waashk/dblp huggingface dataset:
graph-based planning using local information for unknown outdoor environments. one of the common applications for outdoor robots is to follow a path in large scale unknown environments. this task is challenging due to the intensive memory requirements to represent the map, uncertainties in the location estimate of the robot and unknown terrain type and obstacles on the way to the goal. we develop a novel graph-based path planner that is based on only local perceptual information to plan a path in such environments. in order to extend the capabilities of the graph representation, we introduce exploration bias, which is a node attribute that can implicitly encode obstacle features at immediate surrounding of a node in the graph, the uncertainty of the planner about a node location and also the frequency of visiting a location. through simulation experiments, we demonstrate that the resulting path cost and distance that the robot traverses to reach the goal location is not significantly different from those of the previous approaches.
finding the optimal strategies for robotic patrolling with adversaries in topologically-represented environments. using autonomous mobile robots to patrol environments for detecting intruders is a topic of increasing relevance for its possible applications. a large part of strategies for mobile patrolling robots proposed so far adopt some kind of random movements. although these strategies are unpredictable for an intruder, they are not always efficient in getting the patroller a large expected utility. in this paper we propose an approach that considers a model of the adversary in a game theoretic framework to find optimally-efficient patrolling strategies. we show that our approach extends those proposed in literature and we experimentally analyze some of its features.
a framework for modeling steady turning of robotic fish. in this paper we present a novel framework for computing the steady turning motion of a robotic fish undergoing periodic body and/or tail deformation. taking the turning radius and the angular velocity as unknowns, we obtain the absolute motion trajectories of points on the "spinal column" of robotic fish by superimposing relative body/tail motions on the rigid body circular motion. the hydrodynamic reactive force and the resulting moment are then computed from the motion trajectories, using lighthill's large-amplitude elongated-body theory, in terms of the two turning parameters. by integrating the dynamics of rigid body motion and averaging out oscillations, implicit equations involving the turning parameters can be established and solved. we also discuss the plan of applying the proposed framework to the modeling of steady turning maneuvers of biomimetic robotic propelled by an ionic polymer-metal composite (ipmc) caudal fin.
onboard contextual classification of 3-d point clouds with learned high-order markov random fields. contextual reasoning through graphical models such as markov random fields often show superior performance against local classifiers in many domains. unfortunately, this performance increase is often at the cost of time consuming, memory intensive learning and slow inference at testing time. structured prediction for 3-d point cloud classification is one example of such an application. in this paper we present two contributions. first we show how efficient learning of a random field with higher-order cliques can be achieved using subgradient optimization. second, we present a context approximation using random fields with high-order cliques designed to make this model usable online, onboard a mobile vehicle for environment modeling. we obtained results with the mobile vehicle on a variety of terrains, at 1/3 hz for a map 25 × 50 meters and a vehicle speed of 1-2 m/s.
force estimation in a piezoelectric cantilever using the inverse-dynamics-based uio technique. this paper presents the estimation of the force applied by a piezocantilever dedicated to micromanipulation/microassembly. relative to previous works, the presented method avoids the reliance on the force dynamics on the characteristics of the micro-objects. furthermore, the estimation is a closed-loop kind technique so that convergency can be ensured efficiently. to perform these, we consider the force at the tip of a piezocantilever as an unknown input and we use an unknown input observation technique. we especially use the inverse-dynamics-based uio technique because it is well suited for a piezocantilever model. the experiments show that the performances of the observer are convenient for micromanipulation/microassembly tasks.
a geometric approach for the design of singularity-free parallel robots. while a number of researchers have published results in the area of parallel robot singularity determination and the a posteriori elimination of these singularities, far less work has been published in the area of singularity free workspace design. several researchers have committed substantial funds to design hardware prototypes that have proven worthless because of unavoidable singularities. this trend, if carried over to industrial applications, could prove especially detrimental to the future of applied parallel robotics. a comprehensive and straightforward design strategy that guarantees a singularity free workspace is presented in this paper. the design problem is mathematically modeled, and relaxations are suggested for finding solutions. the translational 3-upu parallel robot is studied to verify the efficacy of the design approach.
