waashk/dblp huggingface dataset:
spanning-tree based coverage of continuous areas by a mobile robot. this paper considers the problem of covering a continuous planar area by a square-shaped tool attached to a mobile robot. using a tool-based approximation of the work-area, we present an algorithm that covers every point of the approximate area for tasks such as floor cleaning, lawn mowing, and field demining. the algorithm, called i>spanning tree covering (stc), subdivides the work-area into disjoint cells corresponding to the square-shaped tool, then follows a spanning tree of the graph induced by the cells, while covering every point precisely once. we present and analyze three versions of the stc algorithm. the first version is off-line, where the robot has perfect apriori knowledge of its environment. the off-line stc algorithm computes an optimal covering path in linear time o(i>n), where i>n is the number of cells comprising the approximate area. the second version of stc is on-line, where the robot uses its sensors to detect obstacles and construct a spanning tree of the environment while covering the work-area. the on-line stc algorithm completes an optimal covering path in time o(i>n), but requires o(i>n) memory for its implementation. the third version of stc is &ldquo;ant&rdquo;-like. in this version, too, the robot has no apriori knowledge of the environment, but it may leave pheromone-like markers during the coverage process. the ant-like stc algorithm runs in time o(i>n), and requires only o(1) memory. finally we present simulation results of the three stc algorithms, demonstrating their effectiveness in cases where the tool size is significantly smaller than the work-area characteristic dimension.
building 3-d models from unregistered range images. in this paper, we describe a new approach for building a three-dimensional model from a set of range images. the approach is able to build models of free-form surfaces obtained form arbitrary viewing directions, with no initial estimate of the relative viewing directions. the approach is based on building discrete meshes representing the surfaces observed in each of the range images, to map each of the meshes to a spherical image, and to compute the transformations between the views by matching the spherical images. these meshes are built using an interative fitting algorithm previously developed; the spherical images are built by mapping the nodes of the surface meshes to the nodes of a reference mesh on the unit sphere and by storing a measure of curvature at every node. we describe the algorithms used for building such models from range images and for matching them. we show results obtained using range images of complex objects.
sensor placement desigu for object pose determination with three light-stripe range finders. the pose of a polyhedral object can be determined with range data obtained from a set of simple light-stripe range sensors. however, localization results are highly dependent on sensor placement. this paper presents a method for designing an optimal sensor placement of three light-stripe sensors with which to determine the pose of an arbitrarily positioned object. we evaluate a sensor placement on the basis of average performance measures over the whole state space of object pose by a monte carlo method. an optimal sensor placement is then selected by another monte carlo method which searches for a maximal score function of the performance measures over the whole state of sensor placements.
an integrated mobile robot path (re)planner and localizer for personal robots. personal robotics applications require autonomous mobile robot navigation methods that are safe, robust, and inexpensive. most of the previous techniques proposed do not meet these competing goals. in this paper, we describe a method for navigation in a known indoor environment, such as a home or office, that requires only inexpensive range sensors. our framework includes a high-level planner which integrates and coordinates path planning and localization modules with the aid of a module for computing regions which are expected, with high probability, to contain the robot at any given time. the localization method is based on simple geometric properties of the environment which are computed during a preprocessing stage. the roadmap-based path planner enables one to select routes, and sub-goals along those routes, that will facilitate localization and other optimization criteria. in addition, our framework enables one to quickly plan new routes, dynamically, based on the current position as computed by intermediate localization operations. we present simulation and hardware experimental results that illustrate the practicality and potential of our approach.
a suite of tools for debugging distributed autonomous systems. this paper describes a set of tools that enables developers to log and analyze the run-time behavior of distributed control systems. a feature of the tools is that they can be applied to distributed systems. the logging tools enable developers to instrument c or c++ programs so that data indicating state changes can be logged automatically in a variety of formats. in particular, run-time data from distributed systems can be synchronized into a single relational database. tools are also provided for visualizing the logged data. analysis to verify correct program behavior is done using a new interval logic that is described in this paper. the logic enables system engineers to express temporal specifications for the autonomous control program that are then checked against the logged data. the data logging, visualization, and interval logic analysis tools are all fully implemented. results are given from a nasa distributed autonomous control system application.
