This paper focuses on the problem of active object detection (AOD). AOD is important for
service robots to complete tasks in the family environment, and leads robots to approach the …

In recent years, legged quadruped robots have proved to be a valuable support to humans
in dealing with search and rescue operations. These robots can move with great ability in …

Active object detection (AOD), one of the greatest challenges in the robotics field, is the main
focus of this article. Most current AOD methods are developed by reinforcement learning …

In this paper, we focus on the problem of learning online an optimal policy for Active Visual
Search (AVS) of objects in unknown indoor environments. We propose POMP++, a planning …

In this paper we focus on the problem of learning an optimal policy for Active Visual Search
(AVS) of objects in known indoor environments with an online setup. Our POMP method …

The ability to search for objects is a precondition for various robotic tasks. In this paper, we
address the problem of finding objects in partially known indoor environments. Using the …

We propose a solution for Active Visual Search of objects in an environment, whose 2D floor
map is the only known information. Our solution has three key features that make it more …

Future collaborative robots must be capable of finding objects. As such a fundamental skill,
we expect object search to eventually become an off-the-shelf capability for any robot …

After detecting a target object, a service robot must approach the target object to perform the
associated service task. In active object detection (AOD) tasks, effective feature information …

Abstract Active Object Detection (AOD) gathers additional information by deliberately
adjusting the agent's viewpoint, ensuring precise detection results in complex environments …