Tesollo Inc.

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Tesollo Inc.
26th Floor, Posco Tower, 165 Convensia-daero
Incheon
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On 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.

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Over the past year, the robotics industry has engaged in a competitive race focused on enhancing the computational power, parameters, and algorithms of robotic 'brains.' While advancements in reasoning capabilities are evident, robots still struggle with basic tasks such as grasping objects or performing precise manipulations. This discrepancy raises questions about the effectiveness of current sensory technologies. The core issue lies in the limitations of robotic perception, which relies heavily on either pure vision or multi-sensor fusion approaches. Multi-sensor fusion, favored by many embodied intelligence manufacturers, combines various sensors to improve robustness and accuracy. However, this method introduces challenges related to data synchronization and processing overhead, hindering the scalability of embodied intelligence. Conversely, pure vision systems, exemplified by Tesla's approach, depend on 2D RGB cameras to reconstruct 3D environments. This method lacks depth information and can falter in challenging visual conditions. Both approaches suffer from the loss of information during data transmission and processing, resulting in robots receiving 'second-hand data' rather than real-time, unified information from the physical world. No further timeline was disclosed at the time of publication.

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A recent review published in the Journal of Field Robotics examines the design and technologies behind underwater grippers for dexterous manipulation. These grippers are essential for various underwater applications, including marine research and exploration, where precise handling of objects is crucial. The significance of this review lies in its comprehensive analysis of the current state of underwater gripper technology, highlighting advancements that enhance their functionality and adaptability. As underwater tasks become more complex, the need for sophisticated grippers that can perform delicate operations is increasingly important. Looking ahead, the review suggests that ongoing research and development in this field will focus on improving the dexterity and efficiency of underwater grippers. No further timeline was disclosed at the time of publication.

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On July 3, Yuequan Bionics unveiled the Y-Hand M1, a dexterous robotic hand weighing 299.7 grams. Unlike competitors that focus on increasing degrees of freedom, the Y-Hand M1 employs a unique bionic tension-compression technology, achieving significant dexterity with only 26 degrees of freedom. This innovation is crucial as the robotics industry grapples with the challenge of balancing performance, cost, and reliability in dexterous hands. The Y-Hand M1 represents a paradigm shift, addressing the industry's 'impossible triangle' where high performance often leads to increased costs and reduced reliability. Looking ahead, the dexterous hand market in China is projected to grow significantly, with sales expected to reach 70,200 units in 2026. As investment in this sector surges, the Y-Hand M1's unique approach may set a new standard for future developments in robotic manipulation technology. No further timeline was disclosed at the time of publication.

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