on-line manipulation planning for two robot arms in a dynamic enviroment. in a constantly changing and partially unpredictable environment, robot motion planning must be on-line. the planner receives a continuous flow of information about occurring events and generates new plans, while previously planned motions are being executed. this paper describes an on-line planner for two cooperating arms whose task is to grab parts of various types on a conveyor belt and transfer them to their respective goals while avoiding collision with obstacles. parts arrive on the belt in random order, at any time. both goals and obstacles may be dynamically changed. this scenario is typical of manufacturing cells serving machine-tools, assembling products, or packaging objects. the proposed approach breaks the overall planning problem into subproblems, each involving a low-dimensional configuration or configuration-time space, and orchestrates very fast primitives solving these subproblems. the resulting planner has been implemented and extensively tested in a simulated environment, as well as with a real dual-arm system. its competitiveness has been evaluated against an oracle making (almost) the best decision at any one time; the results show that the planner compares extremely well.
a novel potential-based path planning of 3-d articulated robots with moving bases. this paper proposes a novel path planning algorithm of 3-d articulated robots with moving bases based on a generalized potential field model. the approach computes, similar to that done in electrostatics, repulsive forces and torques between charged objects. a collision-free path can be obtained by locally adjusting the robot configuration to search for minimum potential configurations using these forces and torques. the proposed approach is efficient since these potential gradients are analytically tractable. in order to speedup the computation, a sequential planning strategy is adopted. simulation results show that the proposed algorithm works well, in terms of collision avoidance and computation efficiency.
marker-augmented robot-environment interaction. there has been an increasing interest in developing computational theories of autonomous robots. however, the previous work has focused on intelligent modifications to internal computational structure of a robot, ignoring modifications to external environments. our work is the first to formalize the modification of an environment by an introduction of markers that replace the internal state. replacing internal state by addition of markers increases communication through the world. use of markers has been shown to improve the effectiveness of robots at american association of artificial intelligence robot competitions and robocup competitions. we report on the semantics of markers using their logical description and the internal state they replace. we introduce several properties of markers and marker sets like redundancy, mutual exclusivity and efficiency. we show how the stimuli of behaviours can be modified when markers are introduced to replace internal state. we also report on a semi-automatic algorithm that allows robots to place markers in their world. we show how the algorithm can be extended for obtaining a higher replacement of internal state and for handling an autonomous removal of markers. we provide several guidelines for effectively introducing markers in a robot's world.
the formula one tire changing robot (f-t.c.r.). formula one racing is one of the most fascinating sports ever, it is a perfect combination of high speed, technology, pressure and danger. one problem associated with car racing is the time differential between teams during pits stops, which substantially affects the final results. in addition, a high percentage of the accidents in formula one is due to pit stop problems. changing the tires of a car while almost in motion, after reaching dangerous pressure and temperature values, is a very risky challenge, no matter how well a team is trained. approximately 15&ndash;25 people are constantly exposed to serious dangers. the risks taken are extreme and any idea of reducing it without affecting the quality of the race should be considered. our idea is to build a fully robotized system that takes over the tire changing and refueling process. there will practically be no need for human intervention. the system will demonstrate remarkable time accuracy, precision and low risk implications, uniformity of performance across teams, the competition being relayed solely upon the pilots.
development of self-learning vision-based mobile robots for acquiring soccer robots behaviors. an input generalization problem is one of the most important ones in applying reinforcement learning to real robot tasks. to cope with this problem, we propose a self-partitioning state space algorithm which can make non-uniform quantization of the state space. to show that our algorithm has generalization capability, we apply our method to two tasks in which a soccer robot shoots a ball into a goal and prevents a ball from entering a goal. to show the validity of this method, the experimental results for computer simulation and a real robot are shown
tracking adaptive impedance robot control with visual feedback. in this paper we propose a tracking adaptive impedance controller for robots with visual feedback. it is based on a generalized impedance concept where the sensed distance is introduced as a fictitious force to the control in order to avoid obstacles in restricted motion tasks. the controller is designed to compensate for full non-linear robot dynamics. robot parameters adjustment is introduced to reduce the sensibility of the controller design to dynamic uncertainties of the robot and the manipulated load. it is proved that the vision control errors are ultimately bounded in the image coordinate system. simulations are carried out to evaluate the controller performance.
