Tracking and following objects of interest is critical to several robotics use cases, ranging
from industrial automation to logistics and warehousing, to healthcare and security. In this …

Object tracking is central to robot perception and scene understanding, allowing robots to
parse a video stream in terms of moving objects with names. Tracking-by-detection has long …

In this work we present a novel end-to-end framework for tracking and classifying a robot's
surroundings in complex, dynamic and only partially observable real-world environments …

Robots deployed in human-centric environments may need to manipulate a diverse range of
articulated objects, such as doors, dishwashers, and cabinets. Articulated objects often …

In deployment scenarios such as homes and warehouses, mobile robots are expected to
autonomously navigate for extended periods, seamlessly executing tasks articulated in …

We present an architecture and a training recipe that adapts pretrained open-world image
models to localization in videos. Understanding the open visual world (without being …

The development of aerial autonomy has enabled aerial robots to fly agilely in complex
environments. However, dodging fast-moving objects in flight remains a challenge, limiting …

The ability to recognize objects is an essential skill for a robotic system acting in human-
populated environments. Despite decades of effort from the robotic and vision research …

Active recognition which allows intelligent agents to explore observations for better
recognition performance serves as a prerequisite for various embodied AI tasks such as …

This paper presents a novel approach for tracking static and dynamic objects for an
autonomous vehicle operating in complex urban environments. Whereas traditional …