How can AI improve robotic flexibility?

Robotic flexibility is the ability of robots to adapt to different tasks, environments, and situations. It is a key factor for improving the performance, efficiency, and safety of robotic systems. However, achieving robotic flexibility is not easy, as it requires complex control engineering skills and methods. This is where artificial intelligence (AI) can help. AI is the branch of computer science that deals with creating machines and software that can learn, reason, and act intelligently. In this article, you will learn how AI can improve robotic flexibility in four main ways: learning from data, planning and decision making, perception and manipulation, and human-robot interaction.

1 Learning from data

One of the main advantages of AI is that it can enable robots to learn from data, rather than relying on predefined rules or models. This means that robots can improve their skills and behaviors over time, based on their own experiences and feedback. For example, AI can use reinforcement learning, a technique that rewards or penalizes robots for their actions, to teach them how to optimize their performance in different scenarios. AI can also use supervised learning, a technique that uses labeled data to train robots to perform specific tasks, such as object recognition or classification. By learning from data, robots can become more flexible and adaptable to changing conditions and requirements.

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Ing.Jhonatan Lizcano 📝Socio tecnológico

⚡️Automatización industrial , ejecución de proyectos y tecnología
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AI techniques like supervised learning allow robots to be trained on vast datasets. This data can include images, sensor readings, and past experiences. By analyzing this data, robots can learn to recognize objects, navigate environments, and adapt their movements to handle variations in situations. This makes them more flexible than robots programmed with rigid, pre-defined instructions.

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2 Planning and decision making

Another way that AI can improve robotic flexibility is by enhancing their planning and decision making capabilities. Planning and decision making are essential for robots to achieve their goals and cope with uncertainties and constraints. AI can provide robots with algorithms and frameworks that can help them plan their actions, evaluate their outcomes, and choose the best course of action. For example, AI can use optimization, a technique that finds the optimal solution for a given problem, to help robots allocate their resources, schedule their tasks, and coordinate their movements. AI can also use search, a technique that explores different possibilities and paths, to help robots find the most efficient or effective way to reach their destination or solve their problem.

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3 Perception and manipulation

A third way that AI can improve robotic flexibility is by improving their perception and manipulation skills. Perception and manipulation are crucial for robots to interact with their environment and handle different objects and materials. AI can provide robots with tools and methods that can help them sense, process, and interpret the information from their surroundings, such as vision, sound, touch, or smell. For example, AI can use computer vision, a technique that analyzes images and videos, to help robots recognize, locate, and track objects and features. AI can also use natural language processing, a technique that understands and generates spoken or written language, to help robots communicate with humans or other robots. AI can also provide robots with techniques and strategies that can help them manipulate objects and materials with precision, dexterity, and flexibility. For example, AI can use machine learning, a technique that learns from data, to help robots learn how to grasp, lift, move, or place objects of different shapes, sizes, weights, and textures.

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4 Human-robot interaction

A fourth way that AI can improve robotic flexibility is by facilitating their human-robot interaction. Human-robot interaction is the study and design of how humans and robots can work together, cooperate, and coexist. AI can provide robots with skills and features that can help them understand, respond to, and influence human behavior, emotions, and preferences. For example, AI can use social robotics, a branch of robotics that focuses on creating robots that can interact with humans in a social and natural way, to help robots express and interpret emotions, gestures, and facial expressions. AI can also use human-robot collaboration, a branch of robotics that focuses on creating robots that can assist, support, or complement human workers, to help robots adjust their actions, roles, and responsibilities according to human needs, expectations, and feedback. By improving their human-robot interaction, robots can become more flexible and user-friendly, as well as more productive and safe.

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Israel Erick P.

Principal Solutions Architect @ Global Presales | CTO Ambassador
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La inteligencia artificial revolucionará la robótica, abriendo nuevas posibilidades para la interacción humano-robot. Los robots con IA son serán más adaptables, inteligentes y capaces de trabajar con los humanos de forma segura y eficiente. Los beneficios de la IA en la interacción humano-robot deberán ser en contexto de un mejor aprendizaje automático, donde los robots se adaptan a las necesidades y preferencias humanas; una visión artificial donde los robots comprenderan mejor el entorno y navegan de forma segura; con un procesamiento del lenguaje natural para comunicarse de forma natural con los humanos; permitiendo la planificación y toma de decisiones para realizan tareas de forma eficiente y se adapten a los cambios.

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5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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How can AI improve robotic flexibility?

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1 Learning from data

2 Planning and decision making

3 Perception and manipulation

4 Human-robot interaction

5 Here’s what else to consider

Control Engineering

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