waashk/dblp huggingface dataset:
view planning and automated data acquisition for three-dimensional modeling of complex sites. constructing highly detailed three-dimensional (3-d) models of large complex sites using range scanners can be a time-consuming manual process. one of the main drawbacks is determining where to place the scanner to obtain complete coverage of a site. we have developed a system for automatic view planning called vueplan. when combined with our mobile robot, avenue, we have a system that is capable of modeling large-scale environments with minimal human intervention throughout both the planning and acquisition phases. the system proceeds in two distinct stages. in the initial phase, the system is given a two-dimensional site footprint with which it plans a minimal set of sufficient and properly constrained covering views. we then use a 3-d laser scanner to take scans at each of these views. when this planning system is combined with our mobile robot it automatically computes and executes a tour of these viewing locations and acquires them with the robot's onboard laser scanner. these initial scans serve as an approximate 3-d model of the site. the planning software then enters a second phase in which it updates this model by using a voxel-based occupancy procedure to plan the next best view (nbv). this nbv is acquired, and further nbvs are sequentially computed and acquired until an accurate and complete 3-d model is obtained. a simulator tool that we developed has allowed us to test our entire view planning algorithm on simulated sites. we have also successfully used our two-phase system to construct precise 3-d models of real-world sites located in new york city: uris hall on the campus of columbia university and fort jay on governors island. &copy; 2009 wiley periodicals, inc.
conops and autonomy recommendations for vtol small unmanned aerial system based on hurricane katrina operations. this field study examines vertical takeoff and landing (vtol) small unmanned aerial system (suas) operations conducted as part of an 8-day structural inspection task following hurricane katrina in 2005. from the observations of the 32 flights spread over 12 missions, four key findings are identified for concept of operations (conops) and the next level of artificial intelligence for rotary-wing suass operating in cluttered urban environments. these findings are (1) the minimum useful standoff distance from inspected structures is 2&ndash;5 m, (2) omnidirectional sensor capabilities are needed for obstacle avoidance, (3) global positioning system waypoint navigation is unnecessary, and (4) these operations require three operators for one suas. based on the findings and other observations, a crewing organization and flight operations protocol for suass are proposed. needed directions in research and development are also discussed. these recommendations are expected to contribute to the design of platforms, sensors, and artificial intelligence as well as facilitate the acceptance of suass in the workplace. &copy; 2009 wiley periodicals, inc.
lidar and vision-based pedestrian detection system. a perception system for pedestrian detection in urban scenarios using information from a lidar and a single camera is presented. two sensor fusion architectures are described, a centralized and a decentralized one. in the former, the fusion process occurs at the feature level, i.e., features from lidar and vision spaces are combined in a single vector for posterior classification using a single classifier. in the latter, two classifiers are employed, one per sensor-feature space, which were offline selected based on information theory and fused by a trainable fusion method applied over the likelihoods provided by the component classifiers. the proposed schemes for sensor combination, and more specifically the trainable fusion method, lead to enhanced detection performance and, in addition, maintenance of false-alarms under tolerable values in comparison with single-based classifiers. experimental results highlight the performance and effectiveness of the proposed pedestrian detection system and the related sensor data combination strategies. &copy; 2009 wiley periodicals, inc.
three-dimensional mapping with time-of-flight cameras. this article investigates the use of time-of-flight (tof) cameras in mapping tasks for autonomous mobile robots, in particular in simultaneous localization and mapping (slam) tasks. although tof cameras are in principle an attractive type of sensor for three-dimensional (3d) mapping owing to their high rate of frames of 3d data, two features make them difficult as mapping sensors, namely, their restricted field of view and influences on the quality of range measurements by high dynamics in object reflectivity; in addition, currently available models suffer from poor data quality in a number of aspects. the paper first summarizes calibration and filtering approaches for improving the accuracy, precision, and robustness of tof cameras independent of their intended usage. then, several ego motion estimation approaches are applied or adapted, respectively, in order to provide a performance benchmark for registering tof camera data. as a part of this, an extension to the iterative closest point algorithm has been developed that increases the robustness under restricted field of view and under larger displacements. using an indoor environment, the paper provides results from slam experiments using these approaches in comparison. it turns out that the application of tof cameras is feasible to slam tasks, although this type of sensor has a complex error characteristic. &copy; 2009 wiley periodicals, inc.
