Recursive Estimation of Rigid Body Motions

刚体运动的递归估计

基本信息

批准号：
325035548
负责人：
Professor Dr.-Ing. Uwe D. Hanebeck
金额：
--
依托单位：
Lehrstuhl für Intelligente Sensor-Aktor-Systeme (ISAS)
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2016
资助国家：
德国
起止时间：
2015-12-31 至 2019-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/325035548?language=en
关键词：
Recursive Estimation Rigid Body Motions

项目摘要

In this proposal, we focus on algorithms for recursive estimation of rigid body motions. A rigid body motion consists of a translation and a rotation. The group of rigid body motions in three dimensions is called SE(3) and plays an important role in a variety of applications in robotics, aerospace, and computer vision. Consider for example the problem of accurate motion tracking of a moving object, say, a robotic arm, an airplane, or a head-mounted camera. All these problems necessitate estimation of the pose of the considered object, i.e., the rigid body motion of a reference coordinate frame to the body coordinate frame.For this purpose, we propose a new probability distribution on SE(3) that can be used to represent uncertain rigid body motions. Unlike most approaches in literature, the novel distribution is based on so-called unit dual quaternions, a generalization of unit quaternions to the case of rigid body motions. The novel distribution can be seen as a generalization of the hyperspherical Bingham distribution, which has been applied to estimation on the rotation group SO(3) based on unit quaternions. Similar to the Bingham density, the novel density is antipodally symmetric, i.e., x and -x always have the same probability density, which resolves the problem that unit dual quaternions q and -q represent the same rigid body motion.Based on this new probability density, we plan to develop recursive estimation algorithms that have several key advantages compared to state-of-the-art algorithms. First of all, we can represent all rigid body motions, whereas methods based on the corresponding Lie algebra typically cannot represent rotations by exactly 180 degrees. Second, there are no singularities and there is no need to switch between different parameterizations. Furthermore, we do not need to make any assumptions that the uncertainty is low, that rotations are small, or that the density describing the rigid body motions is approximately Gaussian. Due to these advantages, we expect that recursive estimation algorithms based on the new density will outperform state-of-the-art approaches that rely on Gaussian assumptions or locally linear approximations.

在此提案中，我们专注于递归刚体运动的递归估计算法。刚体的运动由翻译和旋转组成。三个维度的刚体运动组称为SE（3），在机器人技术，航空和计算机视觉中的各种应用中起着重要作用。例如，考虑移动物体的准确运动跟踪问题，例如机器人臂，飞机或头部安装相机。所有这些问题都需要估计所考虑的对象的姿势，即，将参考坐标框架框架框架的刚体运动对身体坐标框架的刚体运动。对于此目的，我们提出了SE（3）上的新概率分布，可用于表示不确定的刚体运动。与文献中的大多数方法不同，新颖的分布基于所谓的单元双季节，将单位四元素的概括对刚体运动的情况进行了概括。新的分布可以看作是超球宾汉分布的概括，该分布已应用于基于单位四元组的旋转组（3）对旋转组的估计。与Bingham密度相似，新型密度是抗焦对称的，即X和-X始终具有相同的概率密度，这可以解决与单位双偶合Q和-Q相同的刚体运动的问题。在这种新的概率密度上，我们计划在这种新的概率密度上，我们计划发展递归估计的算法与几个键相位的态度相比，并且是较高的alg alg and-nate fastages。首先，我们可以代表所有刚体运动，而基于相应的谎言代数的方法通常不能准确地表示旋转180度。其次，没有奇异性，也无需在不同的参数之间切换。此外，我们不需要做出任何假设，即不确定性低，旋转很小，或者描述刚体运动的密度大致相当高于高斯。由于这些优势，我们期望基于新密度的递归估计算法将超过依赖于高斯假设或局部线性近似值的最先进方法。

项目成果

期刊论文数量（7）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Nonlinear Progressive Filtering for SE(2) Estimation

DOI：
10.23919/icif.2018.8455231
发表时间：
2018-07
期刊：
2018 21st International Conference on Information Fusion (FUSION)
影响因子：
0
作者：
Kailai Li;G. Kurz;Lukas Bernreiter;U. Hanebeck
通讯作者：
Kailai Li;G. Kurz;Lukas Bernreiter;U. Hanebeck

Grid-Based Quaternion Filter for SO(3) Estimation

DOI：
10.23919/ecc51009.2020.9143723
发表时间：
2020-01-01
期刊：
2020 EUROPEAN CONTROL CONFERENCE (ECC 2020)
影响因子：
0
作者：
Li, Kailai;Pfaff, Florian;Hanebeck, Uwe D.
通讯作者：
Hanebeck, Uwe D.

Unscented Dual Quaternion Particle Filter for SE(3) Estimation

DOI：
10.1109/lcsys.2020.3005066
发表时间：
2021-04-01
期刊：
IEEE CONTROL SYSTEMS LETTERS
影响因子：
3
作者：
Li, Kailai;Pfaff, Florian;Hanebeck, Uwe D.
通讯作者：
Hanebeck, Uwe D.

Geometry-driven Deterministic Sampling for Nonlinear Bingham Filtering

DOI：
10.23919/ecc.2019.8796102
发表时间：
2019-01-01
期刊：
2019 18TH EUROPEAN CONTROL CONFERENCE (ECC)
影响因子：
0
作者：
Li, Kailai;Frisch, Daniel;Hanebeck, Uwe D.
通讯作者：
Hanebeck, Uwe D.

Geometry-Driven Stochastic Modeling of SE(3) States Based on Dual Quaternion Representation

DOI：
10.1109/icphys.2019.8780254
发表时间：
2019-01-01
期刊：
2019 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL CYBER PHYSICAL SYSTEMS (ICPS 2019)
影响因子：
0
作者：
Li, Kailai;Pfaff, Florian;Hanebeck, Uwe D.
通讯作者：
Hanebeck, Uwe D.