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    Example: In a large e-commerce warehouse, AMRs retrieve shelves containing ordered items and bring them to
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                        human  pickers, significantly speeding up  order  fulfilment.  They  intelligently navigate around  obstacles like fallen
                        boxes or human workers without needing pre-defined routes.
                     Predictive Maintenance and Quality Control
                        Concept: New Age Robotics Systems, often connected through IoT, continuously collect data on their own performance
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                        (e.g., motor  vibrations,  temperature,  operational  hours). This data  is fed into  AI/ML models  to  predict  potential
                        equipment failures before they occur and to identify defects in manufactured products.
                        AI/ML Application: Machine Learning algorithms (especially supervised learning and anomaly detection) are trained
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                        on vast datasets of normal and faulty robot operation or product defects. They can identify subtle patterns that
                        indicate impending failure or quality issues, allowing for proactive maintenance or immediate rejection of faulty
                        products.
                        Impact: Reduced downtime  due  to  unexpected  equipment  failure, lower  maintenance  costs,  improved  product
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                        quality, and reduced waste in manufacturing processes.
                        Example: A robotic arm on an assembly line might have built-in sensors monitoring its joint temperatures and
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                        vibration levels. An AI system continuously analyses this data. If it detects a subtle increase in vibration patterns that
                        it has learned to associate with impending bearing failure, it can alert maintenance staff to replace the bearing before
                        the robot breaks down completely, preventing costly production halts.

                     Healthcare Robotics
                     Robotics in healthcare is moving beyond traditional surgical aids to encompass a broader range of applications, leveraging
                     AI for greater precision, assistance, and patient care.

                     Advanced Surgical Robots
                        Concept: While surgical robots like the Da Vinci system have
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                        been  around, New  Age  Surgical Robotics  are incorporating
                        more AI for enhanced autonomy in specific tasks, improved
                        precision, and better decision support for surgeons.
                        AI/ML Application: Computer Vision and ML algorithms can
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                        assist  surgeons  by  identifying  critical  anatomical  structures,
                        providing  real-time  data  overlays, or even autonomously
                        performing highly repetitive, precise sub-tasks (e.g., suturing
                        in  specific  layers)  under  human  supervision.  Reinforcement
                        Learning is being explored to train robots for complex surgical
                        manoeuvres in simulations.
                        Impact: Enhanced surgical precision, reduced invasiveness, faster patient recovery times, and expanded capabilities
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                        for complex procedures.
                        Example: A future surgical robot, powered by AI vision, might be able to automatically identify a specific blood vessel
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                        based on learned patterns and highlight it for the surgeon, or even autonomously complete a small, intricate stitch
                        perfectly, ensuring consistent quality.
                     Rehabilitation and Assistive Robotics
                        Concept: These robots assist patients in recovering from injuries or provide support for individuals with disabilities.
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                        New age systems are becoming more adaptable and personalised, using AI to understand and respond to individual
                        patient needs.
                        AI/ML Application: ML algorithms analyse patient movement patterns, physiological responses, and progress data
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                        to dynamically adjust therapy intensity or provide tailored assistance. For prosthetic limbs, AI allows for more natural
                        and intuitive control by interpreting muscle signals.

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                                                                                        Introduction to Robots: What Exactly are They?

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