robust outdoor visual localization using a three-dimensional-edge map. visual localization systems that are practical for autonomous vehicles in outdoor industrial applications must perform reliably in a wide range of conditions. changing outdoor conditions cause difficulty by drastically altering the information available in the camera images. to confront the problem, we have developed a visual localization system that uses a surveyed three-dimensional (3d)-edge map of permanent structures in the environment. the map has the invariant properties necessary to achieve long-term robust operation. previous 3d-edge map localization systems usually maintain a single pose hypothesis, making it difficult to initialize without an accurate prior pose estimate and also making them susceptible to misalignment with unmapped edges detected in the camera image. a multihypothesis particle filter is employed here to perform the initialization procedure with significant uncertainty in the vehicle's initial pose. a novel observation function for the particle filter is developed and evaluated against two existing functions. the new function is shown to further improve the abilities of the particle filter to converge given a very coarse estimate of the vehicle's initial pose. an intelligent exposure control algorithm is also developed that improves the quality of the pertinent information in the image. results gathered over an entire sunny day and also during rainy weather illustrate that the localization system can operate in a wide range of outdoor conditions. the conclusion is that an invariant map, a robust multihypothesis localization algorithm, and an intelligent exposure control algorithm all combine to enable reliable visual localization through challenging outdoor conditions. &copy; 2009 wiley periodicals, inc.
leaving flatland: efficient real-time three-dimensional perception and motion planning. in this article we present the complete details of the architecture and implementation of leaving flatland, an exploratory project that attempts to surmount the challenges of closing the loop between autonomous perception and action on challenging terrain. the proposed system includes comprehensive localization, mapping, path planning, and visualization techniques for a mobile robot to operate autonomously in complex three-dimensional (3d) indoor and outdoor environments. in doing so we integrate robust visual odometry localization techniques with real-time 3d mapping methods from stereo data to obtain consistent global models annotated with semantic labels. these models are used by a multiregion motion planner that adapts existing two-dimensional planning techniques to operate in 3d terrain. all the system components are evaluated on a variety of real-world data sets, and their computational performance is shown to be favorable for high-speed autonomous navigation. &copy; 2009 wiley periodicals, inc.
a bayesian regression approach to terrain mapping and an application to legged robot locomotion. we deal with the problem of learning probabilistic models of terrain surfaces from sparse and noisy elevation measurements. the key idea is to formalize this as a regression problem and to derive a solution based on nonstationary gaussian processes. we describe how to achieve a sparse approximation of the model, which makes the model applicable to real-world data sets. the main benefits of our model are that (1) it does not require a discretization of space, (2) it also provides the uncertainty for its predictions, and (3) it adapts its covariance function to the observed data, allowing more accurate inference of terrain elevation at points that have not been observed directly. as a second contribution, we describe how a legged robot equipped with a laser range finder can utilize the developed terrain model to plan and execute a path over rough terrain. we show how a motion planner can use the learned terrain model to plan a path to a goal location, using a terrain-specific cost model to accept or reject candidate footholds. to the best of our knowledge, this was the first legged robotics system to autonomously sense, plan, and traverse a terrain surface of the given complexity. &copy; 2009 wiley periodicals, inc.
path-following algorithms and experiments for an unmanned surface vehicle. this paper addresses the problem of path following in two-dimensional space for underactuated unmanned surface vehicles (usvs), defining a set of guidance laws at the kinematic level. the proposed nonlinear lyapunov-based control law yields convergence of the path-following error coordinates to zero. furthermore, the introduction of a virtual controlled degree of freedom for the target to be followed on the path removes singularity behaviors present in other guidance algorithms proposed in the literature. some heuristic approaches are then proposed to face the problem of speed of advance adaptation based on path curvature measurement and steering action prediction. finally a set of experimental results of all the proposed guidance laws, carried out with the charlie usv, demonstrates the feasibility of the proposed approach and the performance improvements, in terms of precision in following the reference path and transient reduction, obtained by introducing speed adaptation heuristics. &copy; 2009 wiley periodicals, inc.
