Zobrazeno 1 - 10
of 109
pro vyhledávání: '"Andrea L. Thomaz"'
Publikováno v:
Autonomous Robots. 44:1167-1182
Robots are increasingly learning complex skills in simulation, increasing the need for realistic simulation environments. Existing techniques for approximating real-world physics with a simulation require extensive observation data and/or thousands o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a49c188b245760d69690e5d5b6949978
https://doi.org/10.1007/s10514-020-09925-w
https://doi.org/10.1007/s10514-020-09925-w
Publikováno v:
RO-MAN
How team members are treated influences their performance in the team and their desire to be a part of the team in the future. Prior research in human-robot teamwork proposes fairness definitions for human-robot teaming that are based on the work com
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::17f92e7dec205ca1d9cdf5bdfee0b616
https://doi.org/10.1109/ro-man50785.2021.9515428
https://doi.org/10.1109/ro-man50785.2021.9515428
Autor:
Shih-Yun Lo, Andrea L. Thomaz
Publikováno v:
ICRA
Service robots are gaining capabilities to be deployed in public environments for human assistance. While robot actively providing guidance has shown great success in field study, the communication strategy (the strategy to decide whom to initiate th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::36229e154fc01b6eca2055bc11d3e338
https://doi.org/10.1109/icra48506.2021.9561880
https://doi.org/10.1109/icra48506.2021.9561880
Publikováno v:
ICRA
To enable robots to smoothly interact with humans during their travels together as a group, robots need the ability to adapt their motions under environmental changes and ensure all group members’ routes are feasible. To achieve this ability, robot
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::26a43de308148a524d0718921b23d66c
https://doi.org/10.1109/icra48506.2021.9560989
https://doi.org/10.1109/icra48506.2021.9560989
Publikováno v:
ICRA
It is becoming increasingly feasible for robots to share a workspace with humans. However, for them to do so safely while maintaining agile performance, they need the ability to smoothly handle the dynamics and uncertainty caused by human motions. Ma
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0ef04eb15cf9d3faa2f01aa43861b575
https://doi.org/10.1109/icra48506.2021.9561622
https://doi.org/10.1109/icra48506.2021.9561622
Publikováno v:
HRI (Companion)
Robots can use information from people to improve learning speed or quality. However, people can have short attention spans and misunderstand tasks. Our work addresses these issues with algorithms for learning from inattentive teachers that take adva
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::35c25b17d34702cd98eeab62e025e2bc
https://doi.org/10.1145/3434074.3446361
https://doi.org/10.1145/3434074.3446361
Autor:
Andrea L. Thomaz, Mai Lee Chang
Publikováno v:
HRI (Companion)
As robots enter our homes and work places, one of the roles they will have to fulfill is being a teammate. Prior approaches in human-robot teamwork enabled robots to reason about intent, decide when and how to help, and allocate tasks to achieve effi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f80889433f27c724193e7f8e3edcef1a
https://doi.org/10.1145/3434074.3446355
https://doi.org/10.1145/3434074.3446355
Publikováno v:
RO-MAN
We seek to understand the human teammate’s perception of fairness during a human-robot physical collaborative task where certain subtasks leverage the robot’s strengths and others leverage the human’s. We conduct a user study (n=30) to investig
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2e167cf6f1e549a412367303c3c892d2
https://doi.org/10.1109/ro-man47096.2020.9223594
https://doi.org/10.1109/ro-man47096.2020.9223594
Publikováno v:
Robotics: Science and Systems
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::70ad8e525b7ed1da1f77f005b20439a8
https://doi.org/10.15607/rss.2020.xvi.037
https://doi.org/10.15607/rss.2020.xvi.037
Publikováno v:
ICRA
Interactive Reinforcement Learning (RL) enables agents to learn from two sources: rewards taken from observations of the environment, and feedback or advice from a secondary critic source, such as human teachers or sensor feedback. The addition of in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ef1f23a11731d382fac55c9b3f4d70cc
https://doi.org/10.1109/icra40945.2020.9197219
https://doi.org/10.1109/icra40945.2020.9197219