waashk/dblp huggingface dataset:
delayed-state information filter for cooperative decentralized tracking. this paper presents a decentralized data fusion approach to perform cooperative perception with data gathered from heterogeneous sensors, which can be static or carried by robots. particularly, a decentralized delayed-state extended information filter (ddseif) is described, where full state trajectories are considered to fuse the information. this permits to obtain an estimation equal to that obtained by a centralized system, and allows delays and latency in the communications. the sparseness of the information matrix maintains the communications overhead at a reasonable level. the method is applied to cooperative tracking and some results in disaster management scenarios are shown. in this kind of scenarios the target might move in both open field and indoor areas, so fusion of data provided by heterogeneous sensors is beneficial.
distributed sensor analysis for fault detection in tightly-coupled multi-robot team tasks. this paper presents a distributed version of our previous work, called safdetection, which is a sensor analysis-based fault detection approach that is used to monitor tightly-coupled multi-robot team tasks.while the centralized version of safdetection was shown to be successful, a shortcoming of the approach is that it does not scale well to large team sizes. the distributed safdetection approach addresses this problem by adapting and distributing the approach across team members. distributed safdetection has the same theoretic foundation as centralized safdetection, which maps selected robot sensor data to a robot state by using a clustering algorithm, and builds state transition diagrams to describe the normal behavior of the robot system. however, rather than processing multiple robots' sensor data centralized on a server, distributed safdetection performs feature selection and clustering on individual robots to build the normal behavior model of an individual robot and the entire robot team. fault detection is also accomplished in a distributed manner. we have implemented this distributed approach on a physical robot team and in simulation. this paper presents the results of these experiments, showing that distributed safdetection is an efficient approach to detect both local and interactive faults in tightly-coupled multi-robot team tasks. compared to the centralized version, this approach provides more scalability and reliability.
combining color-based invariant gradient detector with hog descriptors for robust image detection in scenes under cast shadows. in this work we present a robust detection method in outdoor scenes under cast shadows using color based invariant gradients in combination with hog local features. the method achieves good detection rates in urban scene classification and person detection outperforming traditional methods based on intensity gradient detectors which are sensible to illumination variations but not to cast shadows. the method uses color based invariant gradients that emphasize material changes and extract relevant and invariant features for detection while neglecting shadow contours. this method allows to train and detect objects and scenes independently of scene illumination, cast and self shadows. moreover, it allows to do training in one shot, that is, when the robot visits the scene for the first time.
generic slung load transportation system using small size helicopters. in this paper we present an overview of techniques and approaches used for a load transportation system based on small size unmanned helicopters. the focus is on the control approach and on the movement of the rope connecting helicopters and load. the proposed approach is based on two control loops: an outer loop to control the translation of each helicopter in compound and an inner loop to control the orientation of helicopters. the challenge here is that in both loops the dynamics of the whole system - all helicopters and load - should be accounted for. it is shown, that for designing the outer loop controller a complex model of the helicopters and load can be replaced by a simplified model based on interconnected mass points. for designing the inner loop controller, the complete dynamics of the whole system are considered. the usage of force sensors in the ropes is proposed in order to simplify the inner loop controller and to make it robust against variations of system parameters. the presented inner loop controller is independent of the number of coupled helicopters. the outer loop controller depends on the number of helicopters. the problem of oscillations in the flexible ropes due to external disturbancies (e.g. wind gusts) is discussed and a solution based on load state observer is presented. the performance of the presented system was verified in simulations and in real flight experiments with one and three helicopters transporting the load. the worldwide first demonstration of a slung load transportation using three helicopters was performed in december 2007.
regrasp planning for pivoting manipulation by a humanoid robot. a method of regrasp planning for humanoid robot manipulation is proposed. we adopt pivoting manipulation for the humanoid robot to move a bulky object without lifting in a stable and dexterous manner. in order to carry the object to a desired place, the humanoid should sometimes move through narrow areas surrounded by obstacles. we propose a roadmap multiplexing planning to allow the robot to leave the object near narrow places and to regrasp it from another position to continue carrying. we utilize visibility probabilistic roadmap (prm) method as a preprocessing to capture the critical configurations for regrasping. then a diffusion method is employed to plan the overall manipulation path including regrasping. the proposed method is verified through planning simulation including whole-body motions.
