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In this paper, we study the problem of controlling a two-dimensional robotic swarm with the purpose of achieving high level and complex spatio-temporal patterns. We use a rich spatio-temporal logic that is capable of describing a wide range of time varying and complex spatial configurations, and develop a method to encode such formal specifications as a set of mixed integer linear constraints, which...
Mobile wireless ad hoc network (MANET) becomes increasingly popular in responding to emergency situation. In this paper a possibility to support rescue team in monitoring heavy gas cloud with MANET comprised of mobile sensing devices is investigated. In the view of the current state of research, two methods for controlling mobile sensing devices during MANET self-organization are presented. The first...
With the development of numerous 3D sensing technologies, object registration on cross-source point cloud has aroused researchers' interests. When the point clouds are captured from different kinds of sensors, there are large and different kinds of variations. In this study, we address an even more challenging case in which the differently-source point clouds are acquired from a real street view....
Soft machine tables are industrial robots with a soft, computer-controlled, deformable surface. They are designed to manipulate objects placed on the surface by changing the surface shape. The current control approaches for the soft actuators embedded in the surface layer are open-loop, because appropriate sensors have not been developed, yet. In this report, we propose a solution based on an array...
A snake-like robot is a hyper-redundant robot. It has flexible movement ability and high stability with low center of gravity. It is very suitable for environment detection in the rugged road or narrow space. In this paper, a 16-DOFs snake robot is composed. It has ten 2-DOFs modular spherical-shape joints. The joints are arranged as the structure of "(Roll-Pitch)-(Roll-Pitch)-", where "(Roll-Pitch)"...
This paper presents a new large scale dataset targeting evaluation of local shape descriptors and 3d object recognition algorithms. The dataset consists of point clouds and triangulated meshes from 292 physical scenes taken from 11 different views, a total of approximately 3204 views. Each of the physical scenes contain 10 occluded objects resulting in a dataset with 32040 unique object poses and...
Multi-robot cooperative navigation in real-world environments is essential in many applications, including surveillance and search-and-rescue missions. State-of-the-art methods for cooperative navigation are often tested in ideal laboratory conditions and not ready to be deployed in real-world environments, which are often cluttered with static and dynamic obstacles. In this work, we explore a graph-based...
Expressive motion can situate a robot's attitude in its task motions, illustrating real-time reactions. Inspired by acting movement training, we construct path shape features that layer expression into a mobile robot's motion traversal. Our video-study results show that simple variations of path shape and orientation can influence human perceptions of a robot's task, focus, and confidence. We further...
Tactile data and kinesthetic cues are two important sensing sources in robot object recognition and are complementary to each other. In this paper, we propose a novel algorithm named Iterative Closest Labeled Point (iCLAP) to recognize objects using both tactile and kinesthetic information. The iCLAP first assigns different local tactile features with distinct label numbers. The label numbers of the...
Module localization is an important aspect of the operation of self-reconfigurable robots. The knowledge of spatial positions of modules, or at least of the overall shape which the modules form, is the usual prerequisite for reconfiguration planning. We present a general, decentralized algorithm for determining the positions of modules placed on a cubic grid from local sensor information. The connection...
We present a new descriptor for tactile 3D object classification. It is invariant to object movement and simple to construct, using only the relative geometry of points on the object surface. We demonstrate successful classification of 185 objects in 10 categories, at sparse to dense surface sampling rate in point cloud simulation, with an accuracy of 77.5% at the sparsest and 90.1% at the densest...
Accurate object shape knowledge provides important information for performing stable grasping and dexterous manipulation. When modeling an object using tactile sensors, touching the object surface at a fixed grid of points can be sample inefficient. In this paper, we present an active touch strategy to efficiently reduce the surface geometry uncertainty by leveraging a probabilistic representation...
We introduce in this paper visibility maps for robots of any shape, representing the reachability limit of the robot's motion and sensing in a 2D gridmap with obstacles. The brute-force approach to determine the optimal visibility map is computationally expensive, and prohibitive with dynamic obstacles. We contribute the Robot-Dependent Visibility Map (RDVM) as a close approximation to the optimal,...
Most modern approaches for tactile object recognition with robotic hands do not use proprioceptive data. In those that do, a limited number of objects with similar shapes is recognized. Furthermore, Self-Organizing Maps (SOM) based on raw values of joint angles/torques are frequently implemented which requires large sets of training data. In this paper, we present an approach based only on joint angles...
In this work we study the problem of exploring surfaces and building compact 3D representations of the environment surrounding a robot through active perception. We propose an online probabilistic framework that merges visual and tactile measurements using Gaussian Random Field and Gaussian Process Implicit Surfaces. The system investigates incomplete point clouds in order to find a small set of regions...
In this paper, we present deformable configuration control — a fully distributed algorithm that allows multiple robots to deform their configuration to avoid various shapes of obstacles while maintaining connectivity. Robots contacted with an obstacle first estimate the width of an obstacle by sharing bumped status of individual robots, and choose an appropriate obstacle avoidance scenarios between...
Contact force play is a significant role in success of the cardiac ablation. However, it is still challenging to estimate contact force when a catheter is under large bending and multiple contacts. This paper develops a new multi-section static model of the tendon-driven catheters for both real-time intrinsic force sensing and interaction control. The model allows estimating the catheter shape by...
Pushing is a motion primitive useful to handle objects that are too large, too heavy, or too cluttered to be grasped. It is at the core of much of robotic manipulation, in particular when physical interaction is involved. It seems reasonable then to wish for robots to understand how pushed objects move.
In this paper, we present a human detecting system based on three-dimensional(3D) point cloud by discriminating between human and other objects by using range sensor. Although the shape of same objects seen from a sensor according to the difference of distance between the object and a sensor, we divided some areas in the vicinity of a sensor (about 0.3m∼5m) by the difference of distance. Then, we...
The active perception makes an important step towards the integration of the sensing in the planning phase of the object manipulation. Closing the perception-planning loop iteratively, this helps to reduce the uncertainty in the sensing and planning offering better scene parsing and object manipulation applications. In this paper we show the active perception concept using an industrial like scene...
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