressing the challenge of coordinating position and force control [7]. Group 3: Architecture and Mechanisms - Tactile-VLA's architecture includes four key modules: instruction adherence to tactile cues, application of tactile-related common sense, adaptive reasoning through tactile feedback, and a multi-modal encoder for unified token representation [12][13]. - The mixed position-force control mechanism ensures precision in position while allowing for fine-tuned force adjustments during contact tasks [13]. - The Tactile-VLA-CoT variant incorporates a chain of thought (CoT) reasoning mechanism, enabling robots to analyze failure causes based on tactile feedback and autonomously adjust strategies [13][14]. Group 4: Experimental Validation and Results - Three experimental setups were designed to validate Tactile-VLA's capabilities in instruction adherence, common sense application, and adaptive reasoning [17]. - In the instruction adherence experiment, Tactile-VLA achieved a success rate of 35% in USB tasks and 90% in charger tasks, significantly outperforming baseline models [21][22]. - The common sense application experiment demonstrated Tactile-VLA's ability to adjust interaction forces based on object properties, achieving success rates of 90%-100% for known objects and 80%-100% for unknown objects [27]. - The adaptive reasoning experiment showed that Tactile-VLA-CoT could successfully complete a blackboard task with an 80% success rate, demonstrating its problem-solving capabilities through reasoning [33].

Core Insights - The article discusses the significance of touch in enhancing the perception and interaction capabilities of robots, highlighting the development of the Touch100k dataset and the TLV-Link pre-training method [1][11]. Group 1: Touch100k Dataset - Touch100k is the first large-scale dataset that integrates tactile, multi-granular language, and visual modalities, aiming to expand tactile perception from "seeing" and "touching" to "expressing" through language [2][11]. - The dataset consists of tactile images, visual images, and multi-granular language descriptions, with tactile and visual images sourced from publicly available datasets and language descriptions generated through human-machine collaboration [2][11]. Group 2: TLV-Link Method - TLV-Link is a multi-modal pre-training method designed for tactile representation using the Touch100k dataset, consisting of two phases: course representation and modality alignment [6][11]. - The course representation phase employs a "teacher-student" paradigm where a well-trained visual encoder transfers knowledge to a tactile encoder, gradually reducing the teacher model's influence as the student model improves [6][11]. Group 3: Experiments and Analysis - Experiments evaluate TLV-Link from the perspectives of tactile representation and zero-shot tactile understanding, demonstrating its effectiveness in material property recognition and robot grasping prediction tasks [8][11]. - Results indicate that the Touch100k dataset is practical, and TLV-Link shows significant advantages over other models in both linear probing and zero-shot evaluations [9][11]. Group 4: Summary - The research establishes a foundational dataset and method for tactile representation learning, enhancing the modeling capabilities of tactile information and paving the way for applications in robotic perception and human-robot interaction [11].

Group 1 - The core point of the news is that PaxiNi Sensory Technology has received a strategic investment of several hundred million yuan from BYD, marking BYD's largest single investment in the field of embodied intelligence to date [1][3] - This funding will be used to advance the research and mass production of PaxiNi's multi-dimensional tactile sensing technology and humanoid robot product matrix [1][3] - PaxiNi, established in 2021, focuses on the independent research and industrialization of high-precision multi-dimensional tactile sensors, breaking the overseas technology monopoly with its 6D Hall array tactile sensor [3] Group 2 - The tactile sensing technology is considered a key component of the embodied intelligence industry and is ranked fourth among China's 35 critical technologies [3][4] - The investment landscape for humanoid robots has significantly increased in 2023, with 37 financing events in the first quarter alone, totaling approximately 3.5 billion yuan [4] - Major cities like Beijing, Shenzhen, and the Yangtze River Delta remain the primary hubs for entrepreneurship and investment in this sector, with many companies established in 2023 and 2024 [4] Group 3 - Despite the rising interest and investment in humanoid robots, challenges remain in commercializing these technologies, with uncertainties regarding application scenarios and profit models [4][5] - The industry faces the important challenge of balancing technological innovation with sustainable commercial development as it moves forward [5]

Core Viewpoint - PaXini Tech, a leader in tactile perception and humanoid robotics, has received a strategic investment exceeding 100 million yuan from BYD, marking BYD's first major equity investment of the year and its largest in the embodied intelligence sector to date [1][3][12] Company Overview - PaXini Tech was established in June 2021 and is one of the few companies in China capable of independently controlling high-precision multi-dimensional tactile sensors, with a complete product matrix including "sensor - dexterous hand - humanoid robot" [1][4] - The founding team comes from Waseda University's Kanno Robotics Laboratory, known for creating the world's first humanoid robot [1][4] Technology and Product Development - PaXini has developed a 6D Hall array tactile sensor that provides robots with human-like tactile perception capabilities, forming a comprehensive embodied intelligence technology system from hardware packaging to algorithm integration [1][4][6] - The high-precision array tactile sensor can achieve 1 million tactile samples per second, capturing 15 types of tactile information with a precision force recognition capability of 0.01N [5][6] Strategic Investment Implications - BYD's investment reflects a deep recognition of PaXini's technology and a strategic move to enhance its position in the embodied intelligence field [3][12] - The collaboration is expected to leverage both companies' strengths, enabling rapid product iteration and industry leadership for PaXini while allowing BYD to advance its smart automotive upgrades [10][12] Market Position and Future Outlook - PaXini's 6D Hall array tactile sensors are already being utilized by leading humanoid robot companies globally, establishing it as the only supplier of tactile sensors in large-scale humanoid robot applications [12] - The investment signifies a pivotal moment in the tactile perception and embodied intelligence sectors, with PaXini poised to lead the transformation towards practical implementation and industrialization of embodied intelligence technologies [11][12]