# Column: Physical AI Patents — Decision-Making Technology in OSARO Logistics Robots

AI Times, a Korean AI publication, has published Managing Partner Yongduck Kim's column on AI patents.

Source: https://www.iplexlaw.co.kr/en/blog/1478286

HOME / NEWS & INSIGHTS NEWS & INSIGHTS Column: Physical AI Patents — Decision-Making Technology in OSARO Logistics Robots AI Times, a Korean AI publication, has published Managing Partner Yongduck Kim's column on AI patents. AI & Software 2026.05.26 published IPLEX 2 min read AI Times, a Korean AI publication, has published Managing Partner Yongduck Kim's column on AI patents. Yongduck Kim, a patent attorney, focuses on patents in cutting-edge technology fields such as artificial intelligence (AI), smart factories, and blockchain, and has experience performing intellectual property (IP) work for various technology companies such as Samsung Electronics, LG Electronics, and Xiaomi. In addition, he has written books such as “AI Patent Examination Practice Guide” and “AI Patent Strategy” and continues to share his expert knowledge on AI technology and patent strategy. In this column, we will look at what artificial intelligence-based decision-making technology means in the next generation of logistics automation competition, with the theme “The robot hand” and “Judgment power” at the core of the physical AI era. The AI industry is rapidly expanding beyond the digital realm of text and images to the era of ‘physical AI’, which understands and acts on the physical environment. In the logistics and manufacturing industries in particular, it is becoming a key competitive advantage to be able to make strategic decisions in a changing environment rather than just robotic hardware. The column analyzes OSARO's U.S. Patent No. 12,447,631 B2, 'Automated Robotic Tool Selection.' It describes selecting an end effector by considering future tasks, tool-changing costs, and overall throughput. The analysis also covers deep learning-based grasp-success prediction, Markov decision processes, void zones, and sparse tree search (STS). This column emphasizes that competition in the era of physical AI is moving beyond simple robot control into a ‘judgmental system’ competition. If conventional industrial robots were to perform a set path over and over again, physical AI robots are evolving to predict environmental changes and future workflows, choosing the right strategy for themselves. This technology is likely to develop into a key infrastructure in logistics, e-commerce, and industrial automation in the future, suggesting that the AI-based decision-making structure itself may be an important patent competition. The full article can be found at the link below. Read the column Read the Korean source This article reflects the information available when it was published. Contact us to discuss your circumstances. Discuss this topic ↗ All articles TALK TO IPLEX Discuss your IP questions We consider your technology and business needs together. ↗ Contact us Newer Yongduck Kim Completes KIPA Training on Employee Invention Systems ↗ Older Russian Trademark Applications: Questions and Answers ↗ Related insights AI & Software 2026.10.01 FiX: fine-grained forgetting in softmax attention Yongduck Kim examines FiX’s feature-wise gates, numerical implementation and paged cache, distinguishing reported gains from unresolved limitations. ↗ Read article AI & Software 2026.09.30 MHAR: Reading earlier layers through different feature subspaces Yongduck Kim examines Multi-Head Attention Residuals: depth routing, reported training results, implementation costs and the relationship between technical features and effects. ↗ Read article AI & Software 2026.09.28 Column: Claude Computer Use and the Data That Trains AI Agents Writing for AI Times, IPLEX Managing Partner Yongduck Kim examines the training data behind computer-operating AI agents through U.S. Patent No. 12,585,862. ↗ Read article

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