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Robotic graspable object recognition is a crucial ingredient in many exciting autonomous manipulation applications. However, identifying complex image features from limited data remains largely unsolved. In this paper, we leverage the advantages of two kinds of feature representation approaches, kernel descriptors and deep neural networks, to present a novel hierarchical feature learning framework...
In this paper, we explore how the integration of auditory and visual cues can help teach the timing of motor skills for the purpose of motor function rehabilitation. We conducted a study using Amazon's Mechanical Turk in which 106 participants played a virtual therapy game requiring wrist movements. To validate that our results would translate to trends that could also be observed during robotic rehabilitation...
In daily life it is necessary to learn skills that can be applied in different tasks and different contexts. Usually these skills are acquired by observation or by direct physical training with another expert person. The critical point is to know which is the best possible way to achieve this knowledge acquisition. In this work we have proposed a collaborative environment where subjects with different...
Motor relearning after stroke is a lengthy process which should be continued after patients get discharged from the clinic. This project aims at developing a system for telerehabilitation which enables stroke patients to exercise at home autonomously or under supervision of a therapist. The system includes haptic therapy devices which are more promising and beneficial for stroke rehabilitation than...
We present a framework from vision based hand movement prediction in a real-world human-robot collaborative scenario for safety guarantee. We first propose a perception submodule that takes in visual data solely and predicts human collaborator's hand movement. Then a robot trajectory adaptive planning submodule is developed that takes the noisy movement prediction signal into consideration for optimization...
Error-Related Potentials (ErrPs) have been used lately in order to improve several existing Brain-Computer Interface (BCI) applications. In our study we investigate the contribution of ErrPs in a Steady State Visual Evoked Potential (SSVEP) based BCI. An extensive study is presented in order to discover the limitations of the proposed scheme. Using Common Spatial Patterns and Random Forests we manage...
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...
It is necessary for a long-range space rover to model its 3D environment in order to identify drivable roads while avoiding obstacles and hazards. We present a method of modeling a 3D environment, while identifying drivable roads and obstacles, by accumulating a sequence of point clouds from stereo. The technical issues we deal with are how to avoid error accumulation in registering point clouds using...
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...
Vision is one of the most important senses that helps people interact with the real world. Commonly visually impaired develop their other senses to feel their surroundings, but in certain cases, this is not enough. The senses can be disturbed by noise or illness. For this reason, many artifacts have been developed to help this group of people. Artifacts such as white canes or guide dogs help sightless...
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...
Two less addressed issues of deep reinforcement learning are (1) lack of generalization capability to new goals, and (2) data inefficiency, i.e., the model requires several (and often costly) episodes of trial and error to converge, which makes it impractical to be applied to real-world scenarios. In this paper, we address these two issues and apply our model to target-driven visual navigation. To...
3Sergey Levine is with Google Brain, Mountain View, CA 94043, USA. We present a policy search method for learning complex feedback control policies that map from high-dimensional sensory inputs to motor torques, for manipulation tasks with discontinuous contact dynamics. We build on a prior technique called guided policy search (GPS), which iteratively optimizes a set of local policies for specific...
Understanding physical phenomena is a key competence that enables humans and animals to act and interact under uncertain perception in previously unseen environments containing novel objects and their configurations. Developmental psychology has shown that such skills are acquired by infants from observations at a very early stage. In this paper, we contrast a more traditional approach of taking a...
We describe a new series pneumatic artificial muscle (sPAM) and its application as an actuator for a soft continuum robot. The robot consists of three sPAMs arranged radially around a tubular pneumatic backbone. Analogous to tendons, the sPAMs exert a tension force on the robot's pneumatic backbone, causing bending that is approximately constant curvature. Unlike a traditional tendon driven continuum...
A variety of end-user devices involving keypoint-based mapping systems are about to hit the market e.g. as part of smartphones, cars, robotic platforms, or virtual and augmented reality applications. Thus, the generated map data requires automated evaluation procedures that do not require experienced personnel or ground truth knowledge of the underlying environment. A particularly important question...
When full automation of mobile robots is not possible or desirable, teleoperation constitutes an alternative. The human operator can be supported with direction cues to facilitate localization or navigation. These cues are presented typically in the auditory, haptic and/or visual modality. An experiment was conducted to evaluate systematically and empirically the (uni-modal and multi-modal) effects...
In this paper, we propose a method for improving the maneuverability of master-slave systems. We aim at reproducing human skillfulness and dynamic performance in master-slave robots by using assist control for human operators. In this paper, we tackle a reaching task performed by a master-slave robot and propose an operation assist algorithm based on visual feedback control. The algorithm consists...
Percutaneous needle procedures are mostly carried out with the guidance of 2D ultrasound (US) imaging. US images are inherently noisy and their resolutions are low. Hence, target tracking can be challenging. Image based tracking methods can be used to track the needle and the target. This paper proposes visual tracking of multiple moving points, such as biopsy needles and targets, in 2D US images...
Many robotics and Augmented Reality (AR) systems that use sparse keypoint-based visual maps operate in large and highly repetitive environments, where pose tracking and localization are challenging tasks. Additionally, these systems usually face further challenges, such as limited computational power, or insufficient memory for storing large maps of the entire environment. Thus, developing compact...
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