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Knee arthroscopy is a very challenging surgical procedure that would strongly benefit from systems that can continuously map the inside of the knee, localize the arthroscope and surgical tools, and control instruments using visual information. A fundamental requirement of most of these systems is the correct and fast matching of visual features. Feature-based systems have been demonstrated in laparoscopy...
Autonomous scene understanding by object classification today, crucially depends on the accuracy of appearance based robotic perception. However, this is prone to difficulties in object detection arising from unfavourable lighting conditions and vision unfriendly object properties. In our work, we propose a spatial context based system which infers object classes utilising solely structural information...
In this paper the authors introduce a method focusing on the robustness improvement of the landmark tracking system for mobile robot operation in natural environments. We extract feature points from the data obtained by a stereo vision system with CenSurE (Center Surround Extremas for Realtime Feature Detection and Matching) used as a detector, and FREAK (Fast Retina Keypoint) as a descriptor. RANSAC...
A common problem in Brain-Machine Interface (BMI) is the variations in neural signals over time, leading to significant decrease in decoding performance if the decoder is not re-trained. However, frequent re-training is not practical in real use case. In our work, we found that a temporally more robust system may be achieved through the use of wavelet transform in feature extraction. We used wavelet...
Visual place recognition (VPR) in changing environments is an urgent challenge for long-term autonomous navigation. One recent ConvNet landmark-based approach exploits region landmarks coupled with ConvNet features to match images, and the approach has shown promising results under significant environmental and viewpoint changes. In this paper, we propose a robust ConvNet landmark-based system for...
Autonomous service mobile robots need to consistently, accurately, and robustly localize in human environments despite changes to such environments over time. Episodic non-Markov Localization addresses the challenge of localization in such changing environments by classifying observations as arising from Long-Term, Short-Term, or Dynamic Features. However, in order to do so, EnML relies on an estimate...
Obstacle Detection is a central problem for any robotic system, and critical for autonomous systems that travel at high speeds in unpredictable environment. This is often achieved through scene depth estimation, by various means. When fast motion is considered, the detection range must be longer enough to allow for safe avoidance and path planning. Current solutions often make assumption on the motion...
Nowadays, the technological and scientific research related to underwater perception is focused in developing more cost-effective tools to support activities related with the inspection, search and rescue of wreckages and site exploration: devices with higher autonomy, endurance and capabilities. Currently, specific tasks are already carried out by remotely-operated vehicles (ROV) and autonomous underwater...
One of the main recent research trends of the Italian Interuniversity Research Center on Integrated Systems for Marine Environment (ISME) is the use of marine cooperative teams of autonomous robots within the fields of security, prevention and management of emergencies at sea. Such fields are of worldwide interest for obvious reasons, but they have recently gained relevance in the current historical...
Place recognition has been intensively studied in the context of robot vision. BoW-based approach gains its popularity for its efficiency and robustness using features extracted from images. Many features have been examined in the past for place recognition purpose. However, there is no such feature that can outperform others in all environments. Each feature has its own advantage, thus, they should...
Vast variety of EMG signal applications have been proposed and practiced on EMG control system such as rehabilitation and prosthetic hand and so on. In this paper, a realization of a robust real time robotic arm control system is proposed. First, the root mean square (RMS) of EMG signal for a hand movement is measured and the measured EMG signal is transformed to a complex number. Secondly, the transformed...
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...
Visual tracking of unknown objects is an essential task in robotic perception, of importance to a wide range of applications. In the general scenario, the robot has no full 3D model of the object beforehand, just the partial view of the object visible in the first video frame. A tracker with this information only will inevitably lose track of the object after occlusions or large out-of-plane rotations...
An algorithm for the robust detection and recognition of gestures for the interaction between human and a domestic floor cleaner robot is presented. The gestures are selected through a user study, in which the participants are asked to show natural gestures to the robot in given specific interaction scenarios. The gestures selected are those repeated by majority of participants and consist both commanding...
Loop-closure detection, which is the ability to recognize a previously visited place, is of primary importance for robotic localization and navigation problems. We here introduce SAIL-MAP, a method for loop-closure detection based on vision only, applied to topological simultaneous localization and mapping (SLAM). Our method allows the matching of camera images using a novel saliency-based feature...
Interest points matching for aerial visual odometry using quadrotor MAV is tackled in this work. First, a set of sparse feature points are extracted using ORB detector. These are then grouped using Gradient Vector Flow (GVF) fields by finding points of high symmetry within the image. A robust matching strategy is introduced to improve the motion estimation. In order to validate ORB features matches,...
Many robotics applications nowadays use cameras for various task such as place recognition, localization, mapping etc. These methods heavily depend on image descriptors. A plethora of descriptors have recently been introduced but hardly any address the problem of illumination robustness. Herein we introduce an illumination robust image descriptor which we dub DIRD (Dird is an Illumination Robust Descriptor)...
In order to perform autonomous manipulation in underwater surveys, a robust seabed type classification technique is crucial. Seabed images convey a lot of information about seabed types and various image segmentation methods have been implemented to classify seabed types by analyzing the features of images such as contour and region. However, these strategies are not robust for diverse underwater...
Feature detection and feature matching are the most crucial parts in visual odometry process. In order to suit the real time process in visual odometry, both of the stages must be robust but at the same time are fast to compute. This paper presents the evaluation of Scale Invariant Feature Transform (SIFT) and Speeded Up Robust Feature (SURF) performances. The results show that SURF is outperform...
3D point cloud segmentation is the process of classifying point clouds into multiple homogeneous regions, the points in the same region will have the same properties. The segmentation is challenging because of high redundancy, uneven sampling density, and lack explicit structure of point cloud data. This problem has many applications in robotics such as intelligent vehicles, autonomous mapping and...
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