The lack of force feedback is considered one of the major limitations in Robot Assisted Minimally Invasive Surgeries. Since add-on sensors are not a practical solution for clinical environments, in this paper we prese...
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The lack of force feedback is considered one of the major limitations in Robot Assisted Minimally Invasive Surgeries. Since add-on sensors are not a practical solution for clinical environments, in this paper we present a force estimation approach that starts with the reconstruction of a 3D deformation structure of the tissue surface by minimizing an energy functional. A Recurrent Neural Network-Long Short Term Memory (RNN-LSTM) based architecture is then presented to accurately estimate the applied forces. According to the results, our solution offers long-term stability and shows a significant percentage of accuracy improvement, ranging from about 54% to 78%, over existing approaches.
SocialRobot is a collaborative European project, which focuses on providing a practical and interactive robotic solution to improve the quality of life of elderly people. Having this in mind, a state of the art mobile...
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ISBN:
(纸本)9781467372435
SocialRobot is a collaborative European project, which focuses on providing a practical and interactive robotic solution to improve the quality of life of elderly people. Having this in mind, a state of the art mobile robot platform has been integrated with virtual social care technology to meet the elderly individual needs and requirements, following a human centered approach. In this paper, we make an overview of SocialRobot, addressing mainly the integration of the platform and the architecture developed for the project, as well as the existing robot services, the human-robot interactive scenarios prepared, and results extracted from experimental tests with the mobile robot platform.
Learning motor skills for robots is a hard task. In particular, a high number of degrees-of-freedom in the robot can pose serious challenges to existing reinforcement learning methods, since it leads to a high-dimensi...
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This paper proposes strategies for the driving and egress of a vehicle with a humanoid robot. To drive the vehicle, the RANSAC method was used to detect obstacles, and the Wagon model was used to control the steering ...
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ISBN:
(纸本)9781479968862
This paper proposes strategies for the driving and egress of a vehicle with a humanoid robot. To drive the vehicle, the RANSAC method was used to detect obstacles, and the Wagon model was used to control the steering and velocity of the vehicle with only a limited number of sensors which were installed on the humanoid robot. Additionally, a manual teleoperating method was used with the lane projection technique. For the egress motion, gain override and the Cartesian position/force control technique were used to interact with the vehicle structure. To overcome the disadvantages of a highly geared manipulator, a special technique was used that included modelled friction compensation and a non-complementary switching mode. DRC-HUBO+ used the proposed method to perform a vehicle driving and egress task in the DRC finals 2015.
In this paper, we present a P300 model for control of Cerebot - a mind-controlled humanoid robot, including a procedure of acquiring P300 signals, topographical distribution analysis of P300 signals, and a classificat...
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This paper presents an improved method to teleoperate impedance of a robot based on surface electromyography (EMG) and test it experimentally. Based on a linear mapping between EMG amplitude and stiffness, an incremen...
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The recent years have shown the emergence of heterogeneous system architecture (HSA), which offers massive computational power assembled into a compact design. computer vision applications with massive inherent parall...
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The recent years have shown the emergence of heterogeneous system architecture (HSA), which offers massive computational power assembled into a compact design. computer vision applications with massive inherent parallelism highly benefits from such heterogeneous processors with on-chip CPU and GPU units. The highly parallel and compute intensive parts of the application program can be mapped to the GPU while the control flow and high level tasks may run on the CPU. However, they pose considerable challenge to software development due to their hybrid architecture. Sharing of resources (GPU or CPU) among applications running concurrently, leads to variations in processing interval and prolonged processing intervals leads to low quality results (frame drops) for computer vision algorithms. In this work, we propose resource-awareness and self organisation within the application layer to adapt to available resources on the heterogeneous processor. The benefits of the new model is demonstrated using a widely used computer vision algorithm called Harris corner detector. A resource-aware runtime-system and a heterogeneous processor were used for evaluation and the results indicate a well constrained processing interval and reduced frame-drops. Our evaluations demonstrate up to 20% improvements in processing rate and accuracy of the detected corner points for Harris corner detection.
In this paper, we present a N200 model for control of a humanoid robot with mind. N200 is a major component of the motion visual evoked potential (mVEP) which can be used to detect the subject's intention. In orde...
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In this paper, we present a N200 model for control of a humanoid robot with mind. N200 is a major component of the motion visual evoked potential (mVEP) which can be used to detect the subject's intention. In order to acquire N200, we design a visual stimulus interface in which the activation of a stimulus is a bar scanning above the image of a humanoid robot behavior. By analyzing brain signals induced by this kind of stimulus and calculating some system indexes, the results of this study demonstrate that the designed interface can induce prominent N200 potentials, and another component P300 induced by this experiment can be considered as another characteristic of the feature vector to contribute to the classification. To our best knowledge, this paper would be the first report on an application of N200 model to control a humanoid robot with visual feedback in realtime.
In this paper, we devise a controller that achieves global uniform exponential stabilization of linear systems while avoiding singular input constraints, that is, the proposed controller never crosses a given input va...
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ISBN:
(纸本)9781467360890
In this paper, we devise a controller that achieves global uniform exponential stabilization of linear systems while avoiding singular input constraints, that is, the proposed controller never crosses a given input value g. We show that it is possible to solve this problem using two linear controllers and an appropriate switching logic, which leads to a hybrid controller.
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