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pro vyhledávání: '"Asfora, Beatriz A."'
Path planning in obstacle-dense environments is a key challenge in robotics, and depends on inferring scene attributes and associated uncertainties. We present a multiple-hypothesis path planner designed to navigate complex environments using obstacl
Externí odkaz:
http://arxiv.org/abs/2308.07420
There has been a plethora of work towards improving robot perception and navigation, yet their application in hazardous environments, like during a fire or an earthquake, is still at a nascent stage. We hypothesize two key challenges here: first, it
Externí odkaz:
http://arxiv.org/abs/2207.13791
Publikováno v:
IEEE Robotics and Automation Letters, vol. 6, no. 2, pp. 3152-3159, April 2021
The ability to develop a high-level understanding of a scene, such as perceiving danger levels, can prove valuable in planning multi-robot search and rescue (SaR) missions. In this work, we propose to uniquely leverage natural language descriptions f
Externí odkaz:
http://arxiv.org/abs/2104.03809
Autor:
Asfora, Beatriz Arruda
Publikováno v:
23rd ABCM International Congress of Mechanical Engineering,December 6-11, 2015, Rio de Janeiro, RJ, Brazil
Robotics can be defined as the connection of perception to action. Taking this further, this project aims to drive a robot using an automated computer vision embedded system, connecting the robot's vision to its behavior. In order to implement a colo
Externí odkaz:
http://arxiv.org/abs/2101.04804
Publikováno v:
IEEE Robotics and Automation Letters, vol. 5, no. 4, pp. 6805-6812, Oct. 2020
In this letter, we consider the Multi-Robot Efficient Search Path Planning (MESPP) problem, where a team of robots is deployed in a graph-represented environment to capture a moving target within a given deadline. We prove this problem to be NP-hard,
Externí odkaz:
http://arxiv.org/abs/2011.12480