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AI ROBOTICS - Coggle Diagram
AI ROBOTICS
Definitions
Robots are automated devices that perform physical tasks in the real world. They are not to be confused with things like robo-advisors, which are software programs.
The goal of robotics is not to replace humans, but to work with humans to improve our lives. For example, self-driving cars could give us more time to relax or work while commuting.
Robots are programmable machines that sense the world around them through sensors and take actions using actuators. They can come in many shapes and sizes, not just humanoid forms.
Advances in robotics are being driven by improvements in hardware (like more powerful computers and better sensors) and algorithms.
Self-driving cars are an example of how robotics can transform an everyday activity. Cars are becoming increasingly autonomous, with different levels of autonomy defined by the National Highway Traffic Safety Administration. Level 5 is the most advanced level, where cars can drive themselves in all environments and at all times.
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Robots function through a feedback loop. Sensors constantly feed data to the control unit, which interprets it and sends instructions to the actuators. This cycle ensures the robot continuously adapts its actions based on real-time information.
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The level of autonomy varies greatly. Some robots are entirely remote-controlled, while others can operate independently. Many robots function with a combination of both remote control and autonomous behavior.
FUTURE OF ROBOTICS
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Creating robots that can seamlessly integrate into our lives remains a work in progress. Key hurdles include:
Cost: Specialized parts like sensors and actuators are expensive, making complex robots costly to produce.
Complexity: Integrating various components like sensors, software, and actuators into a functional robot that operates flawlessly in real-world environments is challenging.
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SELF DRIVING CARS
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Perception System (Mapping and Localization): Creates a map of the environment using features like curb curvature and building textures detected by laser scanners and cameras./ Tracks the car's location within the map (localization).
PLANNING AND CONTROL :Uses the map and real-time obstacle detection to plan a safe trajectory from a starting point to a destination./ Issues commands to the car's motor to follow the planned trajectory.
Dynamic Virtual Bumper: :A virtual safety zone around the car that triggers obstacle avoidance maneuvers if anything enters the zone.
KEYPOINTS
The map used by self-driving cars is a simplified representation focusing on relevant features, not a visual replica like Google Maps.
Self-driving cars can handle situations not included in the pre-made map by relying on real-time obstacle detection and replanning the path.
The system prioritizes safety and may stop the car or adjust its trajectory to avoid collisions with pedestrians or other obstacles.
Traffic rules are incorporated into the decision-making process. The car can break specific rules (like not crossing a solid line) in controlled situations to avoid a deadlock or ensure safety.
Concept: MoD MOBILITY ON DEMAND aims to provide convenient transportation access anytime, anywhere.
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Challenges with Shared Biking:/ Uneven distribution of bikes across stations due to user behavior./ Need for manual rebalancing, requiring manpower and resources.
Optimal Ride-Sharing Algorithm: / Developed by researchers to match supply (available cars) with demand (ride requests) in real-time.
Can handle large numbers of requests simultaneously and find the most efficient routes for shared rides.
KEY TAKEAWAYS
Legged robots vs. wheeled robots: Legged robots are more versatile for navigating uneven terrain but are harder to control and require advanced perception to maintain balance. Wheeled robots are simpler to control and better for flat surfaces.
Manipulation vs. locomotion: Moving robots around is easier than having them manipulate objects. This is because robots struggle with the uncertainties of the real world and lack the dexterity of humans. Soft robotics is a new field that aims to create robots with compliant manipulation capabilities.
CHALLENGES : Limited understanding: Robots are not good at figuring out their surroundings or the semantics of objects./ Poor interaction: Robots struggle to interact naturally with people and their environment. / Slow development cycle: Creating new robot bodies is a slow and complex process.
Shared control between humans and robots: The future of robotics might involve collaboration between humans and machines, where robots assist humans and prevent them from making mistakes but humans remain in control.
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Realtime Robotics Solution: Realtime Robotics has developed a new system that allows robots to plan their movements in real-time. This system is faster and more adaptable than traditional methods, which can take weeks or months to program.
SAMPLES
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Task: Performs repetitive and physically demanding tasks like lifting and positioning wood pieces for sawing.
Benefit for Moduform: Cost Leadership Strategy: Allows Moduform to potentially lower production costs and keep their prices competitive. / Reduced Labor Needs: The robot can handle tasks that might have otherwise required human workers.
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Task: Transports entire pallets of items to human workers who pick individual products for customer orders.
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Cost Leadership Strategy: Increased efficiency allows Amazon to potentially lower fulfillment costs.
Improved Worker Productivity: Kiva robots bring items to workers, saving them time and effort searching the warehouse.
Competitive Advantage: By acquiring Kiva Systems, Amazon restricts this technology to themselves, potentially making it harder for competitors to achieve similar efficiency gains.
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An autonomous machine capable of sensing its environment (through sensors like cameras or sonar), processing information (using a controller or computer), and acting in the real world (with motors and actuators).
KEY COMPONENTS
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Sensors: Robots use various sensors to gather information about their surroundings. This can include cameras, gyroscopes, sonar, and more.
Compute Unit: The "brain" of the robot, this unit processes the sensory data and determines the appropriate actions. It can range from a simple circuit to a powerful computer.
Actuators: These are the components that allow the robot to perform actions in the real world. This could involve motors, grippers, or other mechanisms.
IMPACT : Self-driving cars and ride-sharing have the potential to transform transportation into a convenient utility.
This could significantly improve urban living by reducing congestion, pollution, and increasing access to transportation.