平滑的轨迹可以用少量的状态紧凑地表示,高斯过程回归(Gaussian process regression)可以在任何时间查询机器人的状态。基于这一思路(Using this insight),我们开发了高斯过程运动规划器(GPMP),这是一种新的运动规划算法,利用高斯过程插值和基于梯度的优化来优化由少量状态参数化的轨迹。我们在仿真和一个7-DOF Barrett ...
最近research gate里推送了一篇文章,刘明老师组里刚发的ICRA,讲的是Gaussian过程motion plan,说实话,我第一次了解还能用高斯过程解轨迹规划问题,确实不懂,发现了两篇早期的Gaussian process motion planning,都来自Mukadam,也是本文的reference。Mukadam他们做还开源了这个工具,叫做GPMP2, 有兴趣的可以了解一下。如果研究...
Multi-agent Gaussian Process Motion Planning via Probabilistic InferenceComputer Science - RoboticsThis paper deals with motion planning for multiple agents by representing the problem as a simultaneous optimization of every agent's trajectory. Each trajectory is considered as a sample from a one-...
We propose a method for leveraging past experience to learn how to automatically adapt the parameters of Gaussian Process Motion Planning (GPMP) algorithms. Specifically, we propose a differentiable extension to the GPMP2 algorithm, so that it can be trained end-to-end from data. We perform ...
This library is an implementation of GPMP2 (Gaussian Process Motion Planner 2) algorithm described inMotion Planning as Probabilistic Inference using Gaussian Processes and Factor Graphs(RSS 2016). The core library is developed in C++ language, and an optional Matlab toolbox is provided. Examples ar...
This library is an implementation of GPMP2 (Gaussian Process Motion Planner 2) algorithm described inMotion Planning as Probabilistic Inference using Gaussian Processes and Factor Graphs(RSS 2016). The core library is developed in C++ language, and an optional Matlab toolbox is provided. Examples ar...
This inference process took about 0.1 ms per dynamic. 3.1.3. Step 3: Expansion from latent output space to motion-fields To expand the posterior distribution on yt to motion-fields, a motion model is required. To derive the motion model Φ, first respiratory-resolved MR-images ≔I≔[I...
Our proposed approach also incorporates an edge rewiring step into the belief roadmap construction process, which provably improves the coverage of the belief roadmap. When compared to state-of-the-art methods, REVISE improves median plan accuracy (as measured by Wasserstein distance between the ...
首先,在轨迹的函数空间中直接放置一个鼓励平滑性的高斯过程先验(Gaussian process prior)(第II-A节)。接下来,我们指定一个似然函数(likelihood function),鼓励无碰撞的轨迹(第II-B节)。然后,MAP估计值(MAP estimate)从后验分布中计算得出(第II-C节)。最后,在后验分布的拉普拉斯近似下,可以在任何感兴趣的时间计算...
2.6 The normal inverse gaussian process Barndorff and Nielsen (1998) proposed the normal inverse Gaussian (NIG) distribution as a possible model for the stock price. This process may also be represented as a time-changed Brownian motion, where the time change T(t) is the first passage time ...