Nature

Reinforcement learning-driven deep learning approaches for optimized robot trajectory planning

Trajectory planning and control of bipedal walking robots require precise joint torque computation to ensure stability and efficiency. Given the nonlinear dynamics and complex interactions of bipedal ...
Nature

Hierarchical reinforcement learning with central pattern generator for enabling a quadruped robot simulator to walk on a variety of terrains

We present a data-driven deep reinforcement learning (DRL) method for the optimization of a hierarchically structured control policy that includes the central pattern generator. This method, which is ...
Forbes

MIT Teaches Soft Robots Body Awareness Through AI And Vision

Forbes contributors publish independent expert analyses and insights. I'm a senior tech contributor who writes about science and technology MIT CSAIL researchers have developed a new system that ...

OpenCV 5.0 brings LLMs to the Computer Vision Library

Version 5.0 Modernizes DNN Engine, Adds LLM/VLM Support, and Enhances Core, Hardware Acceleration, and 3D Stack.
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MIT Method Lets Search-and-Rescue Robots Navigate Unexpected Terrain Quickly

MIT researchers have developed a new method that could enable search-and-rescue robots to quickly create accurate maps of unpredictable environments, improving their ability to navigate and respond in ...