passive night vision sensor comparison for unmanned ground vehicle stereo vision navigation. one goal of the "demo iii" unmanned ground vehicle program is to enable autonomous nighttime navigation at speeds of up to 10 m.p.h. to perform obstacle detection at night with stereo vision will require night vision cameras that produce adequate image quality for the driving speeds, vehicle dynamics, obstacle sizes, and scene conditions that will be encountered.this paper analyzes the suitability of four classes of night vision cameras (3-5 mm cooled flir, 8-12 mm cooled flir, 8-12 mm uncooled flir, and image intensifiers) for night stereo vision, using criteria based on stereo matching quality, image signal to noise ratio, motion blur, and synchronization capability. we find that only cooled flirs will enable stereo vision performance that meets the goals of the demo iii program for nighttime autonomous mobility.
multi-robot collaboration for robust exploration. this paper presents a new sensing modality for multirobot exploration. the approach is based on using a pair of robots that observe each other, and act in concert to reduce odometry errors. we assume the robots can both directly sense nearby obstacles and see each other. the proposed approach improves the quality of the map by reducing the inaccuracies that occur over time from dead reckoning errors. furthermore, by exploiting the ability of the robots to see each other, we can detect opaque obstacles in the environment independently of their surface reflectance properties. two different algorithms, based on the size of the environment, are introduced, with a complexity analysis, and experimental results in simulation and with real robots.
motion planning in stereotaxic radiosurgery. stereotaxic radiosurgery is a procedure which uses a beam of radiation as an ablative surgical instrument to destroy brain tumors. the beam is produced by a linear accelerator which is moved by a jointed mechanism. radiation is concentrated by crossfiring at the tumor from multiple directions and the amount of energy deposited in normal brain tissues is reduced. because access to the tumor is obstructed along some directions by critical regions (e.g., brainstem, optic nerves) and most tumors are not shaped like spheres, planning the path of the beam is often difficult and time-consuming. this paper describes a computer-based planner developed to assist the surgeon generate a satisfactory path, given the spatial distribution of the brain tissues obtained with medical imaging. experimental results with the implemented planner are presented, including a comparison with manually generated paths. according to these results, automatic planning significantly improves energy deposition. it can also shorten the overall treatment, hence reducing the patient''s pain and allowing the radiosurgery equipment to be used for more patients. stereotaxic radiosurgery is an example of so-called "bloodless surgery". computer-based planning techniques are expected to facilitate further development of this safer, less painful, and more cost effective type of surgery.
planning paths of minimal curvature. we consider the problem of planning curvature constrained paths amidst polygonal obstacles, connecting given start and target configurations. let the critical curvature rc be the minimal curvature for which a constrained path exists. we describe an algorithm, which approximates the critical curvature and finds a corresponding path. further, we give an efficient decision procedure to determine if there exists a path satisfying a given curvature constraint r, with running time polynomial in |r-rc|/r. 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
a motion planning approach to folding: from paper craft to protein folding. in this paper, we present a framework for studying folding problems from a motion planning perspective. the version of the motion planning problem we consider is that of determining a sequence of motions to transform some configuration of a foldable object (the start) into another configuration (the goal). modeling foldable objects as tree-like multi-link objects allows us to apply recent techniques developed in the robotics motion planning community for articulated objects with many degrees of freedom (many links) to folding problems. an important feature of this approach is that it not only allows us to study foldability questions, such as, can one object be folded (or unfolded) into another object, but also provides us with another tool for investigating the dynamic folding process itself. the framework proposed here has application to traditional motion planning areas such as automation and animation, and presents a novel approach for studying protein folding pathways. preliminary experimental results with traditional paper crafts (e.g., box folding) and small proteins (approximately 60 residues) are quite encouraging.
customizing prm roadmaps at query time. in this paper, we propose a new approach for building and querying probabilistic roadmaps. in the roadmap construction stage, we build coarse roadmaps by performing only an approximate validation of the roadmap nodes and/or edges. in the query stage, the roadmap is validated and refined only in the area of interest for the query, and moreover, is customized in accordance with any specified query preferences. this approach, which postpones some of the validation checks (e.g., collision checks) to the query phase, yields more efficient solutions to many problems. an important benefit of our approach is that it gives one the ability to customize the same roadmap in accordance with multiple, variable, query preferences. for example, our approach enables one to find a path which maintains a particular clearance, or makes at most some specified number of sharp turns. our preliminary results on problems drawn from diverse application domains show that this new approach dramatically improves performance, and shows remarkable flexibility when adapting to different query requirements.
