Building Intelligent Exosuits: AI Control, Sensor Fusion, and Neuro-Robotic Human Augmentation
The future of human mobility will not be determined by stronger machines. It will be determined by smarter machines.
Building an exosuit is a mechanical challenge.
Building an exosuit that understands its user is an intelligence challenge.
Building Intelligent Exosuits takes readers beyond biomechanics and wearable robotics into the computational systems that transform assistive devices into adaptive, learning, and human-aware machines. Combining artificial intelligence, reinforcement learning, digital human modeling, sensor fusion, embedded systems, neuro-robotics, and advanced control architectures, this volume provides a comprehensive engineering blueprint for developing next-generation augmentation technologies.
Inside, readers will explore:
Human intent prediction and neuromuscular signal interpretation
Digital human twins and biomechanical simulation environments
OpenSim-based modeling and virtual prototyping
Reinforcement learning and adaptive assistance strategies
Edge AI deployment for real-time wearable systems
Sensor fusion using IMUs, force sensors, HD-sEMG, and multimodal inputs
Safety-critical control architectures for assistive robotics
Human-in-the-loop optimization and adaptive augmentation
Brain-computer interfaces and future neuro-robotic systems
Real-world deployment challenges, standards, and regulatory frameworks
Written for robotics engineers, AI researchers, biomedical engineers, rehabilitation specialists, wearable technology developers, and students, this volume bridges the gap between intelligent algorithms and physical human augmentation systems.
As artificial intelligence moves from cloud servers into wearable machines, a new era is emerging-one in which technology no longer simply responds to human commands, but learns to understand human intent.
This book provides the engineering roadmap for building that future.
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