MIT and NVIDIA researchers created a GPU-accelerated algorithm that lets robots plan complex tasks in seconds, boosting industrial efficiency.

Researchers have developed a lightweight mapping algorithm that reduces memory use and boosts the scalability of autonomous mobile robots.

The algorithm, called catGRANULE 2.0 ROBOT, helps identify molecular targets for further researches and therapies; it is described in a recent article published in the journal Genome Biology.

In the world of robotics, making fast, smart decisions is crucial. A new algorithm developed by researchers at Caltech is helping robots plan their movements in real-time, no matter what type of ...

Helping robots make good decisions in real time Caltech's algorithm called Spectral Expansion Tree Search helps autonomous robotic systems make optimal choices on the move Date: December 4, 2024 ...

MIT this week showcased a new model for training robots. Rather than the standard set of focused data used to teach robots new tasks, the method goes big, ...

RoVi-Aug, the new robot data augmentation framework introduced by the researchers, is based on state-of-the-art diffusion models. These are computational models that can augment images of a robot's ...

This paper introduces a smart mobile robot for tracking an optimal path road network. The development of smart mobile robots became more useful and an efficient in a wide range of areas. Therefore, ...

In this project, the Dijkstra's path planning algorithm was implemented on a point robot for helping it navigate through an obstacle filled space.