sbc for motion assist using neural oscillator. in this paper we propose a framework for synchronization based control (sbc) using neural oscillators for motion assist. a neural oscillator is used to accomplish synchronization and entrainment between periodic motions by the human and robot. the mutual joint torque between the human and robot is used as an external input signal for the neural oscillator, which generates the desired trajectory of a robot joint angle, so that the robot motion synchronizes with the external mutual joint torque. the validity and feasibility of the proposed method is examined from three points of view. the first is whether synchronization of action between human and robot can be realized. the second is whether the assist effect can be obtained, and the third is whether the proposed method has an acceptable level of usability for the user. we explored those three points of view by conducting computer simulations on a human-motion assist system and experiments with a joint torque sensing robot suit.
performance limitation analysis in visual servo systems: bounding the location error introduced by image points matching. visual servoing consists of positioning a robot end-effector based on the matching of some object features in the image. however, due to the presence of image noise, this matching can never be ensured, hence introducing an error on the final location of the robot. this paper addresses the problem of estimating the worst-case location error introduced by image points matching. in particular, we propose some strategies for computing upper bounds and lower bounds of such an error according to several possible measures for certain image noise intensity and camera-object configuration. these bounds provide an admissible region of the sought worst-case location error, and hence allow one to establish performance limitation of visual servo systems. some examples are reported to illustrate the proposed strategies and their results.
an explorative study of visual servo control with insect-inspired reichardt-model. in this paper, an insect-inspired motion detector (reichardt-model) is applied to visual servo control to ensure the stability of the system with high gain and time delay in its feedback. a reichardt-based control scheme is compared with a conventional visual servoing approach. as a consequence of the specific velocity dependence of the reichardt-model, the stability margin of the visual servo control is increased and high overall gains, thus, better performance are achievable. the response of the reichardt-model in the experiment and the control performance of velocity control approach with the reichardt-model in the closed loop are investigated. the velocity control model is tested on a 1-dof linear motor module with different feedback gain and different time delay in the loop. the results of simulation and realtime experiments demonstrate the stabilizing character of the reichardt-based approach.
dynamic modeling of mckibben pneumatic artificial muscles for antagonistic actuation. this paper presents the dynamic modeling of mckibben pneumatic artificial muscles. the air flow model of a valve orifice and the air volume model of a pneumatic muscle are incorporated into the proposed dynamic model to estimate precisely the pressure variance of a pneumatic muscle when mckibben muscles are in inflating and deflating. coefficient parameters of the proposed model are determined optimally through well-coordinated experiments. frequency response test is performed on an antagonistic structure consisting of mckibben muscles manufactured in our laboratory and a pneumatic circuit with fast pneumatic control valves. comparing with experimental results, simulations revealed that the proposed model gave good performance in estimating motions of the antagonistic actuation as well as the pressure variance of the mckibben muscles.
toward ischemia dynamics based medical diagnosis. for an arbitrary force impartment on tissue, the tissue color changes from red to white due to the decrease of arterial blood. the dynamics leading to (or recovering from) ischemia is a good index for evaluating the vitality of tissue. this paper discusses the ischemia dynamics by using a newly developed active sensing system composed of an air jet nozzle for imparting an air pulse to tissue and a high-speed camera for capturing the change of color of tissue with respect to time. through experiments, we found that the ischemia dynamics is particularly characterized by the recovery phase where the time constant changes depending upon the local physical condition of tissue. we also showed a map on color changing rate conveniently utilized for quickly understanding the location of ischemia area which is a candidate replaced by regenerated tissue.
