In a study published in Robot Learning journal, researchers propose a new learning-based path planning framework that allows mobile robots to navigate safely and efficiently using a Transformer model.
In a study published in Robot Learning journal, researchers propose a new learning-based path planning framework that allows mobile robots to navigate ...
Abstract: Unmanned Aerial Vehicle (UAV) path planning is a critical task that directly affects the efficiency and safety of UAV operations in various fields. This paper proposes an improved Bi-RRT* ...
Abstract: To enhance the efficiency and safety of mobile robot path planning, this letter proposes a hybrid sampling and space-optimized RRT (HB-RRT) method. First, a hybrid sampling strategy ...
We present a variation of RRT* that can explore and exploit the search space (SE) in parallel using many-core GPUs, efficiently producing an initial path that is collision-free, kinematically ...
Data is the life-blood of physical AI. Collecting real-life data is expensive. Generative AI and diffusion to create ...
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Adaptive drafter model uses downtime to double LLM training speed
Reasoning large language models (LLMs) are designed to solve complex problems by breaking them down into a series of smaller steps. These powerful models are particularly good at challenging tasks ...
This is a complete software-only implementation of an autonomous robot main control board. No hardware required! Everything runs in software with a comprehensive graphical user interface.
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