LEADER 04693nam 22005895 450 001 9911047796103321 005 20251124120502.0 010 $a981-9530-44-X 024 7 $a10.1007/978-981-95-3044-1 035 $a(MiAaPQ)EBC32428360 035 $a(Au-PeEL)EBL32428360 035 $a(CKB)43713270900041 035 $a(DE-He213)978-981-95-3044-1 035 $a(EXLCZ)9943713270900041 100 $a20251124d2026 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMulti-Modal Robotic Intelligence $eAn Active Perception Approach /$fby Di Guo, Huaping Liu 205 $a1st ed. 2026. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2026. 215 $a1 online resource (265 pages) 225 1 $aArtificial Intelligence: Foundations, Theory, and Algorithms,$x2365-306X 311 08$a981-9530-43-1 327 $aPart I. Core Concepts and Approaches -- Chapter 1. Introduction to Active Perception -- Chapter 2. Deep Neural Networks Fundamentals -- Chapter 3. Action Learning Fundamentals -- Part II. Active Perception for Robotic Intelligence -- Chapter 4. Active Visual Object Discovery -- Chapter 5. Active Visual Scene Understanding -- Chapter 6. Active Exploration for Robotic Manipulation -- Chapter 7. Active Auditory Recognition -- Part III. Multi-Modal Active Perception for Robotic Intelligence -- Chapter 8. Visual-Guided Active Tactile Recognition -- Chapter 9. Sound-Indicated Active Object Detection -- Chapter 10. Multi-Modal Active Perception for Material Recognition -- Chapter 11. A Multisensory Active Perception Approach for Robotic Manipulation -- Chapter 12. Conclusion. 330 $aRecently, substantial progress has been made in the machine perception, particularly computer vision, largely due to the advancements in deep learning techniques. However, robots often operate in unstructured environments, which differ greatly from the well-defined problems typically addressed in computer vision. Consequently, many existing computer vision solutions are not directly applicable to robotics. Additionally, modern intelligent robots have access to multi-modal sensory information, rather than relying on a single modality. Therefore, it is essential to explore the specific challenges of multi-modal robotic intelligence. A key requirement for all intelligent robots is the capability of active perception. Active perception is an effective approach to bridge the gap between robotics and machine perception. Intelligence emerges when the robot actively interacts with the environment, embodying a close coupling of perception and action within a continuous feedback loop. Perception guided action, and each movement generate information that informs subsequent movements. With a variety of available multi-modal sensory information, it is crucial for robots to leverage active perception techniques to achieve multi-modal robotic intelligence. This book introduces multi-modal robotic intelligence from the perspective of active perception. Extensive robotic multi-modal active perception problems are formulated and corresponding case studies are described. Specifically, this book is organized in three parts. Part I covers core concepts and approaches for multi-modal robotic intelligence. In Part II, active perception for robotic intelligence is described, which presents several typical active perception tasks. Part III further describes the multi-modal active perception for robotic intelligence. The book is primarily intended for researchers and graduates with a foundational knowledge of machine learning, spanning in a wide range of disciplines, particularly those involved in robotic intelligence and sensor fusion. 410 0$aArtificial Intelligence: Foundations, Theory, and Algorithms,$x2365-306X 606 $aRobotics 606 $aImage processing$xDigital techniques 606 $aComputer vision 606 $aMachine learning 606 $aRobotics 606 $aComputer Imaging, Vision, Pattern Recognition and Graphics 606 $aMachine Learning 615 0$aRobotics. 615 0$aImage processing$xDigital techniques. 615 0$aComputer vision. 615 0$aMachine learning. 615 14$aRobotics. 615 24$aComputer Imaging, Vision, Pattern Recognition and Graphics. 615 24$aMachine Learning. 676 $a629.892 700 $aGuo$b Di$01864365 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911047796103321 996 $aMulti-Modal Robotic Intelligence$94471180 997 $aUNINA