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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...
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...
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...
We propose a method for navigation of autonomous underwater vehicle based on visual odometry with regard to the conditions of the local maneuvers. The method is based on the SLAM-algorithm for stereo images and recognition algorithm for re-visited places. The operation of the algorithm for places recognition is based on using of virtual network for coordinate binding, which is constructed at the time...
Map retrieval, the problem of similarity search over a large collection of 3D pointset maps previously built by mobile robots, is crucial for autonomous navigation in indoor and outdoor environments. Bag-of-words (BoW) methods constitute a popular approach to map retrieval; however, these methods have extremely limited descriptive ability because they ignore the spatial layout information of the local...
In this paper we propose a new approach to recovering the relative position and orientation of a pair of platforms moving on the plane by fusing the kinds of estimates provided by visual odometry systems with distance measurements obtained from ranging radio systems. By combining these two complementary sources of information we are able to provide estimates that could not be obtained using either...
We address the problem of modeling complex target behavior using a stochastic model that integrates object dynamics, statistics gathered from the environment and semantic knowledge about the scene. The method exploits prior knowledge to build point-wise polar histograms that provide the ability to forecast target motion to the most likely paths. Physical constraints are included in the model through...
Over the past few decades, robot actuators with variable stiffness or impedance control have been developed. This control adjusts the stiffness of the task space of joint space, enabling the robot to perform explosive tasks and to interact with environments and humans. However, planning the robot stiffness is a difficult task, except in a few optimal control problems, such as maximizing the output...
Therapy environments for robot-assisted stroke rehabilitation are mostly static, in that objects are earmarked for different functional tasks, object locations remain fixed, trajectories are predefined and tasks manually selected. This work advocates the need for a therapy environment that allows dynamic object positioning, different objects can be used for the same functional task and tasks can be...
We present a neuro-dynamic architecture for the generation of movement of the hand toward a visual target that integrates movement planning based on visual input, movement initiation and termination, the generation of the time courses of virtual trajectories of the hand in Cartesian space, and their transformation into virtual joint trajectories and muscle forces. The architecture captures properties...
Error feedback is critical for supporting motor adaptation in rehabilitation, sports, piloting, and skilled manual tasks. Error augmentation interventions, in which participants' errors are amplified with either visual or haptic feedback during training has shown success over repetitive practice. Here we show that the statistical tendencies arising from free movement exploration can improve error...
We present a method for the three-dimensional (3D) steering of a flexible needle under 3D ultrasound guidance. The proposed solution is based on a duty-cycling visual servoing strategy we designed in a previous work, and on a new needle tracking algorithm for 3D ultrasound. The flexible needle modeled as a polynomial curve is tracked during automatic insertion using particle filtering. This new tracking...
We introduce the modelling and control of a rolling microrobot. The microrobot is capable of manipulating micro-objects through the use of a magnetic visual control system. This system consists of a rod-shaped microrobot, a magnetic actuation system and a visual control system. Motion of the rolling microrobot on a supporting surface is induced by a rotating magnetic field. As the robot is submerged...
This paper is about life-long vast-scale localisation in spite of changes in weather, lighting and scene structure. Building upon our previous work in Experience-based Navigation [1], we continually grow and curate a visual map of the world that explicitly supports multiple representations of the same place. We refer to these representations as experiences, where a single experience captures the appearance...
Motor Learning is heavily governed by sensory feedback, and artificially enhancing feedback influences learning as seen in our previous works. This study provides a model-based approach in determining the optimal gain schedules for augmented feedback on a visuomotor learning task. Using Gaussian process regression, we modeled the phenomenological process of learning to operate a robot with visual...
This paper is about building maps which not only contain the traditional information useful for localising — such as point features — but also embeds a spatial model of expected localiser performance. This often overlooked second-order information provides vital context when it comes to map use and planning. Our motivation here is to improve the performance of the popular Teach and Repeat paradigm...
Brain-computer interface (BCI) is currently developed as an alternative technology with a potential to restore lost motor function in patients with neurological injuries. In this paper, we describe an integrated system of a non-invasive electroencephalogram (EEG)-based BCI with a non-invasive functional electrical stimulation (FES). This system enables the direct brain control of upper limbs to achieve...
The use of unmanned aerial vehicles (UAV) offers a unique possibility to capture visual information in areas which are hard to reach or dangerous for humans. For UAVs to become a standard tool in visual inspection, it is of utmost importance that the aerial robot can be operated efficiently by a non-expert UAV pilot and that the navigation system is robust enough to remain operational in rough, industrial...
This paper presents a solution to the 3D Range-Only beacon localization problem using a Sum of Gaussians (SOG) filter together with an Active Localization method, which is based on the minimization of the beacon position uncertainty, in order to ensure the problem observability and a fast convergence. The method is applied to autonomously locate a subsea panel and home to it in order to establish...
Neurological deficits after cerebrovascular accidents very frequently disrupt the kinematics of voluntary movements with the consequent impact in daily life activities. Robotic methodologies enable the quantitative characterization of specific control deficits needed to understand the basis of functional impairments and to design effective rehabilitation therapies. In a group of right handed chronic...
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