development of insect thorax based flapping mechanism. design of a flapping mechanism for flapping wing micro air vehicles (fwmav) is presented based on a mathematical model of insect thorax. this model also includes an aerodynamic model of flapping wings. using experiments on dynamically scaled wings and numerical optimization, the mechanism is tuned for peak aerodynamic performance. the thorax model is used to understand the mechanics of the biological flapping mechanism and reveals the significance of rotational stiffness and inertia distribution in flapping wings. experiments conducted on the actual thorax based mechanism validate theoretical findings and also show significant lift generation capability.
effects of non-negligible cable mass on the static behavior of large workspace cable-driven parallel mechanisms. cable-driven robots are currently extensively studied. generally, for this type of manipulators, cables are considered to be massless and inextensible. but for large working volume applications, their mass cannot be neglected. based on a well-known model which describes the profile of a cable under the action of its own weight, the inverse and forward kinematics of minimally constrained cable-driven manipulators can be numerically computed. this paper studies the effects of taking cable mass into account by comparison to classical massless cable model. it highlights the real effects of such a model on cable lengths to reach a given position. the effects on cable tensions are also studied.
utilizing reflection properties of surfaces to improve mobile robot localization. a main difficulty that arises in the context of probabilistic localization is the design of an appropriate observation model, i.e., determining the likelihood of a sensor measurement given the pose of the robot and a map of the environment. many successful approaches to localization rely on data provided by range sensors, e.g., laser range scanners. when using such data one normally has to deal with erroneous maximum-range readings that occur due to poor-reflecting surfaces. in general, these readings cannot be distinguished from readings obtained when no obstacle is within the measurement range of the sensor. therefore, existing localization techniques treat these readings alike in the observation model. in this paper, we present a novel approach that explicitly considers the reflection properties of surfaces and thus the expectation of valid range measurements. in addition to the expected range measurement, we compute the probability of reflectance for a beam given the relative pose of the robot to the obstacle taking into account the angle of incidence of the beam. we estimate the reflection properties of surfaces using data collected with a mobile robot equipped with a laser range scanner. as we demonstrate in experiments carried out with a real robot, our technique leads to significantly improved localization results compared to a state-of-the-art observation model.
integration of impedance control and manipulability regulation for a finger-arm robot. motion control algorithms were proposed for a 9-dof finger-arm robot by using the finger manipulability obtained in a previous study. however, in the previous study, only methods for achieving unconstrained movement of the finger-arm robot were discussed. in this paper, the authors propose a novel method for having a finger-arm robot complete a constrained task by integrating impedance control with manipulability control of the finger. first, methods of applying the previous heuristic method to the passive impedance control and the active impedance control were developed; and experiments were performed to demonstrate the features. then, an impedance control combined with the steepest ascent method to modulate the manipulability of the finger was proposed. the proposed method demonstrates a strong performance even when a dynamic external force is applied to the finger. by using the proposed method, the arm actively moves along a direction to effectively maintain the moving potential of the finger during both the unconstrained and the constrained tasks.
concurrent synthesis of robot manipulators using hardware-in-the-loop simulation. this paper discusses a practical approach to the concurrent synthesis of robot manipulators, which is based on the alternative design methodology of linguistic mechatronics (lm) as well as the utilization of a modular robotic hardware-in-the-loop simulation (rhils) platform. the rhils platform involves physical joint modules and the control unit to reduce modeling complexities while taking into account various physical phenomena. the lm methodology simplifies the multi-objective constrained optimization problem into a single-objective unconstrained formulation and also brings subjective notions of design into the scope. the new approach is applied to redesigning kinematic, dynamic and control parameters of an industrial manipulator.
a minimum-order kalman filter for ambulatory real-time human body orientation tracking. in this paper, a computationally efficient orientation estimation algorithm using an inertial/magnetic sensor is presented for ambulatory real-time human motion tracking. based on a quaternion formulation, the proposed algorithm is designed to have two main steps that are connected in feedback relationship: a quaternion measurement step with a vector selector scheme and a kalman filter (kf) step. this allows us to choose only the quaternion as the state and measurement vectors in our kf design. thus, the kf has a minimum-order structure (i.e., 4th-order), which decreases the computational cost. the estimated orientation accuracy is validated experimentally by using an optical tracking system.
