Zobrazeno 1 - 10
of 33
pro vyhledávání: '"Andrea Bajcsy"'
Humans have internal models of robots (like their physical capabilities), the world (like what will happen next), and their tasks (like a preferred goal). However, human internal models are not always perfect: for example, it is easy to underestimate
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c4f14490195592d1433b1b37dd2a7f06
Publikováno v:
IEEE Robotics and Automation Letters. 6:24-31
Designing human motion predictors which preserve safety while maintaining robot efficiency is an increasingly important challenge for robots operating in close physical proximity to people. One approach is to use robust control predictors that safegu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c15946a6053edc9ffe1bc3b72a03743b
https://doi.org/10.1109/lra.2020.3028049
https://doi.org/10.1109/lra.2020.3028049
Publikováno v:
IEEE Transactions on Robotics. 36:835-854
Human input has enabled autonomous systems to improve their capabilities and achieve complex behaviors that are otherwise challenging to generate automatically. Recent work focuses on how robots can use such input - like demonstrations or corrections
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a907ac0b4479fd05252d853161467f98
https://doi.org/10.1109/tro.2020.2971415
https://doi.org/10.1109/tro.2020.2971415
When a robot performs a task next to a human, physical interaction is inevitable: the human might push, pull, twist, or guide the robot. The state of the art treats these interactions as disturbances that the robot should reject or avoid. At best, th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6f433b28fe79cdbb13594740cb8d9222
http://arxiv.org/abs/2107.02349
http://arxiv.org/abs/2107.02349
Autor:
Steven Wang, David Fridovich-Keil, Sylvia L. Herbert, Claire J. Tomlin, Jaime F. Fisac, Andrea Bajcsy, Anca D. Dragan
Publikováno v:
The International Journal of Robotics Research. 39:250-265
One of the most difficult challenges in robot motion planning is to account for the behavior of other moving agents, such as humans. Commonly, practitioners employ predictive models to reason about where other agents are going to move. Though there h
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d3eeac6a417940a2e7dae02290b7e256
https://doi.org/10.1177/0278364919859436
https://doi.org/10.1177/0278364919859436
Publikováno v:
IEEE Robot Autom Lett
Robotic systems frequently operate under changing dynamics, such as driving across varying terrain, encountering sensing and actuation faults, or navigating around humans with uncertain and changing intent. In order to operate effectively in these si
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::58007cc03694f3265a8d6b3c6d1b6b31
https://pubmed.ncbi.nlm.nih.gov/33969182
https://pubmed.ncbi.nlm.nih.gov/33969182
Publikováno v:
ICRA
Predictive human models often need to adapt their parameters online from human data. This raises previously ignored safety-related questions for robots relying on these models such as what the model could learn online and how quickly could it learn i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::98ada85a07511075c8294746363b7602
An outstanding challenge with safety methods for human-robot interaction is reducing their conservatism while maintaining robustness to variations in human behavior. In this work, we propose that robots use confidence-aware game-theoretic models of h
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bb46d5721bc8b960be2729cef4621bd1
Publikováno v:
CDC
Real-world autonomous vehicles often operate in a priori unknown environments. Since most of these systems are safety-critical, it is important to ensure they operate safely even when faced with environmental uncertainty. Current safety analysis tool
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f3e068bdf9b0bf8e53ee21392d084762
https://doi.org/10.1109/cdc40024.2019.9030133
https://doi.org/10.1109/cdc40024.2019.9030133
Autor:
Mathew C. Jennings, Anish Khattar, Ramkesh Renganathan, Ryan S. Kuo, Bryan N. Toth, Alexa J. Cohen, Felix A. Lee, Marcio A. Oliveira, Laura W. Migasiuk, Meilin K. Lim, Andrea Bajcsy, Oliver Zhao, Amelia Bateman, Amy Zhang, Emily L. Horton
Publikováno v:
International Journal of Human-Computer Studies. 109:102-111
Students who are visually impaired face unique challenges when learning mathematical concepts due to the visual nature of graphs, charts, tables, and plots. While touchscreens have been explored as a means to assist people with visual impairments in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eea8095f9093072ee6488f6395ec3d14
https://doi.org/10.1016/j.ijhcs.2017.09.004
https://doi.org/10.1016/j.ijhcs.2017.09.004