Honda Motor Co., Ltd. (20240326256). BEHAVIOR GENERATION FOR SITUATIONALLY-AWARE SOCIAL ROBOTS simplified abstract
Contents
BEHAVIOR GENERATION FOR SITUATIONALLY-AWARE SOCIAL ROBOTS
Organization Name
Inventor(s)
Hifza Javed of San Jose CA (US)
Nawid Jamali of San Francisco CA (US)
BEHAVIOR GENERATION FOR SITUATIONALLY-AWARE SOCIAL ROBOTS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240326256 titled 'BEHAVIOR GENERATION FOR SITUATIONALLY-AWARE SOCIAL ROBOTS
The abstract of the patent application describes a method for behavior generation for situationally-aware social robots using a generative adversarial network (GAN) based network trained on a multimodal human behavioral dataset.
- Generating a synthesized behavior based on a latent space representation of a situational context involving a social robot and individuals.
- Performing behavior retargeting on the synthesized behavior using real behavior data to generate a retargeted behavior.
- Implementing the process based on a GAN-based network for accuracy and efficiency.
Potential Applications: - Social robotics - Human-robot interaction research - Artificial intelligence development
Problems Solved: - Enhancing the adaptability and responsiveness of social robots in various situations - Improving the realism and naturalness of robot behaviors
Benefits: - Better communication and interaction between robots and humans - Enhanced user experience with social robots - Advancement in the field of artificial intelligence and robotics
Commercial Applications: "Behavior Generation for Situationally-Aware Social Robots: Advancements in Human-Robot Interaction"
Frequently Updated Research: Stay updated on advancements in GAN-based networks for behavior generation in social robots.
Questions about Behavior Generation for Situationally-Aware Social Robots: 1. How does behavior retargeting improve the performance of social robots? 2. What are the key challenges in training a GAN-based network for behavior generation in robots?
Original Abstract Submitted
according to one aspect, behavior generation for situationally-aware social robots may include generating a synthesized behavior based on a latent space representation indicative of a situational context including a situationally-aware social robot and one or more individuals, performing behavior retargeting on the synthesized behavior based on a real behavior from an initial latent space input to generate a retargeted behavior, and performing the retargeted behavior. the generating the synthesized behavior and the performing behavior retargeting may be implemented based on a generative adversarial network (gan) based network. the gan based network may be trained using a multimodal human behavioral dataset.
