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This paper proposes a self-supervised monocular depth estimation algorithm under multiple constraints, which can generate the corresponding depth map end-to-end based on RGB images. On this basis, based on the traditional visual simultaneous localisation and mapping (VSLAM) framework, a dynamic object detection framework based on deep learning is introduced, and dynamic objects in the scene are culled during mapping.

Typical SLAM algorithms or data sets assume a static environment and do not consider the potential consequences of accidentally adding dynamic objects to a 3D map. This shortcoming limits the applicability of VSLAM in many practical cases, such as long-term mapping. In light of the aforementioned considerations, this paper presents a self-supervised monocular depth estimation algorithm based on deep learning. Furthermore, this paper introduces the YOLOv5 dynamic detection framework into the traditional ORBSLAM2 algorithm for the purpose of removing dynamic objects.

Compared with Dyna-SLAM, the algorithm proposed in this paper reduces the error by about 13%, and compared with ORB-SLAM2 by about 54.9%. In addition, the algorithm in this paper can process a single frame of image at a speed of 15–20 FPS on GeForce RTX 2080s, far exceeding Dyna-SLAM in real-time performance.

This paper proposes a VSLAM algorithm that can be applied to dynamic environments. The algorithm consists of a self-supervised monocular depth estimation part under multiple constraints and the introduction of a dynamic object detection framework based on YOLOv5.

The purpose of this paper is to investigate the effect of different heating approaches during thermal rounding of polymer powders on powder bulk properties such as particle size, shape and flowability, as well as on the yield of process.

This study focuses on the rounding of commercial high-density polyethylene polymer particles in two different downer reactor designs using heated walls (indirect heating) and preheated carrier gas (direct heating). Powder bulk properties of the product obtained from both designs are characterized and compared.

Particle rounding with direct heating leads to a considerable increase in process yield and a reduction in powder agglomeration compared to the design with indirect heating. This subsequently leads to higher powder flowability. In terms of shape, indirect heating yields not only particles with higher sphericity but also entails substantial agglomeration of the rounded particles.

Shape modification via thermal rounding is the decisive step for the success of a top-down process chain for selective laser sintering powders with excellent flowability, starting with polymer particles from comminution. This report provides new information on the influence of the heating mode (direct/indirect) on the performance of the rounding process and particle properties.