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This paper presents a system for classifying images based on Deep Learning and applied in the recognition of traffic signals aiming to increase road safety increased road safety using autonomous and semi-autonomous intelligent robotic vehicles. This Advanced Driver Assistance System (ADAS) is a system created to automate vehicles, but also to help the human drivers to increase safety and the respect...
In bridge buildings, concrete is widely used because its materials are considerably low-cost and it has high plasticity. However, some drawbacks exist in this kind of bridges, and crack is the most common ones. In order to avoid the cracks in bridge buildings becoming worse, it is necessary to periodically perform the inspection for it. Thus, a bridge inspection robot system with machine vision is...
Robots operating in populated environments encounter many different types of people, some of whom might have an advanced need for cautious interaction, because of physical impairments or their advanced age. Robots therefore need to recognize such advanced demands to provide appropriate assistance, guidance or other forms of support. In this paper, we propose a depth-based perception pipeline that...
Indoor object recognition is a key task for mobile robot indoor navigation. In this paper, we proposed a pipeline for indoor object detection based on convolutional neural network (CNN). With the proposed method, we first pre-train an off-line CNN model by using both public Indoor Dataset and private frames of videos (FoV) dataset. This is then followed by a selective search process to extract a region...
The various techniques are proposed for better semantic segmentation. The neuro-fuzzy technique is proposed for learning common nature between object and structure. The proposed technique work better for robotic environment for fast and efficient results. The proposed technique provides better accuracy as compared to previous technique and work better in semantic segmentation as compared to previous...
In a large-scale indoor environment, a mobile robot needs a proper internal representation of the surrounding environment to carry out its tasks. The metric (grid-based) map and topological map are two common internal representations in robotic realm. In order to take advantage of the two kinds of environmental representations, this paper aims to construct a topological map of an indoor environment...
Localizing functional regions of objects or affordances is an important aspect of scene understanding and relevant for many robotics applications. In this work, we introduce a pixel-wise annotated affordance dataset of 3090 images containing 9916 object instances. Since parts of an object can have multiple affordances, we address this by a convolutional neural network for multilabel affordance segmentation...
Segmenting 3D objects from a set of disordered point cloud is always one challenge work in Bin-pi cking systems. In this paper, an easy and valid algorithm is proposed to solve this problem. The point data set obtained from a low-cost depth camera, RealSense, can be quickly filtered to be a much clean compact one, significantly saving the computing resources. The filtered points set is next divided...
Currently, the only mass-market service robots are floor cleaners and lawn mowers. Although available for more than 20 years, they mostly lack intelligent functions from modern robot research. In particular, the obstacle detection and avoidance is typically a simple physical collision detection. In this work, we discuss a prototype autonomous lawn mower with camera-based non-contact obstacle avoidance...
Training a deep neural network is complicated due to the input distribution of each layer changes during training. Small changes are amplified throughout the network and consequently the covariate-shift is likely to occur. That is why small learning is critical but small learning rates is the root to slow training process and may even prevent the escape of suboptimal local minima. This paper purposed...
Loop closure detection (LCD) is a process trying to find a match between the current and a previously visited locations in SLAM. The bag of words (BoW) is a popular approach used in LCD, however, limited by perceptual aliasing primarily due to vector quantization. This paper proposes an improved method of the BoW called spatial partitioning BoW(SPBoW). We first apply scene segmentation to integrate...
Based on the scale-invariant feature transform, this paper presents an approach to keyboard recognition. Not only the skewed keyboard can be corrected, but also the keys in the keyboard can be located. Experimental results confirm the feasibility of the proposed method.
Vision localization apple bagging robot is researched in this paper for young apples. The key technologies of the young fruit stereoscopic images recognizing and positioning are studied in the visible light of the natural environment. Firstly, the Otsu segmentation algorithm is used to preprocess the collected young apple images. Secondly, the improved connected component labeling algorithm is used...
Weed scouting is an important part of modern integrated weed management but can be time consuming and sparse when performed manually. Automated weed scouting and weed destruction has typically been performed using classification systems able to classify a set group of species known a priori. This greatly limits deployability as classification systems must be retrained for any field with a different...
Robust scene understanding of outdoor environments using passive optical sensors is a onerous and essential task for autonomous navigation. The problem is heavily characterized by changing environmental conditions throughout the day and across seasons. Robots should be equipped with models that are impervious to these factors in order to be operable and more importantly to ensure safety in the real-world...
We propose an alternative to the common approaches to the topological segmentation in structured or unstructured environments, Contour-Based Segmentation. It is faster and equally accurate, without the need of fine tuning parameters or heuristics. During robotic exploration, we propose an incremental version that reduces the processing time by reusing the previous segmentation. Tests demonstrate the...
Conventional approaches to semantic segmentation are inappropriate for robotic applications, as they focus on pixel-level performance and give little significance to spurious object detections. This paper presents a region-based conditional random field model for semantic segmentation that focuses on object-level performance, recognising that in a robotics context, false object detections can have...
We propose an intelligent visuomotor system that interacts with the environment and memorizes the consequences of actions. As more memories are recorded and more interactions are observed, the agent becomes more capable of predicting the consequences of actions and is, thus, better at planning sequences of actions to solve tasks. In previous work, we introduced the aspect transition graph (ATG) which...
Modern robotics involves partial or complete automation systems, which in turn requires the presence of elements of artificial intelligence. That's why appears a necessity in system of pattern recognition.
Recognition of human manipulation actions together with the analysis and execution by a robot is an important issue. Also, perception of spatial relationships between objects is central to understanding the meaning of manipulation actions. Here we would like to merge these two notions and analyze manipulation actions using symbolic spatial relations between objects in the scene. Specifically, we define...
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