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pro vyhledávání: '"Tzes A"'
Zero-Shot Object Goal Navigation (ZS-OGN) enables robots or agents to navigate toward objects of unseen categories without object-specific training. Traditional approaches often leverage categorical semantic information for navigation guidance, which
Externí odkaz:
http://arxiv.org/abs/2410.23978
We introduce an innovative approach to advancing semantic understanding in zero-shot object goal navigation (ZS-OGN), enhancing the autonomy of robots in unfamiliar environments. Traditional reliance on labeled data has been a limitation for robotic
Externí odkaz:
http://arxiv.org/abs/2410.21926
In this paper, we present a novel method for reliable frontier selection in Zero-Shot Object Goal Navigation (ZS-OGN), enhancing robotic navigation systems with foundation models to improve commonsense reasoning in indoor environments. Our approach i
Externí odkaz:
http://arxiv.org/abs/2410.21037
Autor:
Papatheodorou, Sotiris, Tzes, Anthony
The objective in this article is to develop a control strategy for coverage purposes of a convex region by a fleet of Mobile Aerial Agents (MAAs). Each MAA is equipped with a downward facing camera that senses a convex portion of the area while its a
Externí odkaz:
http://arxiv.org/abs/2410.13422
This article examines the problem of area coverage for a network of mobile robots with imprecise agent localization. Each robot has uniform radial sensing ability, governed by first order kinodynamics. The convex-space is partitioned based on the Gua
Externí odkaz:
http://arxiv.org/abs/2410.09561
As robots become increasingly capable, users will want to describe high-level missions and have robots fill in the gaps. In many realistic settings, pre-built maps are difficult to obtain, so execution requires exploration and mapping that are necess
Externí odkaz:
http://arxiv.org/abs/2410.03035
Publikováno v:
2023 21st International Conference on Advanced Robotics (ICAR)
This paper proposes an approach for controlling surgical robotic systems, while complying with the Remote Center of Motion (RCM) constraint in Robot-Assisted Minimally Invasive Surgery (RA-MIS). In this approach, the RCM-constraint is upheld algorith
Externí odkaz:
http://arxiv.org/abs/2409.05740
This paper introduces a novel control methodology designed to guide a collective of robotic-sheep in a cluttered and unknown environment using robotic-dogs. The dog-agents continuously scan the environment and compute a safe trajectory to guide the s
Externí odkaz:
http://arxiv.org/abs/2407.15701
A robust, resource-efficient, distributed, and minimally parameterized 3D map matching and merging algorithm is proposed. The suggested algorithm utilizes tomographic features from 2D projections of horizontal cross-sections of gravity-aligned local
Externí odkaz:
http://arxiv.org/abs/2406.19461
Achieving control objectives (e.g., stabilization or convergence of tracking error to zero, input-to-state stabilization) in "prescribed time" has attracted significant research interest in recent years. The key property of prescribed-time results un
Externí odkaz:
http://arxiv.org/abs/2405.00224