waashk/dblp huggingface dataset:
active matching for visual tracking. in the feature matching tasks which form an integral part of visual tracking or slam (simultaneous localisation and mapping), there are invariably priors available on the absolute and/or relative image locations of features of interest. usually, these priors are used post-hoc in the process of resolving feature matches and obtaining final scene estimates, via 'first get candidate matches, then resolve' consensus algorithms such as ransac or jcbb. in this paper we show that the dramatically different approach of using priors dynamically to guide a feature by feature matching search can achieve global matching with far fewer image processing operations and lower overall computational cost. essentially, we put image processing into the loop of the search for global consensus. in particular, our approach is able to cope with significant image ambiguity thanks to a dynamic mixture of gaussians treatment. in our fully bayesian algorithm denoted active matching, the choice of the most efficient search action at each step is guided intuitively and rigorously by expected shannon information gain. we demonstrate the algorithm in feature matching as part of a sequential slam system for 3d camera tracking with a range of settings, and give a detailed analysis of performance which leads to performance-enhancing approximations to the full algorithm.
applications of energy based control methods for the inverted pendulum on a cart. this contribution deals with the application of energy based control methods for the inverted pendulum on a cart model. we will present a swing up controller as well as a nonlinear balancing controller with the focus on the implementation on a laboratory model. therefore we recapitulate well-known control concepts from the literature which will be adapted such that they work on a concrete experiment with all the undesirable effects like friction and quantisation.
recent progress and development of the humanoid robot hansaram. this paper presents an overview of the recent progress and development of the humanoid robot, hansaram series, which have been developed in the robot intelligence technology (rit) laboratory, kaist since 2000. the hansaram series have been designed and developed as a small-sized robot for researching walking gate generation, navigation, task planning and hurocup of fira. in particular, the performance of the 7th and 8th versions have been remarkably improved in the aspect of walking pattern generation and task planning. this paper describes the overall design and architecture of recently developed two versions of hansaram along with a developed vision simulator tool and the real-time walking gate generation scheme, modifiable walking pattern generator.
adaptive supervision of moving objects for mobile robotics applications. one of the main tasks of mobile robotics is vision. lighting independence, adaptivity and automated learning are still the main issues when it comes to applications. in this article, we present an image understanding system and its methods targeting automatic, lighting-independent and reliable color-based object recognition under real time conditions. its application test bed is global vision robot soccer (i.e. fira mirosot und robocup small size leagues) but it has many other applications in color-based supervision of moving objects. under typical conditions, it learns the objects of recognition automatically, has zero setup time and tolerates environmental changes during run-time.
workspace analysis of fully restrained cable-driven manipulators. for cable-driven parallel manipulators (cdpms), employing redundant driving cables is necessary to obtain the full manipulation of the moving platform because of the unilateral driving property of the cables. unlike rigid-link manipulators, the workspace of cdpms is always determined and characterized by positive tension status of driving cables. in addition, it has been realized that the tension factor (tf) reflecting the relative tension distribution among the driving cables is an appropriate measure to evaluate the quality of tension restraint for cdpms. however, since redundant cables are employed to drive the moving platform, the tf values are not unique for a particular moving platform pose. therefore, how to determine the workspace and obtain the optimal tf value so as to generate a workspace with optimized performance become the major subjects of this paper. it is shown that the workspace can be generally formed from tension conditions verified by a recursive dimension-reduction approach and that the optimal tf value at every pose can be efficiently determined through a linear optimization approach, although it is essentially a nonlinear optimization problem. computational examples are provided to demonstrate the effectiveness of the proposed algorithms.
automatic abstraction in reinforcement learning using data mining techniques. in this paper, we used data mining techniques for the automatic discovering of useful temporal abstraction in reinforcement learning. this idea was motivated by the ability of data mining algorithms in automatic discovering of structures and patterns, when applied to large data sets. the state transitions and action trajectories of the learning agent are stored as the data sets for data mining techniques. the proposed state clustering algorithms partition the state space to different regions. policies for reaching different parts of the space are separately learned and added to the model in a form of options (macro-actions). the main idea of the proposed action sequence mining is to search for patterns that occur frequently within an agent's accumulated experience. the mined action sequences are also added to the model in a form of options. our experiments with different data sets indicate a significant speedup of the q-learning algorithm using the options discovered by the state clustering and action sequence mining algorithms.
