Cloud Robotics and Automation Questions and Answers for Viva

Answer-1: Cloud robotics refers to robotic systems that leverage cloud computing for processing, storage, and communication to enhance their capabilities.

Answer-2: Traditional robotics process data locally, while cloud robotics offloads computation and data storage to the cloud for scalability and collaboration.

Answer-3: Benefits include scalability, cost reduction, real-time data sharing, improved AI capabilities, and easier maintenance.

Answer-4: Cloud automation provides centralized control, orchestration, and updates for robotic fleets remotely.

Answer-5: IoT connects robots and sensors to the cloud, enabling data collection and remote management.

Answer-6: AWS RoboMaker, Microsoft Azure IoT, Google Cloud Robotics, and IBM Watson are popular platforms.

Answer-7: They use edge computing, local caching, and optimized network protocols to reduce latency.

Answer-8: RPA is the use of software robots to automate repetitive digital tasks.

Answer-9: RPA automates software tasks while cloud robotics involves physical robots enhanced by cloud computing.

Answer-10: Use cases include warehouse automation, remote surgery, autonomous vehicles, and precision agriculture.

Answer-11: Cloud enables powerful AI model training and updates that robots can access instantly.

Answer-12: Challenges include data privacy, secure communication, and protection from cyber-attacks.

Answer-13: Cloud enables real-time monitoring, updates, and coordination of multiple robots.

Answer-14: Processing data near the robot to reduce latency while still using cloud resources for heavy tasks.

Answer-15: Cloud facilitates data sharing and coordination among cobots in real-time.

Answer-16: MQTT, ROS (Robot Operating System), and HTTP/REST are widely used.

Answer-17: Cloud provides scalable compute power for training and deploying ML models to robots.

Answer-18: ROS is an open-source middleware framework that supports robot software development and integration with cloud services.

Answer-19: Updates are managed centrally in the cloud and pushed to robots over the network.

Answer-20: Analytics helps optimize robot performance, predict maintenance, and improve decision-making.

Answer-21: By minimizing local hardware needs and enabling remote monitoring and maintenance.

Answer-22: High data volumes from sensors require efficient compression and prioritization techniques.

Answer-23: By combining cloud redundancy with failover mechanisms and local fallback processing.

Answer-24: Cloud-based simulation allows testing and training robots virtually before deployment.

Answer-25: Cloud provides a platform for controlling and monitoring robots from any location.

Answer-26: Coordination involves synchronizing tasks across robots, facilitated by cloud-based communication and control.

Answer-27: Manufacturing, logistics, healthcare, agriculture, and defense are key beneficiaries.

Answer-28: Cloud offers scalable and cost-effective storage for large volumes of robot-generated data.

Answer-29: Fog robotics uses local edge nodes for processing closer to the robot, while cloud robotics relies more on centralized cloud resources.

Answer-30: By using encryption, access controls, and compliance with data protection regulations.

Answer-31: LIDAR, cameras, IMUs, ultrasonic sensors, and tactile sensors are common.

Answer-32: Through low-latency communication and fast cloud-based processing.

Answer-33: Middleware acts as a bridge between robot hardware and cloud services, simplifying integration.

Answer-34: By monitoring robot health and automatically rerouting tasks or triggering maintenance.

Answer-35: More autonomous, collaborative, and AI-driven robots with seamless cloud integration.

Answer-36: Robots can be remotely controlled and updated to assist in disaster zones without human presence.

Answer-37: APIs enable communication between robots, cloud services, and third-party applications.

Answer-38: 5G offers low latency and high bandwidth for faster robot-cloud communication.

Answer-39: Efficient power management is crucial due to continuous communication and processing demands.

Answer-40: By isolating data and access permissions for different users or organizations.

Answer-41: Digital twins are virtual replicas of physical robots used for monitoring and simulation in the cloud.

Answer-42: Cloud resources can dynamically scale to manage more robots or heavier workloads.

Answer-43: Containers package robot software for consistent deployment and scaling in cloud environments.

Answer-44: Using cloud-based simulators and test environments that mimic real-world conditions.

Answer-45: AI enables intelligent perception, decision making, and adaptive control of robots.

Answer-46: It increases demand for skills in cloud computing, robotics programming, and data analytics.

Answer-47: Privacy, job displacement, and autonomous decision-making accountability.

Answer-48: Through CI/CD pipelines and centralized software repositories.

Answer-49: To track performance, detect anomalies, and ensure system health.

Answer-50: By automating inventory management, order fulfillment, and real-time tracking.