Abstract: Path planning in robotics and automation often demands solutions that effectively balance efficiency and path smoothness, particularly in diverse and large-scale environments. To address ...

Foundational optimization algorithms are the core driving force behind deep learning, evolving from early stochastic gradient descent (SGD) to the widely adopted Adam family. However, as the scale of ...

Abstract: Task-Parameterized Learning from Demonstrations (TP-LfD) is an effective approach for collaborative robot (cobot). It aims at generating a path of a cobot moving in a dynamic collaborative ...

Claude Code generates computer code when people type prompts, so those with no coding experience can create their own programs and apps. By Natallie Rocha Reporting from San Francisco Claude Code, an ...

Shortest path algorithms sit at the heart of modern graph theory and many of the systems that move people, data, and goods around the world. After nearly seventy years of relying on the same classic ...

For the low efficiency and poor generalization ability of path planning algorithm of industrial robots, this work proposes an adaptive field co-sampling algorithm (AFCS). Firstly, the environment ...

When Edsger W. Dijkstra published his algorithm in 1959, computer networks were barely a thing. The algorithm in question found the shortest path between any two nodes on a graph, with a variant ...

The original version of this story appeared in Quanta Magazine. If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle ...

Unmanned surface vehicles (USVs) nowadays have been widely used in ocean observation missions, helping researchers to monitor climate change, collect environmental data, and observe marine ecosystem ...