TechCrunch News 02月07日
Meta is studying how humans and robots can collaborate on housework
index_new5.html
../../../zaker_core/zaker_tpl_static/wap/tpl_guoji1.html

 

Meta发布PARTNR计划,旨在研究家庭环境中人与机器人如何协作完成清洁、烹饪等日常任务。该计划包含一个包含10万项任务的基准测试,并发布了一个包含人类演示的PARTNR数据集,用于训练具身AI模型。Meta还在波士顿动力的Spot机器人上进行了测试,并构建了一个混合现实界面,以可视化机器人的决策过程。PARTNR的目标是将机器人重新定义为未来的合作伙伴,从而推动人机协作领域的研究。尽管家庭机器人面临价格、可靠性和功能限制等挑战,但人机协作的进步是实现家庭机器人普及的关键一步。

🤖 Meta推出PARTNR计划,专注于研究人与机器人在家庭环境中的互动与协作,旨在解决清洁、烹饪和取外卖等日常家务问题。

📊 PARTNR包含一个拥有10万项任务的基准测试,涵盖各种家务活动,同时发布PARTNR数据集,包含人类完成这些任务的演示,用于训练具身AI模型,加速机器人学习。

🥽 Meta构建了混合现实界面,用于可视化机器人的决策过程,帮助人们更好地理解和信任机器人,从而促进更有效的人机协作。

🐕‍🦺 PARTNR模型已在波士顿动力的Spot机器人上进行测试,验证了该模型在实际环境中的应用潜力,为进一步开发家庭机器人奠定基础。

Meta Friday announced PARTNR, a new program designed to study human-robot interaction (HRI). The research is specifically focused on how humans and robots might collaborate in the home environment. That includes mundane tasks like cleaning, cooking, and picking up food deliveries.

Automated housework is a decades-old dream, most prominently captured by The Jetsons’ Rosie. The robot maid debuted on prime-time television more than 60 years ago, but continues to be a popular touchstone when discussing the potential for sophisticated machines to remove some of the burden of household chores.

To date, however, only the robot vacuum has made significant headway in the market. There are numerous reasons why no other home robots have cracked the mainstream, including price, reliability, and limited functionality. It’s certainly not for lack of trying, nor is it due to consumer disinterest. It’s just that no other robot has hit the mark on both cost and feature set.

It’s likely that seeing more robots in the home will require improved collaboration with the people who own them. The first wave of home robots are unlikely to single-handedly manage chores. Even a good robot vacuum needs help from time to time. Meta is positioning PARTNR as both a benchmark and dataset to determine how people and robots might work together to get things done around the home.

“Our benchmark consists of 100,000 tasks, including household chores such as cleaning up dishes and toys,” Meta writes. “We are also releasing the PARTNR dataset consisting of human demonstrations of the PARTNR tasks in simulation, which can be used for training embodied AI models.”

Simulation has become an increasingly useful tool in robot deployment, allowing organizations to test in seconds what might otherwise take hours or days to accomplish in the real world. Meta says, however, that it has also had success deploying the PARTNR model outside of simulation. It has already been used Boston Dynamics’ Spot robot in testing. Meta has also built a mixed reality interface designed to offer a visual representation of the robot’s decision making processes.

“The potential for innovation and development in the field of human-robot collaboration is vast,” Meta adds. “With PARTNR, we want to reimagine robots as future partners, and not just agents, and jump start research in this exciting field.”

Image Credits:Labrador Systems

Age-tech holds a lot of potential for the category. Labrador’s automated serving cart, for example, offers insight into ways technology might assistant older people who continue to live independently. However, many advances of the variety Meta is aiming to address will be required before such systems gain mainstream acceptance.

Humanoids are another intriguing avenue that have presented themselves in recent years. Most companies behind these bipedal robots foresee a future in which they will eventually help out in the home. That said, pricing needs to come down considerably and reliability needs to  improve by leaps and bounds. That is a large part of the reason most manufacturers are looking to address corporate needs first.

With the right scaling and advancements in AI, one can image a world in which humanoid robots address general purpose tasks in a way that allows them to help in both the factory and the home. A major stepping stone to that place requires solid advancements in human-robot collaboration. Meta, which has been exploring robotics amid its wider AI research, is hoping that PARTNR can help them get there.

Fish AI Reader

Fish AI Reader

AI辅助创作,多种专业模板,深度分析,高质量内容生成。从观点提取到深度思考,FishAI为您提供全方位的创作支持。新版本引入自定义参数,让您的创作更加个性化和精准。

FishAI

FishAI

鱼阅,AI 时代的下一个智能信息助手,助你摆脱信息焦虑

联系邮箱 441953276@qq.com

相关标签

Meta PARTNR 人机协作 家庭机器人 AI
相关文章