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Kaige Tan
Kaige Tan
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Finding critical scenarios for automated driving systems: A systematic mapping study
X Zhang, J Tao, K Tan, M Törngren, JMG Sánchez, MR Ramli, X Tao, ...
IEEE Transactions on Software Engineering 49 (3), 991-1026, 2022
141*2022
Synthesizing the optimal gait of a quadruped robot with soft actuators using deep reinforcement learning
Q Ji, S Fu, K Tan, ST Muralidharan, K Lagrelius, D Danelia, ...
Robotics and Computer-Integrated Manufacturing 78, 102382, 2022
342022
Edge computing for cyber-physical systems: A systematic mapping study emphasizing trustworthiness
JMG Sánchez, N Jörgensen, M Törngren, R Inam, A Berezovskyi, L Feng, ...
ACM Transactions on Cyber-Physical Systems (TCPS) 6 (3), 1-28, 2022
262022
Critical scenario identification for realistic testing of autonomous driving systems
Q Song, K Tan, P Runeson, S Persson
Software Quality Journal 31 (2), 441-469, 2023
222023
A contactless measuring method of skin temperature based on the skin sensitivity index and deep learning
X Cheng, B Yang, K Tan, E Isaksson, L Li, A Hedman, T Olofsson, H Li
Applied Sciences 9 (7), 1375, 2019
212019
Decentralized convex optimization for joint task offloading and resource allocation of vehicular edge computing systems
K Tan, L Feng, G Dán, M Törngren
IEEE Transactions on Vehicular Technology 71 (12), 13226-13241, 2022
202022
Computationally efficient energy management for a parallel hybrid electric vehicle using adaptive dynamic programming
T Liu, K Tan, W Zhu, L Feng
IEEE Transactions on Intelligent Vehicles 9 (2), 4085-4099, 2023
102023
An industrial workbench for test scenario identification for autonomous driving software
Q Song, K Tan, P Runeson, S Persson
2021 IEEE International Conference on Artificial Intelligence Testing …, 2021
102021
A model-based deep reinforcement learning approach to the nonblocking coordination of modular supervisors of discrete event systems
J Yang, K Tan, L Feng, Z Li
Information Sciences 630, 305-321, 2023
72023
Shape estimation of a 3D printed soft sensor using multi-hypothesis extended Kalman filter
K Tan, Q Ji, L Feng, M Törngren
IEEE Robotics and Automation Letters 7 (3), 8383-8390, 2022
72022
Reducing the learning time of reinforcement learning for the supervisory control of discrete event systems
J Yang, K Tan, L Feng, AM El-Sherbeeny, Z Li
IEEE Access 11, 59840-59853, 2023
42023
Edge-Enabled Adaptive Shape Estimation of 3-D Printed Soft Actuators With Gaussian Processes and Unscented Kalman Filters
K Tan, Q Ji, L Feng, M Törngren
IEEE Transactions on Industrial Electronics 71 (3), 3044-3054, 2023
42023
A low-complexity and high-performance energy management strategy of a hybrid electric vehicle by model approximation
T Liu, W Zhu, K Tan, M Liu, L Feng
2022 IEEE 18th International Conference on Automation Science and …, 2022
22022
Finding critical scenarios for automated driving systems: The data extraction form
X Zhang, J Tao, K Tan, M Törngren, JM Gaspar Sánchez, MR Ramli, T Xin, ...
22021
Building verification database and extracting critical scenarios for self-driving car testing on virtual platform
K Tan
22019
Optimal and Adaptive Engine Switch Control for a Parallel Hybrid Electric Vehicle Using a Computationally Efficient Actor-Critic Method
T Liu, K Tan, W Zhu, L Feng
2023 IEEE/ASME International Conference on Advanced Intelligent Mechatronics …, 2023
12023
CommonUppRoad: A Framework of Formal Modelling, Verifying, Learning, and Visualisation of Autonomous Vehicles
R Gu, K Tan, AH Høeg-Petersen, L Feng, KG Larsen
arXiv preprint arXiv:2408.01093, 2024
2024
Optimal Gait Control for a Tendon-driven Soft Quadruped Robot by Model-based Reinforcement Learning
X Niu, K Tan, L Feng
arXiv preprint arXiv:2406.07069, 2024
2024
Optimal Gait Design for a Soft Quadruped Robot via Multi-fidelity Bayesian Optimization
K Tan, X Niu, Q Ji, L Feng, M Törngren
arXiv preprint arXiv:2406.07065, 2024
2024
Collaborative Collision Avoidance of Connected Vehicles Using ADMM with PI-Regulated Lagrangian Multipliers
K Tan, L Feng, M Törngren
2023 IEEE 19th International Conference on Automation Science and …, 2023
2023
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