Heterogeneous computing platform for real-time robotics

TL;DR

This paper proposes a heterogeneous computing platform combining neuromorphic hardware and traditional AI clusters to enable real-time, interactive robotics in smart city environments, demonstrated through a humanoid robot playing music with a human.

Contribution

It introduces a hybrid computing architecture integrating neuromorphic processors with GPU clusters for enhanced robotic perception and interaction in real-time applications.

Findings

Successful integration of Loihi2 neuromorphic hardware with GPU-based AI for robotics

Real-time performance in a humanoid robot playing music with a human

Demonstrated potential for heterogeneous architectures in complex robotic tasks

Abstract

After Industry 4.0 has embraced tight integration between machinery (OT), software (IT), and the Internet, creating a web of sensors, data, and algorithms in service of efficient and reliable production, a new concept of Society 5.0 is emerging, in which infrastructure of a city will be instrumented to increase reliability, efficiency, and safety. Robotics will play a pivotal role in enabling this vision that is pioneered by the NEOM initiative - a smart city, co-inhabited by humans and robots. In this paper we explore the computing platform that will be required to enable this vision. We show how we can combine neuromorphic computing hardware, exemplified by the Loihi2 processor used in conjunction with event-based cameras, for sensing and real-time perception and interaction with a local AI compute cluster (GPUs) for high-level language processing, cognition, and task planning. We demonstrate the use of this hybrid computing architecture in an interactive task, in which a humanoid robot plays a musical instrument with a human. Central to our design is the efficient and seamless integration of disparate components, ensuring that the synergy between software and hardware maximizes overall performance and responsiveness. Our proposed system architecture underscores the potential of heterogeneous computing architectures in advancing robotic autonomy and interactive intelligence, pointing toward a future where such integrated systems become the norm in complex, real-time applications.