{"product_id":"ai-based-robot-safe-learning-and-control-practical-safe-control","title":"AI based Robot Safe Learning and Control - Practical Safe Control","description":"\u003cp\u003eIn this review of AI based Robot Safe Learning and Control, the bottom line is clear: this open access book is best for robotics researchers and graduate students who need a focused, technical treatment of safe control for robot manipulators. The review finds the strongest reason to read it is the emphasis on control schemes built around \u003cstrong\u003edynamic neural network\u003c\/strong\u003e approaches that tie deep reinforcement ideas to real industrial problems, giving readers methods for adaptive tracking, compliance in uncertain environments and dynamic obstacle avoidance.\u003c\/p\u003e\u003ch2\u003eKey Features\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eDynamic neural network methods:\u003c\/strong\u003e Explains control schemes developed with dynamic neural networks so readers can apply deep reinforcement principles to robot arms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAdaptive tracking control:\u003c\/strong\u003e Presents techniques for handling model uncertainties, helping maintain accurate trajectory following when robot parameters are unknown or change.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eCompliance control in uncertainty:\u003c\/strong\u003e Covers compliant interaction strategies suited for uncertain or variable contact conditions in real workspaces.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eObstacle avoidance in dynamic workspace:\u003c\/strong\u003e Describes approaches to detect and avoid moving obstacles, improving operational safety in industrial settings.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eResearch-derived content:\u003c\/strong\u003e Most material is drawn from the authors' published papers, providing direct links between theory and peer-reviewed results.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eWho It's For\u003c\/h2\u003e\u003cp\u003eThis book is intended for graduate students, academic researchers, and engineers working on robot manipulators who want a concentrated source on safety-aware control strategies that leverage neural network dynamics. Readers who are comfortable with control theory and machine learning will get the most from the technical derivations and references to journal articles.\u003c\/p\u003e\u003cp\u003eLess suitable for casual readers or practitioners seeking a hands-on tutorial with extensive code libraries or hardware step-by-step guides; they should look for application guides or textbooks with implementation examples and software packages.\u003c\/p\u003e\u003ch2\u003ePros \u0026amp; Cons\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003ePros\u003c\/strong\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eDirect focus on \u003cstrong\u003esafe control\u003c\/strong\u003e makes it a specialized resource for robot safety research.\u003c\/li\u003e\n\u003cli\u003eMaterial based on published journal papers provides a credible, research-backed foundation.\u003c\/li\u003e\n\u003cli\u003eCovers practical safety topics such as adaptive tracking, compliance, and dynamic obstacle avoidance relevant to industrial deployment.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003cstrong\u003eCons\u003c\/strong\u003e\u003c\/p\u003e\u003cul\u003e\u003cli\u003eNot a beginner tutorial; the book assumes familiarity with control systems and neural-network concepts.\u003c\/li\u003e\u003c\/ul\u003e\u003ch2\u003eSpecifications\u003c\/h2\u003e\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd\u003eTitle\u003c\/td\u003e\n\u003ctd\u003eAI based Robot Safe Learning and Control\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eEdition type\u003c\/td\u003e\n\u003ctd\u003eOpen access book\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePrimary focus\u003c\/td\u003e\n\u003ctd\u003eSafe control of robot manipulators\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eCore methodology\u003c\/td\u003e\n\u003ctd\u003eDynamic neural network and deep reinforcement learning theory\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eApplication topics\u003c\/td\u003e\n\u003ctd\u003eAdaptive tracking, compliance control, obstacle avoidance\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eSource material\u003c\/td\u003e\n\u003ctd\u003eDerived from authors' journal papers\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eAuthors\u003c\/td\u003e\n\u003ctd\u003eXuefeng Zhou, Zhihao Xu, Shuai Li, Hongmin Wu, Taobo Cheng, Xiaojing Lv\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e\u003ch2\u003eOur Verdict\u003c\/h2\u003e\u003cp\u003eAI based Robot Safe Learning and Control is a focused, research-oriented volume that delivers practical control schemes grounded in dynamic neural network theory. Researchers and advanced students building safety-critical robot arm controllers will find it good value for its clear link to journal work and practical industrial motivation, though those seeking implementation tutorials should supplement it with code resources.\u003c\/p\u003e\u003ch2\u003eFrequently Asked Questions\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eDoes the book include implementation code?\u003c\/strong\u003e\u003cbr\u003eThe description indicates the material is derived from published papers; it does not promise code or step-by-step software, so readers should expect theory and algorithm descriptions rather than ready-to-run packages.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eIs this suitable for industrial applications?\u003c\/strong\u003e\u003cbr\u003eYes, the book was conceived during industrial applications and laboratory research, and it emphasizes strategies like obstacle avoidance and compliance that are directly relevant to industry.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWhat background is required?\u003c\/strong\u003e\u003cbr\u003eA solid grounding in control theory and familiarity with neural network or reinforcement learning concepts is recommended to get the most from the material.\u003c\/p\u003e","brand":"Xuefeng Zhou, Zhihao Xu, Shuai Li, Hongmin Wu, Taobo Cheng, Xiaojing Lv","offers":[{"title":"Default Title","offer_id":48136506376411,"sku":"9811555052","price":49.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0724\/1043\/1707\/files\/610vMI12O0L._SL1254.jpg?v=1768365707","url":"https:\/\/gearmusthave.com\/products\/ai-based-robot-safe-learning-and-control-practical-safe-control","provider":"GearMustHave","version":"1.0","type":"link"}