Zobrazeno 1 - 10
of 217
pro vyhledávání: '"Cao, WenHan"'
Existing state estimation algorithms for legged robots that rely on proprioceptive sensors often overlook foot slippage and leg deformation in the physical world, leading to large estimation errors. To address this limitation, we propose a comprehens
Externí odkaz:
http://arxiv.org/abs/2411.11483
Practical Bayes filters often assume the state distribution of each time step to be Gaussian for computational tractability, resulting in the so-called Gaussian filters. When facing nonlinear systems, Gaussian filters such as extended Kalman filter (
Externí odkaz:
http://arxiv.org/abs/2410.15832
Autor:
Lin, Yuxin, Ma, Jiaxuan, Gu, Sizhe, Kong, Jipeng, Xu, Bowen, Zhao, Xiting, Zhao, Dengji, Cao, Wenhan, Schwertfeger, Sören
Mobile robotics datasets are essential for research on robotics, for example for research on Simultaneous Localization and Mapping (SLAM). Therefore the ShanghaiTech Mapping Robot was constructed, that features a multitude high-performance sensors an
Externí odkaz:
http://arxiv.org/abs/2408.00545
In Gaussian Process (GP) dynamical model learning for robot control, particularly for systems constrained by computational resources like small quadrotors equipped with low-end processors, analyzing stability and designing a stable controller present
Externí odkaz:
http://arxiv.org/abs/2406.02272
Multi-object tracking (MOT) is an essential technique for navigation in autonomous driving. In tracking-by-detection systems, biases, false positives, and misses, which are referred to as outliers, are inevitable due to complex traffic scenarios. Rec
Externí odkaz:
http://arxiv.org/abs/2406.01380
Bayesian filtering serves as the mainstream framework of state estimation in dynamic systems. Its standard version utilizes total probability rule and Bayes' law alternatively, where how to define and compute conditional probability is critical to st
Externí odkaz:
http://arxiv.org/abs/2404.00481
Autor:
Cao, Wenhan, Pan, Wei
Integral reinforcement learning (IntRL) demands the precise computation of the utility function's integral at its policy evaluation (PEV) stage. This is achieved through quadrature rules, which are weighted sums of utility functions evaluated from st
Externí odkaz:
http://arxiv.org/abs/2402.17375
Adaptive dynamic programming (ADP) for stochastic linear quadratic regulation (LQR) demands the precise computation of stochastic integrals during policy iteration (PI). In a fully model-free problem setting, this computation can only be approximated
Externí odkaz:
http://arxiv.org/abs/2402.09575
The confluence of soft robotics and fluidic logic have sparked innovations in integrated robots with superior flexibility and potential machine intelligence. However, current fluidically driven soft robots suffer from either a large number of input c
Externí odkaz:
http://arxiv.org/abs/2401.16827
The accuracy of moving horizon estimation (MHE) suffers significantly in the presence of measurement outliers. Existing methods address this issue by treating measurements leading to large MHE cost function values as outliers, which are subsequently
Externí odkaz:
http://arxiv.org/abs/2210.02166