development of complex robotic systems using the behavior-based control architecture ib2c. this paper presents a development methodology for complex robotic systems using the behavior-based control architecture ib2c (integrated behavior-based control). it is shown how architectural principles support several behavior-based mechanisms, e.g. coordination mechanisms, behavior interaction, and hierarchical abstraction. furthermore, design guidelines and structural patterns are presented which support the design and implementation process. the provided analysis tools and visualization techniques help to manage the complexity of large behavior-based networks. finally, application examples are presented and a step by step description of constructing a behavior-based control structure for the outdoor robot ravon is given.
calibration for mobile robots with an invariant jacobian. the kinematics of some mobile robots is described through a strictly invariant jacobian matrix [j]. this is the case for robots with three degrees of freedom and suitable omnidirectional wheels, and that for robots with conventional wheels and differential kinematics. this article proposes a calibration technique for the matrix [j] of such robots. it is based on four accurate configuration measurements associated with particular nominal motions where the generalized velocities maintain a constant proportional relationship. as a consequence, the nominal trajectories are arcs of circumference and may be part of the actual trajectories of the robot. an application example is presented.
optimized obstacle avoidance trajectory generation for a reconfigurable staircase climbing wheelchair. this paper describes the mechanical devices, the control scheme and the trajectory generation of which a new wheelchair prototype capable of climbing staircases is formed. the key feature of the mechanical design is the use of two decoupled mechanisms in each axle, one to negotiate steps, and the other to position the axle with regard to the chair in order to accommodate the overall slope. this design simplifies the control task substantially. kinematic models are necessary to describe the behavior of the system and to control the actuated degrees of freedom of the wheelchair in order to ensure the passenger's comfort. the choice of a good control scheme based on a local and a global trajectory planner simplifies control, decreases power consumption, reduces the time invested in traversing the obstacles and maintains passenger comfort throughout all movements. the paper presented here is the natural continuation of a previous work presented in [r. morales, a. gonzalez, v. feliu, p. pintado, environment adaptation of a new staircase climbing wheelchair, autonomous robots 23 (2007) 275-292]. after studying the time outs in the staircase climbing/descent process due to configuration changes, we started to increase the capabilities of the trajectory planner in order to reduce the time invested in traversing obstacles. the optimization algorithm is only used in the period of time in which configuration changes are being produced. more specifically, we have used the special properties of the mechanical configuration, the kinematic model and the trajectory planner to develop an improvement in the trajectory planning based on complex notation. the new optimized algorithm solves a nonlinear problem in order to discover an auxiliar center of mass route which is free of obstacles, through the work environment of the wheelchair prototype. additional properties of the new optimization algorithm are: (a) the resulting analytical expressions are closed (iterative calculation is not necessary); (b) it is easy to implement in the real prototype and (c) it can be executed in real time. experimental results are reported which show the behavior of the prototype as it climbs a staircase both when using the original trajectory planner and when using the new obstacle avoidance optimization algorithm explained in this paper. the results obtained illustrate a high percentage of time reduction and the maintenance of comfort levels. however, the control prototype becomes more complicated, the power consumption is increased and the comfort level is slightly lower.
multi-robot visual slam using a rao-blackwellized particle filter. this paper describes an approach to solve the simultaneous localization and mapping (slam) problem with a team of cooperative autonomous vehicles. we consider that each robot is equipped with a stereo camera and is able to observe visual landmarks in the environment. the slam approach presented here is feature-based, thus the map is represented by a set of 3d landmarks each one defined by a global position in space and a visual descriptor. the robots move independently along different trajectories and make relative measurements to landmarks in the environment in order to jointly build a common map using a rao-blackwellized particle filter. we show results obtained in a simulated environment that validate the slam approach. the process of observing a visual landmark is simulated in the following way: first, the relative measurement obtained by the robot is corrupted with gaussian noise, using a noise model for a standard stereo camera. second, the visual description of the landmark is altered by noise, simulating the changes in the descriptor which may occur when the robot observes the same landmark under different scales and viewpoints. in addition, the noise in the odometry of the robots also takes values obtained from real robots. we propose an approach to manage data associations in the context of visual features. different experiments have been performed, with variations in the path followed by the robots and the parameters in the particle filter. finally, the results obtained in simulation demonstrate that the approach is suitable for small robot teams.
