Eye movements accompanying daydreaming, visual imagery, and thought suppression.

Relationship between oculometer activity during the waking state and internally produced cognitive processes such as daydreaming and visual imagery were studied by means of continuous electro-oculograms. 24 female college students served as Ss. Eye movements and blinks were more frequent following instructions to engage in active rather than passive thinking; more frequent following instructions to suppress than to generate a wish. Greater ocular activity was observed under instructions to imagine moving than to imagine static visual imagery, the difference holding for both eyes open and closed conditions. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

DenseCut: Densely Connected CRFs for Realtime GrabCut

Figure‐ground segmentation from bounding box input, provided either automatically or manually, has been extremely popular in the last decade and influenced various applications. A lot of research has focused on high‐quality segmentation, using complex formulations which often lead to slow techniques, and often hamper practical usage. In this paper we demonstrate a very fast segmentation technique which still achieves very high quality results. We propose to replace the time consuming iterative refinement of global colour models in traditional GrabCut formulation by a densely connected crf . To motivate this decision, we show that a dense crf implicitly models unnormalized global colour models for foreground and background. Such relationship provides insightful analysis to bridge between dense crf and GrabCut functional. We extensively evaluate our algorithm using two famous benchmarks. Our experimental results demonstrated that the proposed algorithm achieves an order of magnitude (10×) speed‐up with respect to the closest competitor, and at the same time achieves a considerably higher accuracy.     

Robotics-assisted demining with Gryphon

The threat and consequences of landmines have led to a multitude of alternative research activities in the field of demining. While mine sensor-focused research has been intensive, there has been relatively less attention given to the problem of automating the detection and removal procedure. Understandably, autonomous robot operation and interaction in unstructured field environments are difficult. This paper addresses this by presenting a robot meant to assist humanitarian demining by providing a cheap, fast, reliable and safe alternative to human deminers risking their lives on a daily basis. The robot, named Gryphon, is able to autonomously scan 2 m² at a time with any type of mine sensor payload. It then presents acquired sensor images to the operator who selects which spots need further investigation or prodding. The robot then appropriately marks the terrain with paint or marking plates. Gryphon has been extensively field tested in Japan, Croatia and Cambodia.     

Realization of a Pheromone Potential Field for Autonomous Navigation by Radio Frequency Identification

This paper presents the results of our research that aims to implement autonomous navigation with an artificial pheromone system. As social insects, a group of ants show advanced performance in their activity by using a chemical substance called a pheromone. By introducing an artificial pheromone system composed of data carriers and autonomous robots, the robotic system creates a potential field to navigate their group. Using this approach we have developed a pheromone density model to realize the function of pheromones with the help of data carriers. We intend to show the effectiveness of the proposed system by performing computer simulations and real experiments for one and two dimensions. The proposed system can be used for an autonomous navigation system. Results are discussed and future works are proposed.     

Robot Motion Planning in Dynamic Uncertain Environments

In the real world, mobile robots often operate in dynamic and uncertain environments. Therefore, it is necessary to develop a motion planner capable of real-time planning that also addresses uncertainty concerns. In this paper, a new algorithm, Dynamic AO* (DAO*), is developed for navigation tasks of mobile robots. DAO* not only performs a good anytime behavior and offers a fast replanning framework, but also considers the motion uncertainty. Moreover, by incorporating DAO* with D* Lite, a new planning architecture, DDAO*, is represented to efficiently search in large state spaces. Finally, simulations and experiments are shown to verify the efficiency of the proposed algorithms.     

Design of a vision-guided microrobotic colonoscopy system

In this paper presents a novel design of a microrobotic colonoscopy (MRC) system. The proposed microrobotic colonoscope is an autonomous vision-guided device, which is designed to navigate inside a human colon for the purpose of observation, analysis and diagnosis. It is developed to alleviate the shortcomings in the existing manual colonoscopy procedure, which is generally cumbersome and tedious for the colonoscopist and painful to the patients. The MRC system is divided into three areas, i.e. design of the microrobotic device, path planning and guidance, and offboard control system. A novel design of the microrobot is presented which utilizes a pneumatic mechanism to achieve locomotion and steering. A new concept of clamping the colon wall based on passive vacuum devices is suggested. General mathematical analysis governing the differential steering of the robotic tip is also described. The path planning of the microrobot is carried out based on the sensory fusion utilizing the quantitative parameters derived from the captured images and the tactile sensors. An off-board control system to control the directional movements of the microrobot is explained. The proposed colonoscopy system was tested with physical models and animal colons, and the experimental observations are presented.     

