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Robotic manipulation involves the control and coordination of robotic systems to interact with and modify their environment, often mimicking human dexterity and adaptability. It is a multidisciplinary field that combines elements of mechanical engineering, computer science, and artificial intelligence to achieve precise and efficient object handling.
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Kinematics is the branch of classical mechanics that describes the motion of objects without considering the forces that cause the motion. It focuses on parameters such as displacement, velocity, and acceleration to understand how objects move through space and time.
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Dynamics is the branch of physics that studies the forces and their effects on the motion of objects. It is essential for understanding how and why objects move, encompassing both kinematics and the forces that cause motion changes.
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Control theory is a field of study that focuses on the behavior of dynamical systems and the use of feedback to modify the behavior of these systems to achieve desired outcomes. It is widely applied in engineering and science to design systems that maintain stability and performance despite external disturbances and uncertainties.
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Machine learning is a subset of artificial intelligence that involves the use of algorithms and statistical models to enable computers to improve their performance on a task through experience. It leverages data to train models that can make predictions or decisions without being explicitly programmed for specific tasks.
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Grasping is the action of seizing or holding an object, involving complex coordination between sensory perception and motor control. It is a fundamental skill in both human and robotic interaction with the environment, requiring an understanding of object properties and precise execution of movement strategies.
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Motion planning is a computational process used in robotics and autonomous systems to determine a sequence of valid configurations that move an object from a start to a goal position. It involves navigating through complex environments while avoiding obstacles and optimizing certain criteria like time, energy, or distance.
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Sensor fusion is the process of integrating data from multiple sensors to produce more accurate, reliable, and comprehensive information than that provided by any individual sensor alone. It is crucial in applications like autonomous vehicles, robotics, and surveillance systems, where precision and reliability are paramount.
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Force Control is a method used in robotics and automation to manage the interaction between a robot and its environment by regulating the force exerted by the robot. It is essential for tasks requiring precision and adaptability, such as assembly, polishing, or handling delicate objects, where mere position control may not suffice.
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End-effector design is crucial in robotics and automation, as it determines how a robot interacts with objects, affecting its versatility and effectiveness in various applications. The design process involves considerations of functionality, adaptability, and compatibility with the robot's kinematic structure and the task requirements.
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Haptics is the science and technology of transmitting and understanding information through touch, enabling human-computer interaction to be more intuitive and immersive. It plays a crucial role in various applications, from virtual reality to prosthetics, by providing tactile feedback that enhances user experience and functionality.
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Tactile recognition is the process by which humans and machines identify objects through touch, utilizing sensory information to discern shape, texture, temperature, and other physical properties. This ability is crucial for tasks requiring fine motor skills and object manipulation, and is a key area of research in robotics and neuroscience to enhance artificial intelligence and understand human perception.
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Robotic Space Systems are autonomous or remotely operated machines designed to perform tasks in space, such as exploration, maintenance, and assembly, without direct human intervention. These systems are crucial for extending the reach of human capabilities in space, enabling scientific research, resource utilization, and the construction of infrastructure in environments that are inhospitable or inaccessible to humans.
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Collaborative robots, or cobots, are designed to work alongside humans in shared workspaces, enhancing productivity and safety by leveraging advanced sensors and AI for seamless interaction. Unlike traditional industrial robots, cobots are characterized by their adaptability, ease of use, and ability to perform tasks with humans without the need for extensive safety barriers.
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Grasp planning is a critical aspect of robotics that involves determining the optimal way for a robot to pick up and manipulate objects, ensuring stability and precision. This process requires integrating sensory data, geometric reasoning, and control strategies to adapt to varying object shapes and environments.
Machine Learning for Robotics involves leveraging algorithms to enable robots to learn from data and improve their performance over time without being explicitly programmed. This approach enhances robotic capabilities in perception, decision-making, and adaptation to dynamic environments, making robots more autonomous and efficient.
Machine Learning for Grasping involves training models to enable robotic systems to autonomously understand and execute the complex task of grasping objects with precision and adaptability. This field leverages data-driven approaches to improve the dexterity and decision-making capabilities of robots in dynamic environments.
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Force closure is a condition in robotics and mechanics where a set of contact forces can be applied to an object to constrain its motion in all directions, ensuring it remains static or moves predictably. This concept is crucial for the design of robotic grippers and manipulators to ensure they can securely grasp and manipulate objects of various shapes and sizes.
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Soft robotics is an interdisciplinary field focused on creating robots with flexible and deformable materials, allowing them to mimic the adaptability and resilience of biological organisms. This approach enables robots to safely interact with humans and navigate unpredictable environments, broadening their application in areas like healthcare, search and rescue, and manufacturing.
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Space robotics involves the design and deployment of robotic systems to perform tasks in the challenging environment of outer space, where human presence is limited or impossible. These robots are crucial for exploration, satellite servicing, and maintenance of space stations, enhancing our ability to conduct scientific research and expand human presence beyond Earth.
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Robotics is an interdisciplinary field that integrates computer science and engineering to design, construct, and operate robots, which are machines capable of performing tasks autonomously or semi-autonomously. The field aims to enhance efficiency and precision in various applications, from manufacturing and healthcare to exploration and personal assistance.
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Controlled movement refers to the deliberate and precise regulation of motion, often involving coordination between sensory input and motor output to achieve a specific goal. It is essential in various fields such as robotics, biomechanics, and physical therapy, where the accuracy and efficiency of movements are crucial for performance and rehabilitation.
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Articulated structures are systems composed of interconnected segments or parts that can move relative to each other, allowing for flexibility and adaptability in various applications such as robotics, architecture, and biomechanics. They are designed to mimic natural movement and can be used to enhance the functionality and efficiency of mechanical systems by enabling complex motion and load distribution.
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A force-torque sensor is a device used to measure the amount of force and torque applied to an object, often used in robotics and manufacturing to enhance precision and control. These sensors are crucial for applications requiring delicate manipulation or feedback-based adjustments in dynamic environments.
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