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Robotics usually combines three aspects of design work to create robot systems: Mechanical construction: a frame, form or shape designed to achieve a particular task. For example, a robot designed to travel across heavy dirt or mud might use caterpillar tracks. Origami inspired robots can sense and analyze in extreme environments. [2]
Software engineering is a fundamental aspect of robotics, focusing on the development of the code and systems that control a robot's hardware, manage real-time decision-making, and ensure reliable operation in complex environments. Software in robotics encompasses both low-level control software and high-level applications that enable advanced ...
Robot Operating System (ROS or ros) is an open-source robotics middleware suite. Although ROS is not an operating system (OS) but a set of software frameworks for robot software development , it provides services designed for a heterogeneous computer cluster such as hardware abstraction , low-level device control , implementation of commonly ...
Robotic process automation (RPA) is a form of business process automation that is based on software robots (bots) or artificial intelligence (AI) agents. [1] RPA should not be confused with artificial intelligence as it is based on automation technology following a predefined workflow. [2]
Swarm robotics is the study of how to design independent systems of robots without centralized control. The emerging swarming behavior of robotic swarms is created through the interactions between individual robots and the environment. [ 1 ]
2005 DARPA Grand Challenge winner Stanley performed SLAM as part of its autonomous driving system. A map generated by a SLAM Robot. Simultaneous localization and mapping (SLAM) is the computational problem of constructing or updating a map of an unknown environment while simultaneously keeping track of an agent's location within it.
Human–robot interaction (HRI) is the study of interactions between humans and robots.Human–robot interaction is a multidisciplinary field with contributions from human–computer interaction, artificial intelligence, robotics, natural language processing, design, psychology and philosophy.
Adaptable robotics systems successfully adapt to their environment using techniques such as modular design, machine learning, and sensor feedback. Using this, they have revolutionized various industries and can address many real-world challenges in the medical , industrial , extraterrestrial, and experimental fields.