Visual control of two aerial micro-robots by insect-based autopilots

In the framework of our research on biologically inspired microrobotics, we have developed two novel Automatic Flight Control Systems (AFCs): OCTAVE ( Optical flow Control sysTem for Aerospace VEhicles) and OSCAR ( Optical Scanning sensor for the Control of Autonomous Robots), both based on insects' visuomotor control systems. OCTAVE confers upon a tethered aerial robot (the OCTAVE robot) the ability to perform terrain following. OSCAR gives a tethered aerial robot (the OSCAR robot) the ability to fixate and track a contrasting target with a high level of accuracy. Both OCTAVE and OSCAR robots are based on optical velocity sensors, the principle of which is based on the results of previous electrophysiological studies on the fly's Elementary Motion Detectors (EMDs) performed at our laboratory. Both processing systems described are light enough to be mounted on-board Micro-Air Vehicles (MAVs) with an avionic payload small enough to be expressed in grams rather than kilograms.     

Collision dynamics of a visual target marker for small-body exploration

MUSES-C mission is the world first sample and return attempt to or from a near-Earth asteroid. In deep space, it is hard to navigate, guide and control a spacecraft on a real-time basis remotely from the earth, mainly due to the communication delay. Thus, autonomy and robotics technologies are required for final approach and landing to an unknown body. In the final descent phase, cancellation of the horizontal speed relative to the surface of the landing site is essential. During the touchdown and sampling phase, the spacecraft will be navigated relative to the asteroid surface using an optical target marker (TM) placed on the asteroid surface. By using the TM as a reference point, navigation during the landing phase will be much more reliable and precise. Thus, it is important to design a TM with as small a coefficient of restitution as possible to reduce the settling time. To develop a small coefficient of restitution of less than 0.1 in vertical direction, the authors propose a novel TM, which is constructed out of a shell with beads stored internally. To better predict the performance of such a TM, analytical and numerical investigations are performed. The validity and the effectiveness of the proposed method are confirmed and evaluated by numerical simulations and flight results.     

Robot Localization in Indoor Environments Using Radio Frequency Identification Technology and Stereo Vision

In this paper, a novel method of obstacle recognition and localization for mobile robots using radio frequency identification (RFID) technology and stereo vision is proposed. It is inexpensive, flexible and easy to use in practical environments. As information about the obstacles or environment can be written in ID tags, the proposed method can detect the obstacles easily and quickly compared with other methods. RF is not so stable, so the Bayes rule was introduced to calculate the probability where the ID tag exists in order to improve the accuracy of localizing obstacles with the ID tags. Then the stereo camera starts to process the image of the region of interest where the obstacle exists. The proposed method does not need to process all the image and easily gets some information about obstacles such as size, and color, and thus decreases the processing computation. Research on RFID technology integrating stereo vision to localize an indoor mobile robot has also been performed. This paper introduces the architecture of the proposed method and some experimental results.     

Moment feature-based three-dimensional tracking using two high-speed vision systems

When considering real-world applications of robot control with visual servoing, both three-dimensional (3-D) information and a high feedback rate are required. We have developed a 3-D target-tracking system with a 1-ms feedback rate using two high-speed vision systems called Column Parallel Vision (CPV) systems. To obtain 3-D information, such as position, orientation and shape parameters of the target object, a feature-based algorithm has been introduced using moment feature values extracted from vision systems for a spheroidal object model. Also, we propose a new 3-D self-windowing method to extract the target in 3-D space using epipolar geometry, which is an extension of the conventional self-windowing method in 2-D images.