Affordance-Driven Next-Best-View Planning for Robotic Grasping

Grasping occluded objects in cluttered environments is an essential component in complex robotic manipulation tasks. In this paper, we introduce an AffordanCE-driven Next-Best-View planning policy (ACE-NBV) that tries to find a feasible grasp for target object via continuously observing scenes from new viewpoints. This policy is motivated by the observation that the grasp affordances of an occluded object can be better-measured under the view when the view-direction are the same as the grasp view. Specifically, our method leverages the paradigm of novel view imagery to predict the grasps affordances under previously unobserved view, and select next observation view based on the highest imagined grasp quality of the target object. The experimental results in simulation and on a real robot demonstrate the effectiveness of the proposed affordance-driven next-best-view planning policy. Project page: https://sszxc.net/ace-nbv/.Comment: Conference on Robot Learning (CoRL) 202

One-Shot High-Fidelity Talking-Head Synthesis with Deformable Neural Radiance Field

Talking head generation aims to generate faces that maintain the identity information of the source image and imitate the motion of the driving image. Most pioneering methods rely primarily on 2D representations and thus will inevitably suffer from face distortion when large head rotations are encountered. Recent works instead employ explicit 3D structural representations or implicit neural rendering to improve performance under large pose changes. Nevertheless, the fidelity of identity and expression is not so desirable, especially for novel-view synthesis. In this paper, we propose HiDe-NeRF, which achieves high-fidelity and free-view talking-head synthesis. Drawing on the recently proposed Deformable Neural Radiance Fields, HiDe-NeRF represents the 3D dynamic scene into a canonical appearance field and an implicit deformation field, where the former comprises the canonical source face and the latter models the driving pose and expression. In particular, we improve fidelity from two aspects: (i) to enhance identity expressiveness, we design a generalized appearance module that leverages multi-scale volume features to preserve face shape and details; (ii) to improve expression preciseness, we propose a lightweight deformation module that explicitly decouples the pose and expression to enable precise expression modeling. Extensive experiments demonstrate that our proposed approach can generate better results than previous works. Project page: https://www.waytron.net/hidenerf/Comment: Accepted by CVPR 202

Recent Progress of Natural Mineral Materials in Environmental Remediation

Organic contaminants, volatile organic compounds (VOCs), and heavy metals have posed long-term threats to the ecosystem and human health. Natural minerals have aroused widespread interest in the field of environmental remediation due to their unique characteristics such as rich resources, environmentally benign, and excellent photoelectric properties. This review briefly introduced the contributions of natural minerals such as sulfide minerals, oxide minerals, and oxysalt minerals in pollution control, which include organic pollution degradation, sterilization, air purification (NO VOCs oxidation), and heavy metal treatment by means of photocatalysis, Fenton catalysis, persulfate activation, and adsorption process. At last, the future challenges of natural mineral materials in pollution control are also outlooked

Recent Progress of Natural Mineral Materials in Environmental Remediation

Organic contaminants, volatile organic compounds (VOCs), and heavy metals have posed long-term threats to the ecosystem and human health. Natural minerals have aroused widespread interest in the field of environmental remediation due to their unique characteristics such as rich resources, environmentally benign, and excellent photoelectric properties. This review briefly introduced the contributions of natural minerals such as sulfide minerals, oxide minerals, and oxysalt minerals in pollution control, which include organic pollution degradation, sterilization, air purification (NO VOCs oxidation), and heavy metal treatment by means of photocatalysis, Fenton catalysis, persulfate activation, and adsorption process. At last, the future challenges of natural mineral materials in pollution control are also outlooked

Enhanced perovskite crystallization by the polyvinylpyrrolidone additive for high efficiency solar cells

Enhanced perovskite crystallization by the polyvinylpyrrolidone additive for high efficiency solar cell

Ruthenium oxychloride supported by manganese oxide for stable oxygen evolution in acidic media

Despite the recent advances in enhancing the durability and reducing the overpotential of ruthenium (Ru)-based electrocatalysts for acidic oxygen evolution reaction (OER), their stability hardly meets the requirement of practical application. Moreover, a cost-effective strategy to stabilize the highly active but unstable Ru species is desirable. Herein, we report a stable electrocatalyst for acidic OER by dispersing the Ru oxychloride active species into a manganese oxide support (RuOCl@MnOx) to form highly dispersed Ru-O-Mn without the alteration of vibrational modes and bond parameters of the MnO6 group, as suggested by Raman and synchrotron radiation characterization studies. The catalyst is stable for continuous operation over 280 h with an overpotential of 228 mV at 10 mA cm−2 and over 200 h at 100 mA cm−2, among the most stable low-mass-loading Ru-based OER electrocatalysts in acidic media. Complementary theoretical calculations ascribe the excellent stability to its high oxidation potential and low formation/surface energies, consistent with experimental observations. The enhanced activity is attributed to the four-coordinated Ru site that bears a low overpotential determined by the formation of O* from OH*. Our work thus offers a new strategy for synthesizing robust OER electrocatalysts of PEM electrolyzers with superior activity.Agency for Science, Technology and Research (A*STAR)Nanyang Technological UniversityPublished versionThe work was partially supported by A*STAR Science & Engineering Research Council AME IRG funding (A1983c0029) and Nanyang Technological University via an ACE grant (NTUACE2021-02). H. J. is thankful for financial support from the National Natural Science Foundation of China (Grant No. 21676216)