دنبال کردن
Katherine Driggs-Campbell
Katherine Driggs-Campbell
Assistant Professor, University of Illinois at Urbana-Champaign
ایمیل تأیید شده در illinois.edu - صفحهٔ اصلی
عنوان
نقل شده توسط
نقل شده توسط
سال
Combining planning and deep reinforcement learning in tactical decision making for autonomous driving‏
CJ Hoel, K Driggs-Campbell, K Wolff, L Laine, MJ Kochenderfer‏
IEEE transactions on intelligent vehicles 5 (2), 294-305, 2019‏
2992019
Hg-dagger: Interactive imitation learning with human experts‏
M Kelly, C Sidrane, K Driggs-Campbell, MJ Kochenderfer‏
2019 International Conference on Robotics and Automation (ICRA), 8077-8083, 2019‏
2362019
Adaptive stress testing with reward augmentation for autonomous vehicle validation‏
A Corso, P Du, K Driggs-Campbell, MJ Kochenderfer‏
2019 IEEE Intelligent Transportation Systems Conference (ITSC), 163-168, 2019‏
1552019
Semiautonomous vehicular control using driver modeling‏
VA Shia, Y Gao, R Vasudevan, KD Campbell, T Lin, F Borrelli, R Bajcsy‏
IEEE Transactions on Intelligent Transportation Systems 15 (6), 2696-2709, 2014‏
1482014
Ensembledagger: A bayesian approach to safe imitation learning‏
K Menda, K Driggs-Campbell, MJ Kochenderfer‏
2019 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2019‏
140*2019
Decentralized structural-rnn for robot crowd navigation with deep reinforcement learning‏
S Liu, P Chang, W Liang, N Chakraborty, K Driggs-Campbell‏
2021 IEEE international conference on robotics and automation (ICRA), 3517-3524, 2021‏
1282021
Data-driven probabilistic modeling and verification of human driver behavior‏
D Sadigh, K Driggs-Campbell, A Puggelli, W Li, V Shia, R Bajcsy, ...‏
AAAI spring symposium-technical report, 56-61, 2014‏
1092014
A wireless hybrid chemical sensor for detection of environmental volatile organic compounds‏
C Chen, F Tsow, KD Campbell, R Iglesias, E Forzani, N Tao‏
IEEE sensors journal 13 (5), 1748-1755, 2013‏
872013
Intention aware robot crowd navigation with attention-based interaction graph‏
S Liu, P Chang, Z Huang, N Chakraborty, K Hong, W Liang, ...‏
2023 IEEE international conference on robotics and automation (ICRA), 12015 …, 2023‏
84*2023
A taxonomy and review of algorithms for modeling and predicting human driver behavior‏
K Brown, K Driggs-Campbell, MJ Kochenderfer‏
arXiv preprint arXiv:2006.08832, 2020‏
83*2020
Integrating intuitive driver models in autonomous planning for interactive maneuvers‏
K Driggs-Campbell, V Govindarajan, R Bajcsy‏
IEEE Transactions on Intelligent Transportation Systems 18 (12), 3461-3472, 2017‏
752017
Improved robustness and safety for autonomous vehicle control with adversarial reinforcement learning‏
X Ma, K Driggs-Campbell, MJ Kochenderfer‏
2018 IEEE Intelligent Vehicles Symposium (IV), 1665-1671, 2018‏
712018
Simulating emergent properties of human driving behavior using multi-agent reward augmented imitation learning‏
RP Bhattacharyya, DJ Phillips, C Liu, JK Gupta, K Driggs-Campbell, ...‏
2019 International Conference on Robotics and Automation (ICRA), 789-795, 2019‏
702019
Towards trustworthy automation: User interfaces that convey internal and external awareness‏
T Rezvani, K Driggs-Campbell, D Sadigh, SS Sastry, SA Seshia, R Bajcsy‏
2016 IEEE 19th International conference on intelligent transportation …, 2016‏
682016
A new sensor for the assessment of personal exposure to volatile organic compounds‏
C Chen, KD Campbell, I Negi, RA Iglesias, P Owens, N Tao, F Tsow, ...‏
Atmospheric environment 54, 679-687, 2012‏
682012
To explain or not to explain: A study on the necessity of explanations for autonomous vehicles‏
Y Shen, S Jiang, Y Chen, KD Campbell‏
arXiv preprint arXiv:2006.11684, 2020‏
622020
Proactive anomaly detection for robot navigation with multi-sensor fusion‏
T Ji, AN Sivakumar, G Chowdhary, K Driggs-Campbell‏
IEEE Robotics and Automation Letters 7 (2), 4975-4982, 2022‏
582022
Improved driver modeling for human-in-the-loop vehicular control‏
K Driggs-Campbell, V Shia, R Bajcsy‏
2015 IEEE International Conference on Robotics and Automation (ICRA), 1654-1661, 2015‏
512015
Robust, informative human-in-the-loop predictions via empirical reachable sets‏
K Driggs-Campbell, R Dong, R Bajcsy‏
IEEE Transactions on Intelligent Vehicles 3 (3), 300-309, 2018‏
502018
Long-term pedestrian trajectory prediction using mutable intention filter and warp LSTM‏
Z Huang, A Hasan, K Shin, R Li, K Driggs-Campbell‏
IEEE Robotics and Automation Letters 6 (2), 542-549, 2020‏
46*2020
سیستم در حال حاضر قادر به انجام عملکرد نیست. بعداً دوباره امتحان کنید.
مقاله‌ها 1–20