passive event-based extrapolation for lossy haptic data compression in bilateral presence systems. a new lossy compression method is proposed for haptic (force, velocity) data as exchanged in bilateral telepresence systems. the method is based on the passive extrapolative compression strategy proposed in [1]. the innovation is that the extrapolations do not have a stiff horizon, but are triggered by considerable changes (events) in the target environment. this enables longer average extrapolation horizons and thus, higher compression. experiments are conducted using two dlr light weight robots. the results indicate that the method outperforms older implementations.
observations and models for needle-tissue interactions. the asymmetry of a bevel-tip needle results in the needle naturally bending when it is inserted into soft tissue. in this study we present a mechanics-based model that calculates the deflection of the needle embedded in an elastic medium. microscopic observations for several needle-gel interactions were used to characterize the interactions at the bevel tip and along the needle shaft. the model design was guided by microscopic observations of several needle-gel interactions. the energy-based model formulation incorporates tissue-specific parameters such as rupture toughness, nonlinear material elasticity, and interaction stiffness, and needle geometric and material properties. simulation results follow similar trends (deflection and radius of curvature) to those observed in macroscopic experimental studies of a robot-driven needle interacting with different kinds of gels. these results contribute to a mechanics-based model of robotic needle steering, extending previous work on kinematic models.
a simple nonlinear pid control for finite-time regulation of robot manipulators. a simple nonlinear proportional-integral-derivative (pid) controller is proposed to solve the finite-time regulation of uncertain robot manipulators. the semiglobal finite-time stabilization is shown by using lyapunov theory and finite-time stability theory. the proposed control algorithm does not involve the modeling information in the control law formulation and the control gains can be explicitly determined based on some well-known bounds extracted from the robot dynamics, and thus permits easy implementation. simulations preformed on a two degrees-of-freedom (dof) manipulator demonstrate the expected properties of the proposed approach.
mechanics of bending, torsion, and variable precurvature in multi-tube active cannulas. active cannulas are a relatively new continuum robot subclass characterized by their use of preshaped tubes that transmit bending moments as they slide within one another and are axially rotated. previous (experimentally vetted) mechanics-based models of active cannula shape assume piece-wise constant precurvature of component tubes, and neglect torsion in curved sections of the device. recently a general, coordinate-free, energy-based framework for active cannula shape has been formulated that relaxes these requirements and includes all prior models as special cases. however, only the 2-tube, constant-precurvature case has thus far been explored in detail using the framework. in this paper we consider the general case of an arbitrary number of component tubes and precurvatures that vary with arc length, deriving a set of differential equations that capture both bending and torsional effects continuously along the active cannula backbone. we then show how to solve these differential equations numerically to describe active cannula shape.
autonomous robot cameraman - observation pose optimization for a mobile service robot in indoor living space. this paper presents a model based system for a mobile robot to find an optimal pose for the observation of a person in indoor living environments. we define the observation pose as a combination of the camera position and view direction as well as further parameters like the aperture angle. the optimal placement of a camera is not trivial because of the high dynamic range of the scenes near windows or other bright light sources, which often results in poor image quality due to glare or hard shadows. the proposed method tries to minimize these negative effects by determining an optimal camera pose based on two major models: a spatial free space model and a representation of the lighting. in particular, a task-dependent optimization takes into account the intended purpose of the camera images, e.g. different inputs are needed for video communication with other people or for an image-processing based passive observation of the person's activities. to prove the validity of our approach, we present first experimental results comparing the chosen observation pose and resulting image with and without respect to lighting in different observation tasks.
a force control based cell injection approach in a bio-robotics system. robotic cell injection is a technique that employs automated device to insert substances into a single living cell with a fine needle. most existing microinjection methods are based on position control without explicit regulation of the injection force. the injection force, if not controlled properly, may destroy the cell and lead to death of the cells. in this paper, we propose a force control based cell injection technology to explicitly regulate the injection force to follow the desired force trajectory during the injection. any desired force trajectory that is twice continuously differentiable can be realized by the proposed approach. the convergence of the force tracking algorithm is provably guaranteed. experiments performed on a laboratorial robotic cell injection system demonstrate the effectiveness of the proposed approach.
potential field guide for humanoid multicontacts acyclic motion planning. we present a motion planning algorithm that computes rough trajectories used by a contact-points planner as a guide to grow its search graph. we adapt collision-free motion planning algorithms to plan a path within the guide space, a submanifold of the configuration space included in the free space in which the configurations are subject to static stability constraint. we first discuss the definition of the guide space. then we detail the different techniques and ideas involved: relevant c-space sampling for humanoid robot, task-driven projection process, static stability test based on polyhedral convex cones theory's double description method. we finally present results from our implementation of the algorithm.
