Rather than viewing robots and automated machines as isolated systems with limited computation and memory, “Cloud Robotics and Automation” provides access to 1) Big Data: access to updated libraries of images, maps, and object/product data, 2) Cloud Computing: access to parallel grid computing on demand for statistical analysis, learning, and motion planning, 3) Collective Learning: robots and systems sharing trajectories, control policies, and outcomes, and 4) Human Computation: use of crowdsourcing to tap human skills for analyzing images and video, classification, learning, and error recovery. The Cloud can also provide access to a) datasets, publications, models, benchmarks, and simulation tools, b) open competitions for designs and systems, and c) open-source software. Cloud Robotics and Automation raises critical new questions related to network latency, quality of service, privacy, and security.
As the U.S. continues in its shift from a manufacturing to a services oriented economy, engineering education must respond.
The Residential Load Monitoring Project aims to improve energy consumers’ knowledge of their consumption by…
In electricity grids, demand response (DR) changes the traditional way that customers consume electricity.