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In this paper we present a new system for a mobile robot to generate an articulated scene model by analyzing complex dynamic 3D scenes. The system extracts essential knowledge about the foreground, like moving persons, and the background, which consists of all visible static scene parts. In contrast to other 3D reconstruction approaches, we suggest to additionally distinguish between static parts,...
We present a system for 2D robot mapping which is entirely based on line segment representation of the environment. The system consists of multiple modules, i.e. scan number reduction, global scan alignment, scan merging and segment-error filtering, which give an example of the simplicity of mid level data processing and the advanced possibilities opened by segment based design. The compact segment...
Visual teach-and-repeat navigation enables long-range rover autonomy without solving the simultaneous localization and mapping problem or requiring an accurate global reconstruction. During a learning phase, the rover is piloted along a route, logging images. After post-processing, the rover is able to repeat the route in either direction any number of times. This paper describes and evaluates the...
Although robot navigation in indoor environments has achieved great success, robots are unable to fully navigate these spaces without the ability to operate elevators, including those which the robot has not seen before. In this paper, we focus on the key challenge of autonomous interaction with an unknown elevator button panel. A number of factors, such as lack of useful 3D features, variety of elevator...
A new method of vision-based guidance line detection is developed to find guidance line in row crop fields for agricultural machinery, which uses the mathematical morphology to process images and segment crops in images and to extract target crops. The guidance line is fit with the least-square method according to the centroids of individual target crops or/and the central points of several pixel...
Autonomous robot navigation in unstructured outdoor environments is a challenging and largely unsolved area of active research. The navigation task requires identifying safe, traversable paths that allow the robot to progress towards a goal while avoiding obstacles. Machine learning techniques are well adapted to this task, accomplishing near-to-far learning by training appearance-based models using...
For a coexisting and collaborative society that incorporates humans and robots, the detection, tracking, and recognition of human motion are indispensable techniques for a robot to safely and securely interact with humans. The present paper proposes a motion tracking system using distributed network cameras that are placed in a sizeable environment, such as a street or a town. Model-based motion tracking...
One of the ultimate challenges in robotics is to manipulate an arbitrary object without knowing its exact shape beforehand. The shape is rather acquired on the spot via using a laser range scanner, structure from multiple views; therefore, maybe only partially observed and corrupted by a certain degree of noise. We propose an algorithm to identify available failsafe strategies capable of preventing...
Most large-scale public environments provide direction signs to facilitate the orientation for humans and to find their way to a goal location in the environment. Thus, for a robot operating in the same environment, it would be beneficial to interpret such signs correctly for a safe and efficient navigation. In this work, we propose a novel approach to infer the meaning of direction signs and to use...
A leading obstacles detection and recognition method based on binocular vision is mainly described in this paper. An edge fitting method based on the regional border of fusion segmentation image is used in fitting the edge of road, a viable region and suspected obstacles are obtained through fusing the fusion segmentation image and fitted edge. The method of partial edge contour extraction is used...
We present an integrated vision and robotic system that plays, and learns to play, simple physically-instantiated board games that are variants of TIC TAC TOE and HEXA-PAWN. We employ novel custom vision and robotic hardware designed specifically for this learning task. The game rules can be parametrically specified. Two independent computational agents alternate playing the two opponents with the...
The iterative closest points (ICP) algorithm is widely used for ego-motion estimation in robotics, but subject to bias in the presence of outliers. We propose a random sample consensus (RANSAC) based algorithm to simultaneously achieving robust and realtime ego-motion estimation, and multi-scale segmentation in environments with rapid changes. Instead of directly sampling on measurements, RANSAC matching...
Magnetic Resonance Imaging (MRI) guided prostate biopsy and brachytherapy has been introduced in order to enhance the cancer detection and treatment. For the accurate needle positioning, a number of robotic assistants have been developed. However, problems exist due to the strong magnetic field and limited workspace. Pneumatically actuated robots have shown the minimum distraction in the environment...
There are several applications for which it is important to both detect and communicate changes in data models. For instance, in some mobile robotics applications (e.g. surveillance) a robot needs to detect significant changes in the environment (e.g. a layout change) which it may achieve by comparing current data provided by its sensors with previously acquired data (e.g. map) of the environment...
A team of robots cooperating to quickly produce a map needs to share landmark information between members so that the local maps can be accurately merged. However, the appearance of landmarks as seen by members of the team can change dramatically due to the phenomenon of occlusion. We have previously presented an approach to landmark representation using Terrain Spatiograms an extension to image spatiograms...
Image-based scene representations enable a mobile robot to make a realistic prediction of its environment. Hence, it is able to rapidly detect changes in its surroundings by comparing a virtual image generated from previously acquired reference images and its current observation. This facilitates attentional control to novel events. However, illumination effects can impair attentional control if the...
A learning method capable of empowering a robot to successfully grasp a novel object through vision has recently been demonstrated, and generated much interest in the robotics community. In this paper we carefully analyze this new approach and apply dimensionality reduction techniques to decrease the number of features that need to be computed in order to classify whether a given pixel in an image...
It is interesting to observe from human visually guided tasks that visual feedback is not used for the entire movement, but only at end phases when our hand is near the target. We are able to move our hand from an initial position that is not within our field of view and transit smoothly and easily into visual feedback when the target is near. Inspired by this natural action, this paper presents a...
Insertion velocity, tip asymmetry, and shaft diameter may influence steerable needle insertion paths in soft tissue. In this paper we examine the effects of these variables on needle paths in ex vivo goat liver, and demonstrate practical applications of robotic needle steering for ablation, biopsy, and brachytherapy. All experiments were performed using a new portable needle steering robot that steers...
This paper describes an approach to interactive object categorization that couples exploratory behaviors and their resulting acoustic signatures to form object categories. The framework was tested with an upper-torso humanoid robot on a container/non-container categorization task. The robot used six exploratory behaviors (drop block, grasp, move, shake, flip, and drop object) and applied them to twenty...
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