trajectory planning and control of an underactuated dynamically stable single spherical wheeled mobile robot. the ballbot is a dynamically stable mobile robot that moves on a single spherical wheel and is capable of omnidirectional movement. the ballbot is an underactuated system with nonholonomic dynamic constraints. the authors propose an offline trajectory planning algorithm that provides a class of parametric trajectories to the unactuated joint in order to reach desired static configuration of the system with regard to the dynamic constraint. the parameters of the trajectories are obtained using optimization techniques. a feedback controller is proposed that ensures accurate trajectory tracking. the trajectory planning algorithm and tracking controller are validated experimentally. the authors also extend the offline trajectory planning algorithm to a generalized case of motion between non-static configurations.
motion control of multi-limbed robots for asteroid exploration missions. the interest on the study of asteroids has increased due to the recent missions that have been sent to explore such low gravity bodies. due to its complexity, little attention has been given to close surface analysis by a mobile robotic system. in this paper, the authors present a study on the locomotion of limbed robotic systems based on the detection of friction force in an emulated microgravity environment. the issues rose by the microgravity environment and its effect on the dynamics of such robotic system during motion are addressed, and an algorithm to generate compliant motion gaits is presented. experimental results show that the control system is capable of maintaining balanced contacts during motions.
robot kinematics based model to predict compensatory motion of transradial prosthesis while performing bilateral tasks. in order to perform activities of daily living (adl), a person with an amputation(s) must use a greater than normal range of movement from other anatomical body joints to compensate for the loss of movement caused by the amputation, this is called compensatory motion. by studying the compensatory motion of prosthetic users the mechanics of how they adapt to the loss of range of motion in a given limb for can be analyzed for select tasks. the purpose of this study is to create a robotic based kinematic model that can simulate the compensatory motion of a given task using given subject data. this paper reviews the use of the model to simulate compensatory motion of a transradial amputee performing two bilateral tasks: turning a steering wheel, and lifting a box. the simulation operates by changing a set of prosthetic configurations that are represented by parameters that consist of the joint degrees of freedom (dof) provided by each prosthesis in the set. the task information is inputted into the model by defining a trajectory which the hand or prosthesis must follow to perform the task. the inclusion of the ability to model bilateral tasks is accomplished by giving control of the proximal joints to the prosthetic side. analysis of tasks is completed by running the simulation with prosthetic and anatomical constraints attached to the left arm of the model, the right arm maintains an anatomical configuration. by running the model through this simulation the compensatory motions can be determined. results obtained from the model can be used to select the best prosthesis for a given user, design prostheses that are more effective at selected tasks, further analyze previous studies, or to determine areas of interest for further human study.
visual topological slam and global localization. visual localization and mapping for mobile robots has been achieved with a large variety of methods. among them, topological navigation using vision has the advantage of offering a scalable representation, and of relying on a common and affordable sensor. in previous work, we developed such an incremental and real-time topological mapping and localization solution, without using any metrical information, and by relying on a bayesian visual loop-closure detection algorithm. in this paper, we propose an extension of this work by integrating metrical information from robot odometry in the topological map, so as to obtain a globally consistent environment model. also, we demonstrate the performance of our system on the global localization task, where the robot has to determine its position in a map acquired beforehand.
a genericity condition for general serial manipulators. generic manipulators possess the desireable properties that their set of singulartities is a smooth manifold, and that the drop of rank of the manipulator jacobian is bounded. a sufficient condition for genericity is the transverse-regularity of its jacobian mapping in any configuration. in this paper a necessary and sufficient condition for transverse-regularity is presented. the condition is based on the manipulator's joint screws and their screw products. it is also shown that a manipulator is non-generic if it can attain a pose where the rank of the manipulator's screw system together with the screw products is not the maximal rank of the jacobian.
