[Show abstract][Hide abstract] ABSTRACT: In this paper, we investigate the use of a robot's gaze to improve the timing and subjective experience of face-to-face robot-to-human handovers. Based on observations of human gaze behaviors during face-to-face human–human handovers, we implement various gaze behaviors on a PR2 humanoid robot. We conducted two consecutive robot-to-human handover studies. Results show that when the robot continually gazes at a projected handover position while handing over an object, the human receivers reach for the object significantly earlier than when the robot looks down, away from the handover location; further, when the robot continually gazes at the receiver's face instead of the handover position, the receivers reach for the object even earlier. When the robot—instead of continually gazing at a location—transitions its gaze from the handover position to the receivers' face, or vice versa, the receivers' reach time did not improve; however, the receivers perceive these gaze transitions to better communicate handover timing than continual gazes. Finally, the receivers perceive the robot to be more likeable and anthropomorphic when it looks at their face than when it does not. Findings from our studies indicate that robot's use of gaze can help improve both fluency and subjective experience of the robot-to-human handover interactions.
International Journal of Social Robotics 06/2015; DOI:10.1007/s12369-015-0305-z · 1.21 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Ulcer is one of the most common symptoms of many serious diseases in the human digestive tract. Especially for the ulcers in the small bowel where other procedures cannot adequately visualize, wireless capsule endoscopy (WCE) is increasingly being used in the diagnosis and clinical management. Because WCE generates large amount of images from the whole process of inspection, computer-aided detection of ulcer is considered an indispensable relief to clinicians. In this paper, a two-staged fully automated computer-aided detection system is proposed to detect ulcer from WCE images. In the first stage, we propose an effective saliency detection method based on multi-level superpixel representation to outline the ulcer candidates. To find the perceptually and semantically meaningful salient regions, we first segment the image into multi-level superpixel segmentations. Each level corresponds to different initial region sizes of the superpixels. Then we evaluate the corresponding saliency according to the color and texture features in superpixel region of each level. In the end, we fuse the saliency maps from all levels together to obtain the final saliency map. In the second stage, we apply the obtained saliency map to better encode the image features for the ulcer image recognition tasks. Because the ulcer mainly corresponds to the saliency region, we propose a saliency max-pooling method integrated with the Locality-constrained Linear Coding (LLC) method to characterize the images. Experiment results achieve promising 92.65% accuracy and 94.12% sensitivity, validating the effectiveness of the proposed method. Moreover, the comparison results show that our detection system outperforms the state-ofthe- art methods on the ulcer classification task.
[Show abstract][Hide abstract] ABSTRACT: A robot that can fluently hand over objects to people can be useful in many applications. In an effort to develop a fluent robot-to-human handover system, this work investigates people's behavioural responses to a robot that hands over objects to them while using different types of gaze cues. In our previous work, we found empirical evidence that the use of a robot's head gaze can affect a person's timing of reaching towards the offered object. In this paper, we investigate this effect further by exploring the manner in which human's reaching and gaze behaviours are affected by a robot's head gaze. We conducted a video-based investigation of 97 naïve participants' behavioural responses to robot-to-human handovers. Through a frame-by-frame analysis, we recorded a detailed timeline of the robot's and human's gaze and reaching behaviours. Results confirm the finding from our previous study that the robot's head gaze can significantly impact the timing of human receiver's reaching behaviour during handovers. In addition, our results demonstrate that the robot's head gaze affects human's gaze behaviour during handovers, and this effect explains some unexpected findings in our previous work.
2014 IEEE International Conference on Robotics and Biomimetics; 12/2014
[Show abstract][Hide abstract] ABSTRACT: To learn object models for robotic manipulation, unsupervised methods cannot
provide accurate object structural information and supervised methods require a
large amount of manually labeled training samples, thus interactive object
segmentation is developed to automate object modeling. In this article, we
formulate a novel dynamic process for interactive object segmentation, and
develop a solution based on particle filter and active learning so that a robot
can manipulate and learn object structures incrementally and automatically. We
demonstrate our method with a humanoidrobot on different types of objects, and
compare its segmentation performancewith established methods on selected
objects. The result shows that our approach allows more accurate object
modeling and reveals richer object structural information.