navigating with ranging radios: five data sets with ground truth. here we present five large data sets with range-only measurements between a mobile robot and stationary nodes. each data set consists of range measurements, surveyed locations of the stationary radio nodes, dead-reckoned trajectory of the robot, and ground truth from a sophisticated inertial navigation system-global positioning system mounted on a robot traveling several kilometers at a time. range measurements are made with two radio-based ranging systems: a rfid tag-based ranging system and an ultra&ndash;wide band ranging system. all the data are accurately time-stamped and presented in standard formats (i.e., text files). in addition to the raw data, we present some noise characteristics of the two different ranging systems to offer insight into the quality of the range data from each system. &copy; 2009 wiley periodicals, inc.
gaussian process modeling of large-scale terrain. building a model of large-scale terrain that can adequately handle uncertainty and incompleteness in a statistically sound way is a challenging problem. this work proposes the use of gaussian processes as models of large-scale terrain. the proposed model naturally provides a multiresolution representation of space, incorporates and handles uncertainties aptly, and copes with incompleteness of sensory information. gaussian process regression techniques are applied to estimate and interpolate (to fill gaps in occluded areas) elevation information across the field. the estimates obtained are the best linear unbiased estimates for the data under consideration. a single nonstationary (neural network) gaussian process is shown to be powerful enough to model large and complex terrain, effectively handling issues relating to discontinuous data. a local approximation method based on a &ldquo;moving window&rdquo; methodology and implemented using k-dimensional (kd)-trees is also proposed. this enables the approach to handle extremely large data sets, thereby completely addressing its scalability issues. experiments are performed on large-scale data sets taken from real mining applications. these data sets include sparse mine planning data, which are representative of a global positioning system&ndash;based survey, as well as dense laser scanner data taken at different mine sites. further, extensive statistical performance evaluation and benchmarking of the technique has been performed through cross-validation experiments. they conclude that for dense and-or flat data, the proposed approach will perform very competitively with grid-based approaches using standard interpolation techniques and triangulated irregular networks using triangle-based interpolation techniques; for sparse and-or complex data, however, it would significantly outperform them. &copy; 2009 wiley periodicals, inc.
performance of laser and radar ranging devices in adverse environmental conditions. a comparative evaluation of millimeter-wave radar and two-dimensional scanning lasers in dust and rain conditions for sensor applications in field robotics is presented. a robust and reliable method for measuring the level of suspended dust (or other obscurant media) by determining the transmission coefficient is developed and used for quantitative assessment of sensor performance. the criteria of target acquisition reliability, precision, and accuracy under varying environmental conditions are assessed via sensor operation in a controlled environment. this environment generated dust and rain of varying densities. sensor performance is also assessed for the potential effect on digital terrain mapping and haul truck localization due to sensor-specific behaviors in these conditions (e.g., false targets, increased noise). trials on a research electric face shovel are conducted to test observed behaviors. it is concluded that laser scanners are suitable for environments with transmissions exceeding 92&percnt;&ndash;93&percnt;-m for targets closer than 25 m. the radar remained relatively unaffected by the generated conditions of rain (50&ndash;70 mm-h) and dust (10-m visibility); however, its accuracy (0.1 m with a corner reflector and 0.3 m on a haul truck), free-space clutter, and scan rate were insufficient for locating unmodified haul trucks for this application. &copy; 2009 wiley periodicals, inc.
coverage path planning algorithms for agricultural field machines. in this article, a coverage path planning problem is discussed in the case of agricultural fields and agricultural machines. methods and algorithms to solve this problem are developed. these algorithms are applicable to both robots and human-driven machines. the necessary condition is to cover the whole field, and the goal is to find as efficient a route as possible. as yet, there is no universal algorithm or method capable of solving the problem in all cases. two new approaches to solve the coverage path planning problem in the case of agricultural fields and agricultural machines are presented for consideration. both of them are greedy algorithms. in the first algorithm the view is from on top of the field, and the goal is to split a single field plot into subfields that are simple to drive or operate. this algorithm utilizes a trapezoidal decomposition algorithm, and a search is developed of the best driving direction and selection of subfields. this article also presents other practical aspects that are taken into account, such as underdrainage and laying headlands. the second algorithm is also an incremental algorithm, but the path is planned on the basis of the machine's current state and the search is on the next swath instead of the next subfield. there are advantages and disadvantages with both algorithms, neither of them solving the problem of coverage path planning problem optimally. nevertheless, the developed algorithms are remarkable steps toward finding a way to solve the coverage path planning problem with nonomnidirectional vehicles and taking into consideration agricultural aspects. &copy; 2009 wiley periodicals, inc.
