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ROS 2 was announced at ROSCon 2014, [64] the first commits to the ros2 repository were made in February 2015, followed by alpha releases in August 2015. [65] The first distribution release of ROS 2, Ardent Apalone, was released on 8 December 2017, [ 65 ] ushering in a new era of next-generation ROS development.
Robotics engineering is a branch of engineering that focuses on the conception, design, manufacturing, and operation of robots.It involves a multidisciplinary approach, drawing primarily from mechanical, electrical, software, and artificial intelligence (AI) engineering.
Open source robotics means that information about the hardware is easily discerned, so that others can easily rebuild it. In turn, this requires design to use only easily available standard subcomponents and tools, and for the build process to be documented in detail including a bill of materials and detailed ('Ikea style') step-by-step building and testing instructions.
Robot learning is a research field at the intersection of machine learning and robotics. It studies techniques allowing a robot to acquire novel skills or adapt to ...
A rapidly exploring random tree (RRT) is an algorithm designed to efficiently search nonconvex, high-dimensional spaces by randomly building a space-filling tree.The tree is constructed incrementally from samples drawn randomly from the search space and is inherently biased to grow towards large unsearched areas of the problem.
A behavior tree is graphically represented as a directed tree in which the nodes are classified as root, control flow nodes, or execution nodes (tasks). For each pair of connected nodes the outgoing node is called parent and the incoming node is called child.
The first RFC broadly outlining the general ideas that would later form the core design principles of Cyphal (branded UAVCAN at the time) was published in early 2014. [4] It was a response to the perceived lack of adequate technology that could facilitate robust real-time intra-vehicular data exchange between distributed components of modern intelligent vehicles (primarily unmanned aircraft).
Markov random fields find application in a variety of fields, ranging from computer graphics to computer vision, machine learning or computational biology, [13] [14] and information retrieval. [15] MRFs are used in image processing to generate textures as they can be used to generate flexible and stochastic image models.