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A robot is expected to carry out a task autonomously with its own knowledge system. Using the knowledge system, the robot can recognize current situation and recall a proper sequence for performing an appropriate task in that situation. To build such knowledge system, the robot learns the knowledge from user demonstrations as if a child learns through interactions with parents and teachers. User demonstration...
This paper presents a method of identification and azimuth estimation for one or two concurrent speakers in simultaneous utterances. This method is applicable to human-machine interaction and robot audition. Identification and localization have been rarely mutually addressed and related works rely on time-frequency exploitation strategies to extract and treat each source's contribution to the received...
Robotic first responders have potential to significantly improve rescue efficiency and safety in search and rescue missions. To operate intelligently, a robot requires the capability to recognize critical objects in a disaster environment, in order to effectively locate victims and/or prevent secondary disasters. In this report, we introduce a novel dataset of Critical Objects for Response to Emergency...
Human Robot Interaction is a multidisciplinary field which involves developing, perceiving and assessing robotic systems. In effective communication, the understanding of emotions and intentions are essential. A robotic system that is capable of recognizing emotion states and synthesizing proper response would be beneficial for Human Robot Interaction (HRI). Human emotion recognition could be achieved...
Rotary-wing unmanned aerial vehicles (UAV) are being widely used in different applications due to its several features, such as mobility, lightweight, embedded processing and capability of flying in different height levels. Among the possible applications they are used in surveillance tasks, agriculture environments monitoring, power lines inspections and diseases detection in crops. The images captured...
The use of emotional states for Human-Robot Interaction (HRI) has attracted considerable attention in recent years. One of the most challenging tasks is to recognize the spontaneous expression of emotions, especially in an HRI scenario. Every person has a different way to express emotions, and this is aggravated by the complexity of interaction with different subjects, multimodal information and different...
Continuum tubular robots, which are constructed by telescoping pre-curved elastic tubes, are capable of balancing the force application and steerability during minimally invasive surgeries. These devices are able to reach the desired surgical sites in body cavities without colliding with critical blood vessels, nerves and tissues. However, the motion planning of continuum tubular robots is quite challenging...
We propose a discriminative compact scene descriptor for single-view cross-season place recognition. Unlike previous bag-of-words approaches which rely on a library of vector quantized visual features, the proposed scene descriptor is based on a library of raw image data (such as available visual experience, images shared by other colleague robots, and publicly available image data on the web) that...
An automated diagnosis methodology is necessary for the maintenance of superannuated social infrastructures. In this context, the hammering test is an efficient inspection method, and it has been widely used because of the resulting accuracy and efficiency of operation. While robotic automation of the hammering inspection method is highly desirable, the development of an automatic diagnostic algorithm...
We have studied the problem of retrieval of arbitrary object instances from a large point cloud data set. The context is autonomous robots operating for long periods of time, weeks up to months and regularly saving point cloud data. The ever growing collection of data is stored in a way that allows ranking candidate examples of any query object, given in the form of a single view point cloud, without...
We present an evaluation of standard image features in the context of long-term visual teach-and-repeat mobile robot navigation, where the environment exhibits significant changes in appearance caused by seasonal weather variations and daily illumination changes. We argue that in the given long-term scenario, the viewpoint, scale and rotation invariance of the standard feature extractors is less important...
We present a new mapping and navigation system based on human-recognizable landmarks with highly compact representations. Road segments, intersections and salient structures such as houses and trees are detected using vision and LiDAR data. The landmarks are entered in a sparse metrictopological map that is used for navigation. In contrast to traditional SLAM approaches, however, we only store the...
The use of social robots for elderly care is becoming ever more relevant, thus introducing new challenges which need to be solved to achieve acceptable performance. One fundamental task for a social robot is to move to the person of interest in order to start interacting or perform a service. In this paper we address the task of a robot having to navigate to a possibly occluded person, which needs...
This paper presents an audio-visual beat-tracking method for an entertainment robot that can dance in synchronization with music and human dancers. Conventional music robots have focused on either music audio signals or dancing movements of humans for detecting and predicting beat times in real time. Since a robot needs to record music audio signals by using its own microphones, however, the signals...
A necessary skill when using liquids in the preparation of food is to be able to estimate viscosity, e.g. in order to control the pouring velocity or to determine the thickness of a sauce. We introduce a method to allow a robotic kitchen assistant discriminate between different but visually similar liquids. Using a Kinect depth camera, surface changes, induced by a simple pushing motion, are recorded...
In this paper, we present a monocular visual-inertial odometry algorithm which, by directly using pixel intensity errors of image patches, achieves accurate tracking performance while exhibiting a very high level of robustness. After detection, the tracking of the multilevel patch features is closely coupled to the underlying extended Kalman filter (EKF) by directly using the intensity errors as innovation...
In general, the problems of objects' and rooms' categorizations for robotic applications have been addressed separately. The current trend is, however, towards a joint modelling of both issues in order to leverage their mutual contextual relations: object → room (e.g. the detection of a microwave indicates that the room is likely to be a kitchen), and room → object (e.g. if the robot is in a bathroom,...
Robust, scalable localization unlocks path-planning, obstacle avoidance as well as manipulation and thus is a core competency for many robotic applications. However, as we leave the lab and move out in the world, models of the environment no longer span distances of meters but kilometers in length. Now, gigabytes instead of megabytes of memory are required to hold the model of the environment required...
Robust object recognition is a crucial skill for robots operating autonomously in real world environments. Range sensors such as LiDAR and RGBD cameras are increasingly found in modern robotic systems, providing a rich source of 3D information that can aid in this task. However, many current systems do not fully utilize this information and have trouble efficiently dealing with large amounts of point...
We present a novel method for clustering segmented dynamic parts of indoor RGB-D scenes across repeated observations by performing an analysis of their spatial-temporal distributions. We segment areas of interest in the scene using scene differencing for change detection. We extend the Meta-Room method and evaluate the performance on a complex dataset acquired autonomously by a mobile robot over a...
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