[Show abstract][Hide abstract] ABSTRACT: In a robot-centered smart home, the robot observes the home states with its
own sensors, and then it can change certain object states according to an
operator's commands for remote operations, or imitate the operator's behaviors
in the house for autonomous operations. To model the robot's imitation of the
operator's behaviors in a dynamic indoor environment, we use multi-relational
chains to describe the changes of environment states, and apply inverse
reinforcement learning to encoding the operator's behaviors with a learned
reward function. We implement this approach with a mobile robot, and do five
experiments to include increasing training days, object numbers, and action
types. Besides, a baseline method by directly recording the operator's
behaviors is also implemented, and comparison is made on the accuracy of home
state evaluation and the accuracy of robot action selection. The results show
that the proposed approach handles dynamic environment well, and guides the
robot's actions in the house more accurately.
[Show abstract][Hide abstract] ABSTRACT: In order to share information in the cloud for multi-robot systems, efficient data transmission is essential for real-time operations such as coordinated robotic missions. As a limited resource, bandwidth is ubiquitously required by applications among physical multi-robot systems. In this paper, we proposed a hierarchical auction-based mechanism, namely LQM (Link Quality Matrix)-auction. It consists of multiple procedures, such as hierarchical auction, proxy scheduling. Note that the proposed method is designed for real-time resource retrieval for physical multi-robot systems, instead of simulated virtual agents. We validate the proposed mechanism through real-time experiments. The results show that LQM-auction is suitable for scheduling a group of robots, leading to optimized performance for resource retrieval.
IEEE International Conference on Robotics & Automation (ICRA), Hong Kong Convention and Exhibition Center; 05/2014
[Show abstract][Hide abstract] ABSTRACT: Data association is a fundamental problem in multisensor fusion, tracking, and localization. The joint compatibility test is commonly regarded as the true solution to the problem. However, traditional joint compatibility tests are computationally expensive, are sensitive to linearization errors, and require the knowledge of the full covariance matrix of state variables. The paper proposes a posterior-based joint compatibility test scheme to conquer the three problems mentioned above. The posterior-based test naturally separates the test of state variables from the test of observations. Therefore, through the introduction of the robot movement and proper approximation, the joint test process is sequentialized to the sum of individual tests; therefore, the test has O(n) complexity (compared with O(n2) for traditional tests), where n denotes the total number of related observations. At the same time, the sequentialized test neither requires the knowledge to the full covariance matrix of state variables nor is sensitive to linearization errors caused by poor pose estimates. The paper also shows how to apply the proposed method to various simultaneous localization and mapping (SLAM) algorithms. Theoretical analysis and experiments on both simulated data and popular datasets show the proposed method outperforms some classical algorithms, including sequential compatibility nearest neighbor (SCNN), random sample consensus (RANSAC), and joint compatibility branch and bound (JCBB), on precision, efficiency, and robustness.
[Show abstract][Hide abstract] ABSTRACT: In this paper, a novel method is proposed to recover and extract the original signal parameters from the saturated multifrequency sinusoid wave signals. It makes use of the zero-crossing characteristics of the multifrequency sinusoid signals, to collect valid samples in unsaturated parts of the signals. On these valid samples, the amplitudes and phases of the specific original ac sensing signals can be linearly computed by applying the least square method. The simulation results show that the proposed method has satisfactory accuracy even with very large saturation ( ~ 10 times of the saturation limit) and large dc offset, which frees us from the restriction to avoid the signal saturation problem in the signal acquisition. The method is realized by the software algorithm, and no longer requires the common used hardware-the phase sensitive detection circuit. Hence when it is applied to the magnetic coupling system, we will obtain much simpler system composition, higher accuracy, and high execution speed.
[Show abstract][Hide abstract] ABSTRACT: Networked multi-robot systems benefit from a large amount of heterogeneous online data on the server, and enable poor-equipped robots to fulfill complex tasks. However, as a major bottleneck of practical network, the limited bandwidth is lack of consideration. In the matter of fact, resource competition is pervasive for practical networked robotic applications. We propose a multi-robot negotiation mechanism in this paper. It includes a game theory based auction for allocating resources that are shared among robot clients, such as the network bandwidth. We validate the proposed strategy by a joint-surveillance scenario. Experimental results demonstrate that the proposed framework achieves excellent Quality of Service (QoS) performance under the condition of resource competition, where a shared network with limited bandwidth is optimized.
