Accelerating the Development of Multimodal, Integrative-AI Systems with Platform for Situated Intelligence
Sean Andrist, Dan Bohus
- Year
- 2020
- Access
- Open access
Abstract
We describe Platform for Situated Intelligence, an open-source framework for multimodal, integrative-AI systems. The framework provides infrastructure, tools, and components that enable and accelerate the development of applications that process multimodal streams of data and in which timing is critical. The framework is particularly well-suited for developing physically situated interactive systems that perceive and reason about their surroundings in order to better interact with people, such as social robots, virtual assistants, smart meeting rooms, etc. In this paper, we provide a brief, high-level overview of the framework and its main affordances, and discuss its implications for HRI.
Keywords
Related papers
Review and perspectives on multimodal perception, mutual cognition, and embodied execution for human–robot collaboration in Industry 5.0
Kai Ding, Qingyuan Mao, Yaqian Zhang +3 more
Robotics and Computer-Integrated Manufacturing · 2026
Towards human-centric manufacturing: Task planning under uncertainties in human–robot collaborative assembly
Yingchao You, Ze Ji, Changyun Wei
Robotics and Computer-Integrated Manufacturing · 2026
Agentic HRC: Achieving context alignment via memory for Human–Robot Collaboration
Jiahui Si, Wenchao Li, Xi Chen +4 more
Robotics and Computer-Integrated Manufacturing · 2026
Adaptive Physics-informed Transformer with Gaussian process residual compensation for inverse dynamics modeling in Human–Robot Collaboration
Rui Qian, Xi Zhang, Dongpeng Li +2 more
Robotics and Computer-Integrated Manufacturing · 2026