Critical Fidelity

Using a Wigner Lorentzian Random Matrix ensemble, we study the fidelity, $F(t)$, of systems at the Anderson metal-insulator transition, subject to small perturbations that preserve the criticality. We find that there are three decay regimes as perturbation strength increases: the first two are associated with a gaussian and an exponential decay respectively and can be described using Linear Response Theory. For stronger perturbations $F(t)$ decays algebraically as $F(t)\sim t^{-D_2}$, where $D_2$ is the correlation dimension of the critical eigenstates.Comment: 4 pages, 3 figures. Revised and published in Phys. Rev. Let

Robust 6D Object Pose Estimation by Learning RGB-D Features

Accurate 6D object pose estimation is fundamental to robotic manipulation and grasping. Previous methods follow a local optimization approach which minimizes the distance between closest point pairs to handle the rotation ambiguity of symmetric objects. In this work, we propose a novel discrete-continuous formulation for rotation regression to resolve this local-optimum problem. We uniformly sample rotation anchors in SO(3), and predict a constrained deviation from each anchor to the target, as well as uncertainty scores for selecting the best prediction. Additionally, the object location is detected by aggregating point-wise vectors pointing to the 3D center. Experiments on two benchmarks: LINEMOD and YCB-Video, show that the proposed method outperforms state-of-the-art approaches. Our code is available at https://github.com/mentian/object-posenet.Comment: Accepted at ICRA 202

3DFeat-Net: Weakly Supervised Local 3D Features for Point Cloud Registration

In this paper, we propose the 3DFeat-Net which learns both 3D feature detector and descriptor for point cloud matching using weak supervision. Unlike many existing works, we do not require manual annotation of matching point clusters. Instead, we leverage on alignment and attention mechanisms to learn feature correspondences from GPS/INS tagged 3D point clouds without explicitly specifying them. We create training and benchmark outdoor Lidar datasets, and experiments show that 3DFeat-Net obtains state-of-the-art performance on these gravity-aligned datasets.Comment: 17 pages, 6 figures. Accepted in ECCV 201

Supramolecular Assembly and Chirality of Synthetic Carbohydrate Materials

Hierarchical carbohydrate architectures serve multiple roles in nature. Hardly any correlations between the carbohydrate chemical structures and the material properties are available due to the lack of standards and suitable analytic techniques. Therefore, designer carbohydrate materials remain highly unexplored, as compared to peptides and nucleic acids. A synthetic D‐glucose disaccharide, DD, was chosen as a model to explore carbohydrate materials. Microcrystal electron diffraction (MicroED), optimized for oligosaccharides, revealed that DD assembled into highly crystalline left‐handed helical fibers. The supramolecular architecture was correlated to the local crystal organization, allowing for the design of the enantiomeric right‐handed fibers, based on the L‐glucose disaccharide, LL, or flat lamellae, based on the racemic mixture. Tunable morphologies and mechanical properties suggest the potential of carbohydrate materials for nanotechnology applications

Clothoid-Based Three-Dimensional Curve for Attitude Planning

Interest in flying robots, also known as unmanned aerial vehicles (UAVs), has grown during last years in both military and civil fields [1, 2]. The same happens to autonomous underwater vehicles (AUVs) [3]. These vehicles, UAVs and AUVs, offer a wide variety of possible applications and challenges, such as control, guidance or navigation [2, 3]. In this sense, heading and attitude control in UAVs is very important [4], particularly relevant in airplanes (fixed-wing flying vehicles), because they are strongly non-linear, coupled, and tend to be underactuated systems with non-holonomic constraints. Hence, designing a good attitude controller is a difficult task [5, 6, 7, 8, 9], where stability must be taken into account by the controller [10]. Indeed, if the reference is too demanding for the controller or non-achievable because its dynamics is too fast, the vehicle might become unstable. In order to address this issue, autonomous navigation systems usually include a high-level path planner to generate smooth reference trajectories to be followed by the vehicle using a low-level controller. Usually a set of waypoints is given in GPS coordinates, normally from a map, in order to apply a smooth point-to-point control trajectory [11, 12]

Synthetic phosphoethanolamine-modified oligosaccharides reveal the importance of glycan length and substitution in biofilm-inspired assemblies

Bacterial biofilm matrices are nanocomposites of proteins and polysaccharides with remarkable mechanical properties. Efforts understanding and tuning the protein component have been extensive, whereas the polysaccharide part remained mostly overlooked. The discovery of phosphoethanolamine (pEtN) modified cellulose in E. coli biofilms revealed that polysaccharide functionalization alters the biofilm properties. To date, the pattern of pEtN cellulose and its mode of interactions with proteins remains elusive. Herein, we report a model system based on synthetic epitomes to explore the role of pEtN in biofilm-inspired assemblies. Nine pEtN-modified oligosaccharides were synthesized with full control over the length, degree and pattern of pEtN substitution. The oligomers were co-assembled with a representative peptide, triggering the formation of fibers in a length dependent manner. We discovered that the pEtN pattern modulates the adhesion of biofilm-inspired matrices, while the peptide component controls its stiffness. Unnatural oligosaccharides tune or disrupt the assembly morphology, revealing interesting targets for polysaccharide engineering to develop tunable bio-inspired materials