Proceeding of the IEEE International Conference on Information and Automation, Yinchuan, China; 08/2013
[Show abstract][Hide abstract] ABSTRACT: Recently, applying control theory to regulate the intracellular mRNA level was introduced as a new direction for gene regulation. However, the high nonlinearity in the gene regulatory networks imposes significant challenges in control design. As a well understood benchmark example, the GAL regulatory network in S. cerevisiae was recently proposed as a test-bed system for validating theoretical control algorithms in cellular systems. A simple proportional feedback control approach was previously proposed for regulating the intracellular mRNA level in the GAL network, however, there were still limitations with its use to control the nonlinear GAL network. To improve the performance and effectiveness, this paper proposes an advanced nonlinear control strategy. The reduced mathematical model for the GAL network is reorganized into a nonlinear affine system. Then, a partial feedback linearization control approach was employed to regulate the concentration of a protein at a desired level. For validating the control approach in experimental studies, we choose Gal1p as a measurable output, instead of GAL1 mRNA used in the previous study. Simulation results demonstrate that this control approach can shorten the convergence time between states comparing with the proportional feedback control.
International Journal of Information Acquisition 04/2013; 09(01). DOI:10.1142/S0219878913500022
[Show abstract][Hide abstract] ABSTRACT: Natural orifice translumenal endoscopic surgery (NOTES) is the latest surgery paradigm in which the abdominal cavity is accessed via the body's natural orifice, e.g., vagina, mouth, etc. Compared with traditional laparoscopic surgery, NOTES completely eliminates the skin incision and therefore benefits the patients in several aspects such as less post-operative pain, shorter recovery period, fewer complications, etc. Due to the unique characteristics of NOTES, instruments for traditional laparoscopic surgery are not suitable for NOTES and hence novel hardware design is necessary for facilitating system development. This paper gives an overview of the state of the arts in the development of surgical instruments for NOTES, particularly with a focus on the promising robotic endoscopes.
Journal of Mechanics in Medicine and Biology 04/2013; 13(2-02):1350044. DOI:10.1142/S0219519413500449 · 0.73 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: For the demands of surgical navigation, this paper proposes some simple 3-D point reconstruction methods. These methods regard the perpendicular feet on back-projection lines as the measurements of a 3-D point, since these feet are close to the 3-D point. And then the methods utilize the distance between 3-D point and camera and error propagation rules to adjust the weights of the feet. Finally, the weighted average of these feet is taken as the final estimation for the 3-D point. They are easy to implement, and can be used in both biocular systems and multiocular systems. Especially, as these methods have closed-form solutions, their errors can be predicted by using error propagation rules. Experiments show that they are faster and more accurate than iterative methods and their error covariance matrix can be exactly predicted.
[Show abstract][Hide abstract] ABSTRACT: This paper introduces a novel tracking framework for robots that can adapt various appearance changes of object and also owns the ability of reacquisition after drift. Two classifiers, LaRank and Online Random Ferns, are adopted to realize this tracking algorithm. The former one maintains the adaptive tracking using a Condensation-based method with an online support vector machine (SVM) as observation model, which also provides the reliable image patch samples to detector for updating. The other one is in charge of the task of detection in order to redetect the object when the target drifts. We also present a refinement strategy to improve the tracker's performance by discarding the support vector corresponding to possible wrong updates by a matching template after re-initialization. The experiments on benchmark dataset compare our tracking method with several other state-of-the-art algorithms, demonstrating a promising performance of the proposed framework.
Robotics and Automation (ICRA), 2013 IEEE International Conference on; 01/2013
[Show abstract][Hide abstract] ABSTRACT: Wireless capsule endoscopy (WCE) is an advanced, patient-friendly imaging technique that enables close examination of the entire small intestine. Since it usually takes hours to review all the video data even by professional clinician, the automatic computer-aided technique is highly demanded. This paper presents a hierarchical methodology for detecting key frames in WCE images. In the first stage, we choose key frames whose changes of information entropies take the local maximum by automatic threshold to cut the images into several sub clots. Then AP clustering method is applied in each clot to extract the second stage key frames. Our method maintains the temporal information and maximizes the content distance. Experimental results demonstrate that the proposed techniques achieve inspiring performance with fidelity 0.9206 and compression ratio 0.9125 on average.
Mechatronics and Automation (ICMA), 2013 IEEE International Conference on; 01/2013
[Show abstract][Hide abstract] ABSTRACT: We propose an efficient and effective magnetic tracking method in this paper. The tracking method is based on tri-axial transmitting coils and uniaxial sensing of the generated electromagnetic field. Three mutually orthogonal transmitting coils are excited simultaneously with alternating current (AC) signals of different frequency. At a specific position, the sum of amplitude square of the three different frequency sensing signals will reach maximum when the uniaxial coil points to the tri-axial transmitting coils. The maximum value is reciprocally proportional to the cube of the distance between the transmitter and receiver. By processing the output signals from the uniaxial sensing coil when it is rotating, the direction and distance between the sensing coil and transmitting coils can be decided with an efficient method with low calculation overheads. Experiments were conducted to validate the proposed method.