NeuroBayesSLAM: Neurobiologically inspired Bayesian integration of multisensory information for robot navigation T Zeng, F Tang, D Ji, B Si Neural Networks 126, 21-35, 2020 | 34 | 2020 |
Cognitive mapping based on conjunctive representations of space and movement T Zeng, B Si Frontiers in neurorobotics 11, 61, 2017 | 27 | 2017 |
A brain-inspired compact cognitive mapping system T Zeng, B Si Cognitive Neurodynamics 15 (1), 91-101, 2021 | 19 | 2021 |
Mobile robot exploration based on rapidly-exploring random trees and dynamic window approach T Zeng, B Si 2019 5th International Conference on Control, Automation and Robotics (ICCAR …, 2019 | 14 | 2019 |
Sups: A simulated underground parking scenario dataset for autonomous driving J Hou, Q Chen, Y Cheng, G Chen, X Xue, T Zeng, J Pu 2022 IEEE 25th International Conference on Intelligent Transportation …, 2022 | 8 | 2022 |
Unilateral laryngeal pacing system and its functional evaluation T Zeng, Z Zhang, W Peng, F Zhang, BY Shi, F Chen Neural Plasticity 2017 (1), 8949165, 2017 | 8 | 2017 |
A theory of geometry representations for spatial navigation T Zeng, B Si, J Feng Progress in Neurobiology 211, 102228, 2022 | 5 | 2022 |
Stereoneurobayesslam: a neurobiologically inspired stereo visual slam system based on direct sparse method T Zeng, X Li, B Si arXiv preprint arXiv:2003.03091, 2020 | 3 | 2020 |
Entorhinal-hippocampal interactions lead to globally coherent representations of space T Zeng, B Si, X Li Current Research in Neurobiology 3 (100035), 2022 | 2* | 2022 |
Learning Continuous Control through Proximal Policy Optimization for Mobile Robot Navigation T Zeng 2018 International Conference on Future Technology and Disruptive Innovation …, 2018 | 2 | 2018 |
Bayesian Integration of Multi-resolutional Grid Codes for Spatial Cognition T Zeng, XL Li, B Si arXiv preprint arXiv:1910.05881, 2019 | 1 | 2019 |
Learning sparse spatial codes for cognitive mapping inspired by entorhinal-hippocampal neurocircuit T Zeng, XL Li, B Si arXiv preprint arXiv:1910.04590, 2019 | 1 | 2019 |
LOP-Field: Brain-inspired Layout-Object-Position Fields for Robotic Scene Understanding J Hou, W Guan, X Xue, T Zeng arXiv preprint arXiv:2406.05985, 2024 | | 2024 |