gaussian process modeling of large scale terrain. this paper addresses the problem of large scale terrain modeling for a mobile robot. building a model of large scale terrain data that can adequately handle uncertainty and incompleteness in a statistically sound way is a very challenging problem. this work proposes the use of gaussian processes as models of large scale terrain. the proposed model naturally provides a multi-resolution 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 unknown areas) elevation information across the field. the estimates obtained are the best linear unbiased estimates for the data under consideration. a single non-stationary (neural network) gaussian process is shown to be powerful enough to model large and complex terrain, handling issues relating to discontinuous data effectively. a local approximation methodology based on kd-trees is also proposed in order to ensure local smoothness and yet preserve the characteristic features of rich and complex terrain data. the use of the local approximation technique based on kd-trees further addresses concerns relating to the scalability of the proposed approach for large data sets. experiments performed on sparse gps based survey data as well as dense laser scanner data taken at different mine-sites are reported in support of these claims.
utilizing object-object and object-scene context when planning to find things. in this paper, our goal is to search for a novel object, where we have a prior map of the environment and knowledge of some of the objects in it, but no information about the location of the specific novel object. we develop a probabilistic model over possible object locations that utilizes object-object and object-scene context. this model can be queried for any of over 25,000 naturally occurring objects in the world and is trained from labeled data acquired from the captions of photos on the flickr website. we show that these simple models based on object co-occurrences perform surprisingly well at localizing arbitrary objects in an office setting. in addition, we show how to compute paths that minimize the expected distance to the query object and show that this approach performs better than a greedy approach. finally, we give preliminary results for grounding our approach in object classifiers.
modelling and control of obstacle-aided snake robot locomotion based on jam resolution. a snake robot can traverse cluttered and irregular environments by using irregularities around its body as pushpoints to aid the propulsion. this characteristic feature of snake locomotion, denoted obstacle-aided locomotion, has received limited focus in previous literature. this paper presents a model of this phenomenon and a control strategy employing measured contact forces to maintain propulsion while simultaneously preventing the snake robot from being jammed between obstacles in its path. the simulation results validate the contact modelling approach and the effectiveness of the proposed control strategy.
physical parameter identification of rheological object based on measurement of deformation and force. there are many kinds of deformable objects in our living life. some of them exhibit rheological behaviors when they are subject to external force, such as human tissues, human organs, and food. if we want to simulate or control such behaviors, we have to know the physical parameters of the object in advance. in this paper, we propose an approach to identify these parameters based on 2d finite element (fe) simulation and measurement of deformation and force. at first, 2d fe model used to simulate rheological deformation was described. then, identification method was presented according to the analysis of simulation results. identification results for simulation were also given. finally, this method was applied to a object made of clay. deformation and force were measured by camera and tactile sensor respectively. the identification results show the validity and effectiveness of this method.
semi-closed microchip for probe manipulation and the target cell harvesting. in this paper, we propose a semi-closed microchip which can realize the probe type manipulation in the microchip with the internal environment sealed off from the external environment. long-term experiments can be conducted for in-situ culture and analysis of cells by the semi-closed microchip. the semi-closed microchip has a bath in the middle of microchannel to allow the insertion of micropipettes into the microchip. the bath is sealed off by thin oil film to prevent the evaporation of the solution in the bath. the seal by the oil film can maintain even if micropipettes are inserted into the bath and pulled out from the bath because the oil film can fill the hole by its surface tension. the seal by the oil film was evaluated by measuring the weight of the bath after 12/24 hours. to use the semi-closed microchip for cell culture and cell analysis, the exchange of the solution in the bath was demonstrated. it was also demonstrated that the cell fixation with the thermo sensitive gel in the proposed semi-closed microchip by fabricating the ito electrodes as heaters in the bath. cell culture and the target cell harvesting were conducted by the semi-closed microchip. the proposed semi-closed microchip can be used for cell culture, cell analysis and cell harvesting under a microscope as the biological applications for single cell analysis.
playing with toys: towards autonomous robot manipulation for therapeutic play. when young children play, they often manipulate toys that have been specifically designed to accommodate and stimulate their perceptual-motor skills. robotic playmates capable of physically manipulating toys have the potential to engage children in therapeutic play and augment the beneficial interactions provided by overtaxed care givers and costly therapists. to date, assistive robots for children have almost exclusively focused on social interactions and teleoperative control. within this paper we present progress towards the creation of robots that can engage children in manipulative play. first, we present results from a survey of popular toys for children under the age of 2 which indicates that these toys share simplified appearance properties and are designed to support a relatively small set of coarse manipulation behaviors. we then present a robotic control system that autonomously manipulates several toys by taking advantage of this consistent structure. finally, we show results from an integrated robotic system that imitates visually observed toy playing activities and is suggestive of opportunities for robots that play with toys.