maneuverability and path following control of wheeled mobile robot in the presence of wheel skidding and slipping. this paper addresses the path following control problem of wheeled mobile robots in the presence of wheel skidding and slipping. a conditional global positioning system (gps)-based path following controller is proposed for four generic wmrs to achieve high-precision path following performance. the proposed controller utilizes real-time kinematic-gps and other aiding sensors to determine the robot's pose and wheel skidding and slipping perturbations to achieve accurate path following control. the reported simulation and experimental results suggest that with this control scheme, the wmrs are able to maneuver with precision. &copy; 2009 wiley periodicals, inc. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
segmented slam in three-dimensional environments. simultaneous localization and mapping (slam) has been shown to be feasible in many small, two-dimensional, structured domains. the next challenge is to develop real-time slam methods that enable robots to explore large, three-dimensional, unstructured environments and allow subsequent operation in these environments over long periods of time. to circumvent the scale limitations inherent in slam, the world can be divided up into more manageable pieces. slam can be formulated on these pieces by using a combination of metric submaps and a topological map of the relationships between submaps. the contribution of this paper is a real-time, three-dimensional slam approach that combines an evidence grid&ndash;based volumetric submap representation, a robust rao&ndash;blackwellized particle filter, and a topologically flexible submap segmentation framework and map representation. we present heuristic methods for deciding how to segment the world and for reconstructing large-scale metric maps for the purpose of closing loops. we demonstrate our method on a mobile robotic platform operating in large, three-dimensional environments. &copy; 2009 wiley periodicals, inc.
developing monocular visual pose estimation for arctic environments. arctic regions present one of the harshest environments on earth for people or mobile robots, yet many important scientific studies, particularly those involving climate change, require measurements from these areas. for the successful deployment of mobile sensors in the arctic, a high-quality localization system is required. although a global positioning system can provide coarse positioning (within several meters), it cannot provide any orientation information. a single-camera-pose-estimation system is presented, based on visual odometry techniques, which is capable of operating in the feature-poor environments of the arctic. to validate the system, a prototype rover was developed and fielded on a glacier in alaska. the resulting pose estimates compare favorably to values obtained by hand registering the same video sequence. although pose errors do accumulate over time, these errors are typical of a standard odometry system but obtained in an environment where standard odometry is not practical. &copy; 2009 wiley periodicals, inc. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
mixed kinematic and dynamic sideslip angle observer for accurate control of fast off-road mobile robots. automation in outdoor applications (farming, surveillance, military activities, etc.) requires highly accurate control of mobile robots, at high speed, although they are moving on low-grip terrain. to meet such expectations, advanced control laws accounting for natural ground specificities (mainly sliding effects) must be derived. in previous work, adaptive and predictive control algorithms, based on an extended kinematic representation, have been proposed. satisfactory experimental results have been reported (accurate to within &plusmn;10 cm, whatever the grip conditions), but at limited velocity (below 3 m&middot;s-1). nevertheless, simulations reveal that control accuracy is decreased when vehicle speed is increased (up to 10 m&middot;s-1). in particular, oscillations are observed at curvature transition. this drawback is due to delays in sideslip angle estimation, unavoidable at high speed because only an extended kinematic representation was used. in this paper, a mixed backstepping kinematic and dynamic observer is designed to improve observation of these variables: the slow-varying data are still estimated from a kinematic representation, which is then injected into a dynamic observer to supply reactive and reliable sliding variable (namely sideslip angle) estimation, without increasing the noise level. the algorithm is evaluated via advanced simulations (coupling adams and matlab software) investigating high-speed capabilities. actual experiments at lower speed (experimental platform maximum velocity) demonstrate the benefits of the proposed approach. &copy; 2009 wiley periodicals, inc. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player