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Page 155 - Toucpad robotics C11
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    Algorithms:
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                            Global Path Planning: Calculates an optimal path from the robot’s current location to its goal on a known map,
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                            avoiding static obstacles.
                            Local Path Planning/Obstacle Avoidance: Deals with dynamic obstacles (moving people, unexpected objects)
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                            in real-time, making immediate adjustments to the path to avoid collisions.
                        Example: A self-driving car uses a pre-built map for global planning but relies on real-time LIDAR, radar, and camera
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                        data to detect a sudden pedestrian crossing the road (obstacle avoidance) and adjust its trajectory instantly.

                                                ANYmal the Robot Dog Plays Badminton---And It’s Surprisingly Good

                                          ANYmal, a four-legged AI robot, plays badminton using an arm and stereo camera.
                                            Trained through 50 million simulated trials, its real-world counterpart can strike
                          BRAINY                  shuttlecocks at up to 12 m/s—half the speed of an amateur human.
                           FACT
                                        It tracks the shuttle, adjusts movement dynamically, and even returns to the center of the
                                       court. While it currently doesn’t predict human opponent cues, future enhancements could
                                                    broaden its agility applications to tasks like disaster response.

                     Role in Logistics, Transportation, and Search and Rescue Operations
                     Mobile robots are transforming these sectors due to their ability to automate tasks that require movement
                     and adaptability.

                     Logistics
                        Role: Automating the  movement  of goods  and materials  within
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                        warehouses, distribution centers, and even between facilities.

                        Examples:
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                            Autonomous  Mobile Robots (AMRs): Used in e-commerce
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                            warehouses to transport shelves of goods to human pickers,
                            or to move packages to shipping areas, significantly improving
                            efficiency and reducing manual labour.
                            Automated Guided Vehicles (AGVs): Traditional, track-based robots moving materials in factories. New age
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                            AMRs offer more flexibility.
                            Forklift Robots: Autonomous forklifts that can load, unload, and transport pallets of goods without human drivers.
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                        Impact: Increased  throughput,  reduced  operational  costs, improved  safety  by  reducing  human  interaction  with
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                        heavy machinery, and 24/7 operation capabilities.

                     Transportation
                        Role: Revolutionising personal and commercial transport by enabling vehicles to drive themselves.
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                        Examples:
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                            Self-Driving Cars: Aiming to transport passengers without human intervention, promising increased safety (by
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                            eliminating human error), reduced traffic congestion, and more efficient use of road space.
                            Autonomous  Trucks:  Hauling goods  long distances, potentially  improving  efficiency  and  addressing  driver
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                            shortages.

                            Delivery Robots and Drones: Last-mile delivery of packages or food in urban and suburban areas, reducing
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                            delivery costs and speed.
                            Autonomous Public Shuttles: Transporting people within campuses, airports, or specific city zones.
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                                                                                                    Applications of Robotic Systems

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