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We present a novel method based on saliency and segmentation to generate generic object candidates from RGB-D data. Our method uses saliency as a cue to roughly estimate the location and extent of the objects present in the scene. Salient regions are used to glue together the segments obtained from over-segmenting the scene by either color or depth segmentation algorithms, or by a combination of both...
The octopus uses the arm-swimming behavior primarily for escape, defense, or foraging. This mode of locomotion is comprised of two strokes, with the arms opening slowly and closing rapidly, and generally results in considerable propulsive acceleration. In light of the recent development by our group of an octopus-like eight-arm underwater robot, we are interested to analyze the details of the biological...
The goal of saliency detection is to highlight objects in image data that stand out relative to their surrounding. Therefore, saliency detection aims to capture regions that are perceived as important. The most recent bottom-up approaches for saliency detection measure contrast based on visual features in 2D scenes, ignoring depth value. This work presents an effective method to measure saliency by...
In order to realize many of the potential benefits associated with robotically assisted minimally invasive surgery, the robot must be more than a remote controlled device. Currently using a surgical robot can be challenging, fatiguing, and time consuming. Teaching the robot to actively assist surgical tasks, such as suturing, has the potential to vastly improve both patient outlook and the surgeon's...
In this paper, we present a novel learning framework for traversable region detection. Firstly, we construct features from the super-pixel level which can reduce the computational cost compared to pixel level. Multi-scale super-pixels are extracted to give consideration to both outline and detail information. Then we classify the multiple-scale super-pixels and merge the labels in pixel level. Meanwhile,...
In continuously operating robotic systems, efficient representation of the previously seen camera feed is crucial. Using a highly efficient compression coreset method, we formulate a new method for hierarchical retrieval of frames from large video streams collected online by a moving robot. We demonstrate how to utilize the resulting structure for efficient loop-closure by a novel sampling approach...
This paper reports on a method to perform robust visual relocalization between temporally separated sets of underwater images gathered by a robot. The place recognition and relocalization problem is more challenging in the underwater environment mainly due to three factors: 1) changes in illumination; 2) long-term changes in the visual appearance of features because of phenomena like biofouling on...
As robots begin to collaborate with humans in everyday workspaces, they will need to understand the functions of tools and their parts. To cut an apple or hammer a nail, robots need to not just know the tool's name, but they must localize the tool's parts and identify their functions. Intuitively, the geometry of a part is closely related to its possible functions, or its affordances. Therefore, we...
In this paper we describe a new technique for segment meaningfully objects autonomously. Traditional segmentation scheme tries to find the best segmentation result at some trade off between level of user input and level of meaningful segmentation. Segmentation with user input will ensure better segmentation result but is not applicable to the realtime autonomous robotics system. For most of the commercial...
Knowing the terrain is vital for small autonomous robots traversing unstructured outdoor environments. We present a technique using 3D laser point clouds combined with RGB camera images to classify terrain into four pre-defined classes: grass, sand, concrete, and metal. Our technique first segments the point cloud into distinct regions and then applies a simple classifier to determine the classification...
For autonomous navigation in urban environments, the ability to detect road intersections in advance is crucial, especially in the absence of auxiliary geographic information. In this paper we investigate a 3D Point Cloud based solution for intersection recognition and road segment classification. We set up the intersection recognition problem as one of decoding a linear-chain Conditional Random Field...
In this paper, we introduce an efficient point-cloud segmentation algorithm, inspired by efficient segmentation (also named as super-pixel extraction). It uses parameterised “normal words” as distance measures, which are obtained by clustering of surface normals. We estimate the surface normals by the sparse tensor voting framework, which enables adaptive structural extraction, even for the case of...
The vision system of the mobile robot is a low-level function that provides the required target information of the current environment for the upper vision tasks. The real-time performance and robustness of object segmentation in cluttered environments is still a serious problem in robot visions. In this paper, a new real-time indoor scene segmentation method based on RGB-D image, is presented and...
Segmentation and mapping of planar building facades (PBFs) can increase a robot's ability of scene understanding and localization in urban environments which are often quasi-rectilinear and GPS-challenged. PBFs are basic components of the quasi-rectilinear environment. We propose a passive vision-based PBF segmentation and mapping algorithm by combining both appearance and geometric constraints. We...
The spatial configuration of actuated flexible instruments is fundamental for control applications in robotic noscar surgery. In these operations, the instruments are inserted in the channels of a flexible guide equipped with an endoscopic camera. In this paper we propose to estimate the position of the instruments of the Anubis platform (Karl Storz) using the endoscopic images provided by the embedded...
In order for robots to function in unstructured environments in interaction with humans, they must be able to reason about the world in a semantic meaningful way. An essential capability is to segment the world into semantic plausible object hypotheses. In this paper we propose a general framework which can be used for reasoning about objects and their functionality in manipulation activities. Our...
The robotized endoscope holder in laparoscopic surgery allows a surgeon to control the endoscope without the intervention of an assistant. For providing the more convenient interactions between the surgeon and a robotized endoscope holder, we propose a new method for the automatic 3D-tracking of laparoscopic instruments in real-time. The method is based on the measurement of the 3D positions of the...
The handling of twist-locks has been a heavy burden for the container industry. To address this challenge, we are developing a customized mobile manipulator for handling the twist-locks. In this paper, we propose a fast normal computation algorithm for depth image, which is able to use normal deviation along eight directions to extract key points for segmenting points into objects on manipulation...
The idea that connected convex surfaces, separated by concave boundaries, play an important role for the perception of objects and their decomposition into parts has been discussed for a long time. Based on this idea, we present a new bottom-up approach for the segmentation of 3D point clouds into object parts. The algorithm approximates a scene using an adjacency-graph of spatially connected surface...
This paper describes a vision-based 3D navigation technique for path-following control of Quad rotor Aerial Visual-Teach-and-Repeat system. The navigation method is developed on Funnel Lane theory, which defines possible positions to fly straight. The navigation calculation utilizes the reference images and features to compute the desired heading angle and height during path following. The type of...
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