LLM as a Robotic Brain: Cloud-Driven Robot Action Sequences Generated by Large... - Sitong Mao
Description:
Explore a 34-minute conference talk on leveraging large language models (LLMs) as robotic brains for generating cloud-driven robot action sequences. Delve into the concept of embodied AI in robotics and its importance in creating coherent action sequences for physical task execution. Examine how high-performance LLMs like Stanford Alpaca are opening new possibilities in robotics. Learn about RoboPilot, an open-source project in the KubeEdge community that combines LLMs with edge-cloud collaboration to enable flexible deployment and execution of real-world robots in open environments. Discover the challenges in achieving unified behavior definition and balancing resource conflicts between large models and edge robots. Gain insights into the potential of edge-cloud collaboration in advancing cloud-native robotics research and enabling advanced robot capabilities.
LLM as a Robotic Brain: Cloud-Driven Robot Action Sequences Generated by Large Language Models