disassembly sequencing using a motion planning approach. we propose a new approach for generating disassembly sequences. our motion planning based approach treats the parts in the assembly as robots and operates in the composite configuration space of the parts'' individual configuration spaces. randomized techniques inspired by recent methods proposed for motion planning are used to sample configurations in this space. although a purely randomized approach to sampling is successful in systems with a small number of parts, typical assemblies consist of numerous parts and the corresponding composite c-spaces have high dimensionality. in such cases, a completely randomized sampling approach would be ineffective since many important configurations for the disassembly sequence will involve closely packed parts, i.e., the disassembly sequence will pass through narrow passages in the c-space. our solution to this problem is to bias the sampling by computing potential movement directions based on the geometric characteristics of configurations known to be reachable from the assembled configuration (the start). for example, we select potential directions which are perpendicular to part faces. thus, our disassembly algorithm constructs a disassembly tree which is rooted at the starting assembled configuration. our experimental results with several non-trivial puzzle-like assemblies show the potential of this approach.
maprm: a probabilistic roadmap planner with sampling on the medial axis of the free space. probabilistic roadmap planning methods have been shown to perform well in a number of practical situations, but their performance degrades when paths are required to pass through narrow passages in the free space. we propose a new method of sampling the configuration space in which randomly generated configurations, free or not, are retracted onto the medial axis of the free space. we give algorithms that perform this retraction while avoiding explicit computation of the medial axis, and we show that sampling and retracting in this manner increases the number of nodes found in small volume corridors in a way that is independent of the volume of the corridor and depends only on the characteristics of the obstacles bounding it. theoretical and experimental results are given to show that this improves performance on problems requiring traversal of narrow passages.
motion capture from demonstrator's viewpoint and its application to robot teaching. in this paper, we propose a kind of &ldquo;teaching by demonstration&rdquo; method, aiming at its application to humanoid robots at home in the future. the demonstrator's motion is captured by a pair of stereo cameras mounted on his&sol;her head, locating very close to his&sol;her eyes. by tracking the landmarks attached to the demonstrator's hand and the working environment, one can estimate not only the demonstrator's hand motion but also his&sol;her head motion, which can be used for the active vision system. experimental result shows the effectiveness of the proposed framework. &copy; 2005 wiley periodicals, inc.
automatic calibration and visual servoing for a robot navigation system. this paper attacks the problem of automatic location of a mobile robot in an indoor environment. this may be used for calibration to locate the robot accurately before it starts to navigate, or it can be used in visual servoing as feed back to the controller which is maintaining the robot on a course. in this paper, we examine the problem in a special case, where the ground plane is assumed to be horizontal and there are two locally parallel side-lines available. this assumption holds in many indoor environments, such as hallways, where the system''s success has been demonstrated. the algorithm uses geometric features such as vanishing points and line orientations. both theoretical analysis and experimental results show that this algorithm works very robustly and accurately.
revising the robust control design for rigid robot manipulators. robust controllers for robot manipulators ensure stability of the closed-loop system, even if only partial knowledge of the dynamic model of the manipulator is available. existing derivations of robust-control laws, while guaranteeing the stability result, present an undesired dependence of the robust-control term on the gains of the controller for the nominal system. this dependence forces larger robust-control terms when the nominal control gains are large. based on a structured representation of the model uncertainty, this paper proposes a derivation of the robust-control law, where these limitations are removed. experimental results on the comau smart 3s industrial robot in a 3-degree-of-freedom (dof) configuration confirm the advantages of the proposed controller.
multi-robot area patrol under frequency constraints. patrolling involves generating patrol paths for mobile robots such that every point on the paths is repeatedly covered. this paper focuses on patrolling in closed areas, where every point in the area is to be visited repeatedly by one or more robots. previous work has often examined paths that allow for repeated coverage, but ignored the frequency in which points in the area are visited. in contrast, we first present formal frequency-based optimization criteria used for evaluation of patrol algorithms. then, we present a patrol algorithm that guarantees maximal uniform frequency, i.e., each point in the target area is covered at the same optimal frequency. this solution is based on finding a circular path that visits all points in the area, while taking into account terrain directionality and velocity constraints. robots are positioned uniformly along this path in minimal time, using a second algorithm. moreover, the solution is guaranteed to be robust in the sense that uniform frequency of the patrol is achieved as long as at least one robot works properly. we then present a set of algorithms for handling events along the patrol path. the algorithms differ in the way they handle the event, as a function of the time constraints for handling them. however, all the algorithms handle events while maintaining the patrol path, and minimizing the disturbance to the system.