a realistic benchmark for visual indoor place recognition. an important competence for a mobile robot system is the ability to localize and perform context interpretation. this is required to perform basic navigation and to facilitate local specific services. recent advances in vision have made this modality a viable alternative to the traditional range sensors, and visual place recognition algorithms emerged as a useful and widely applied tool for obtaining information about robot's position. several place recognition methods have been proposed using vision alone or combined with sonar and/or laser. this research calls for standard benchmark datasets for development, evaluation and comparison of solutions. to this end, this paper presents two carefully designed and annotated image databases augmented with an experimental procedure and extensive baseline evaluation. the databases were gathered in an uncontrolled indoor office environment using two mobile robots and a standard camera. the acquisition spanned across a time range of several months and different illumination and weather conditions. thus, the databases are very well suited for evaluating the robustness of algorithms with respect to a broad range of variations, often occurring in real-world settings. we thoroughly assessed the databases with a purely appearance-based place recognition method based on support vector machines and two types of rich visual features (global and local).
classification and characterization of inverse kinematics solutions for anthropomorphic manipulators. topological properties of the kinematics map are exploited to develop a novel method for redundancy parameterization and extremely fast inverse kinematics solutions for 7-dof anthropomorphic manipulators and animation characters. the method consists of generating joint angles vectors (configurations) and determining their associated hand position/orientation (pose) via the known forward kinematics. the generated data are classified into various inverse kinematics solutions manifolds. these manifolds are subsequently segmented so that the redundancy can be parameterized and the solutions can be represented by simple equations whose parameters are stored for rapid online computation. during the online phase, given the desired hand pose, the appropriate stored parameters are retrieved and various inverse kinematics solutions are computed. the online time to provide various solutions is of the order of several microseconds, which allow real-time inverse kinematics evaluations for fast moving animation characters or manipulators.
vision guided manipulation for planetary robotics - position control. manipulation systems for planetary exploration operate under severe restrictions. they need to integrate vision and manipulation to achieve the reliability, safety, and predictability required of expensive systems operating on remote planets. they also must operate on very modest hardware that is shared with many other systems, and must operate without human intervention. typically such systems employ calibrated stereo cameras and calibrated manipulators to achieve precision of the order of one centimeter with respect to instrument placement activities. this paper presents three complementary approaches to vision guided manipulation designed to robustly achieve high precision in manipulation. these approaches are described and compared, both in simulation and on hardware. in situ estimation and adaptation of the manipulator and/or camera models in these methods account for changes in the system configuration, thus ensuring consistent precision for the life of the mission. all the three methods provide several-fold increases in accuracy of manipulator positioning over the standard flight approach.
an adaptive fuzzy sliding mode controller for remotely operated underwater vehicles. sliding mode control is a very attractive control scheme because of its robustness against both structured and unstructured uncertainties as well as external disturbances. in this way, it has been widely employed for the dynamic positioning of remotely operated underwater vehicles. nevertheless, in such situations the discontinuities in the control law must be smoothed out to avoid the undesirable chattering effects. the adoption of properly designed boundary layers has proven effective in completely eliminating chattering, however, leading to an inferior tracking performance. this work describes the development of a dynamic positioning system for remotely operated underwater vehicles. the adopted approach is primarily based on the sliding mode control strategy and enhanced by an adaptive fuzzy algorithm for uncertainty/disturbance compensation. using the lyapunov stability theory and barbalat's lemma, the boundedness and convergence properties of the closed-loop signals are analytically proven. the performance of the proposed control scheme is also evaluated by means of numerical simulations.
a solution to the path planning problem using angle preprocessing. the path planning problem is a common topic for robotics and computational geometry. many important results have been found to this classic problem, some of them based on plane or space tessellation. the new approach we propose in this paper computes a partition of the plane called the polar diagram, using angle properties as criterion of construction. compared to some other plane partitions as voronoi diagrams, this tessellation can be computed much more efficiently for different geometric objects. the polar diagram used as preprocessing can be applied to many geometric problems where the solution can be given by angle processing, such as visibility or path planning problems.
stereo vision specific models for particle filter-based slam. this work addresses the slam problem for stereo vision systems under the unified formulation of particle filter methods. in contrast to most existing approaches to visual slam, the present method does not rely on restrictive smooth camera motion models, but on computing incremental 6-dof pose differences from the image flow through a probabilistic visual odometry method. moreover, our observation model, which considers both the 3d positions and the sift descriptors of the landmarks, avoids explicit data association between the observations and the map by marginalizing the observation likelihood over all the possible associations. we have experimentally validated our research with two experiments in indoor scenarios.
geographical information systems for map based navigation in urban environments. in order to solve most of the existing mobile robotics applications, the robot needs some information about its spatial environment encoded in what it has been commonly called a map. the knowledge contained in such a map, whatever approach is used to obtain it, will mainly be used by the robot to gain the ability to navigate in a given environment. we are describing in this paper, a method that allows a robot or team of robots to navigate in large urban areas for which an existing map in a standard human understandable fashion is available. as detailed maps of most urban areas already exist, it will be assumed that a map of the zone where the robot is supposed to work is given, which has not been constructed using the robot's own sensors. we propose in this paper, the use of an existing geographical information system based map of an urban zone so that a robot or a team of robots can connect to this map and use it for navigation purposes. details of the implemented system architecture as well as a position tracking experiment in a real outdoor environment, a university campus, are provided.
modeling floor-cleaning coverage performances of some domestic mobile robots in a reduced scenario. in this paper, floor-cleaning coverage performances of some domestic mobile robots are measured, analyzed and modeled. results obtained in a reduced scenario show that floor-cleaning coverage is complete in all cases if the path-planning exploration algorithm has some random dependence. additionally, the evolution of the area cleaned by the mobile robot expressed in a distance domain has an exponential shape that can be modeled with a single exponential where the amplitude defines the maximum cleaning-coverage achieved and the time-constant defines the dynamic evolution of the coverage. both parameters are robot dependent and can be estimated if the area of the room is known and then floor-cleaning coverage can be predicted and over-cleaning minimized.
hardness of edge-modification problems. for a graph property p consider the following computational problem. given an input graph g, what is the minimum number of edge modifications (additions and/or deletions) that one has to apply to g in order to turn it into a graph that satisfies p? namely, what is the edit distance @d(g,p) of a graph g from satisfying p? clearly, the computational complexity of such a problem strongly depends on p. for over 30 years this family of computational problems has been studied in several contexts and various algorithms, as well as hardness results, were obtained for specific graph properties. alon, shapira and sudakov studied in [n. alon, a. shapira, b. sudakov, additive approximation for edge-deletion problems, in: proc. of the 46th ieee focs, 2005, 419-428. also: annals of mathematics (in press)] the approximability of the computational problem for the family of monotone graph properties, namely properties that are closed under removal of edges and vertices. they describe an efficient algorithm that achieves an o(n^2) additive approximation to @d(g,p) for any monotone property p, where g is an n-vertex input graph, and show that the problem of achieving an o(n^2^-^@e) additive approximation is np-hard for most monotone properties. the methods in [n. alon, a. shapira, b. sudakov, additive approximation for edge-deletion problems, in: proc. of the 46th ieee focs, 2005, 419-428. also: annals of mathematics (in press)] also provide a polynomial time approximation algorithm which computes @d(g,p)+/-o(n^2) for the broader family of hereditary graph properties (which are closed under removal of vertices). in this work we introduce two approaches for showing that improving upon the additive approximation achieved by this algorithm is np-hard for several sub-families of hereditary properties. in addition, we state a conjecture on the hardness of computing the edit distance from being induced h-free for any forbidden graph h.
a direct proof of the confluence of combinatory strong reduction. i give a proof of the confluence of combinatory strong reduction that does not use the one of @l-calculus. i also give simple and direct proofs of a standardization theorem for this reduction and the strong normalization of simply typed terms.
rank/select on dynamic compressed sequences and applications. operations rank and select over a sequence of symbols have many applications to the design of succinct and compressed data structures managing text collections, structured text, binary relations, trees, graphs, and so on. we are interested in the case where the collections can be updated via insertions and deletions of symbols. two current solutions stand out as the best in the tradeoff of space versus time (when considering all the operations). one solution, by makinen and navarro, achieves compressed space (i.e., nh"0+o(nlog@s) bits) and o(lognlog@s) worst-case time for all the operations, where n is the sequence length, @s is the alphabet size, and h"0 is the zero-order entropy of the sequence. the other solution, by lee and park, achieves o(logn(1+log@sloglogn)) amortized time and uncompressed space, i.e. nlog"2@s+o(n)+o(nlog@s) bits. in this paper we show that the best of both worlds can be achieved. we combine the solutions to obtain nh"0+o(nlog@s) bits of space and o(logn(1+log@sloglogn)) worst-case time for all the operations. apart from the best current solution to the problem, we obtain several byproducts of independent interest applicable to partial sums, text indexes, suffix arrays, the burrows-wheeler transform, and others.