active localization of a robot on a lattice of rfid tags by using an entropy map. we have developed a novel way for robots to estimate their pose dynamically in an environment in which rfid tags have been arranged. we previously developed a method for localizing robots using a particle filter. testing in a room equipped with a lattice of rfid tags at 300-mm intervals revealed that the estimation fails when the robot's rfid readers are near the center of the robot's rotation because the reader could not detect enough tags by rotating movements when the robot's positions are not suitable. we have overcome this problem by developing an active localization algorithm that generates an entropy map from the rfid arrangement information, predicts the pose using a particle filter, and attracts the robot to the target using a dynamic model, the fundamental unit of which is rotation-based angular velocity. testing demonstrated that a robot using this algorithm and an entropy map can estimate its pose robustly without falling into a dead zone by moving only about 20 cm at most.
evaluation of pinching effort by a tendon-driven robot hand. in this paper, we focus on the hand posture when a human subject pinches an object, and the correlation between the results of sensory evaluation by the subject and the tendon force of the subject's fingers are investigated. surface electromyogram (surface emg) and pinching force are measured during the pinching motion of human subjects. experimental results show that subjects feel comfortable pinching a 60 [mm] cylinder. the surface emgs are lower in the vicinity of 60 [mm]. furthermore, a tendon-driven robot hand is developed as a sensing hand prototype. the surface emgs and the motor torque are compared in a pinching experiment using the tendon-driven robot hand. experimental results show that the tendon-driven robot hand is effective for quantitatively evaluating pinching effort. simulation of the pinching motion is conducted using a simple finger model. the simulation results show the importance of finger posture and the moment arm in estimating tendon force. taken together, these results demonstrate the possibility of conducting quantitative evaluation using the tendon-driven robot hand.
tuning the gains of haptic couplings to improve force feedback stability in nanorobotics. this paper deals with the problem of bilateral haptic control in nanorobotics. at this scale, a human operator cannot interact directly with objects. he needs special tools manipulated through robotic systems. therefore, force feedback devices are the only solution to provide him a sense of touch. however, the quality of the rendering strongly influences his ability to perform a given task. stability is the main requirement that the system must fulfil to be usable. as the choice of the controller and its tuning are critical issues, a general method to tune the parameters of two haptic controllers is presented. a theoretical study is carried out and the methodology is validated with an experiment composed of several phases with high dynamic phenomena. intrinsic limitations of the two controllers are also pointed out.
optimized passive dynamics improve transparency of haptic devices. for haptic devices, compensation of the robot's gravity is a frequent strategy with the aim to reduce interaction forces between robot and human in zero-impedance control. however, a closer look at the composition of these interaction forces may reveal that the net effect of uncompensated gravitational components of the robot actually reduces interaction forces during dynamic movements, because inertial and gravitational components at least partially compensate each other. this is the case in lower extremity exoskeletons, where less user force is necessary to swing the robot's leg when gravity helps. here, we go one step further by shaping optimal passive dynamics for arbitrary haptic devices. the proposed method of generalized elasticies uses conservative force fields to improve haptic transparency for certain movements types. in an example realization, these force fields are generated by elasticities spanning multiple joints. practical experiments with the lokomat lower extremity exoskeleton show the success of the proposed method in terms of reduced interaction torques and more physiological user motion compared to gravity compensation.
ground plane velocity estimation embedding rectification on a particle filter multi-target tracking. this paper presents an integrated solution for vehicle's velocity estimation and vehicle counting. the proposed restores the scene geometric properties, building a ground plane rectified image. moreover, multiple vehicles tracking is performed embedding the concept of region covariance descriptors in a particle filter framework. the results show the effectiveness of the approach here proposed in very clutter scenes.
perceptual factors for interaction modeling using haptic device. in this paper a perceptual model of the interaction with pliable surface is presented. the aim of this work is to evaluate those human factors most relevant to surface contact task in a bilateral teleoperation system characterized by a low stiffness environment. three psychophysical experiments are conducted using an high performance haptic device and a virtual environment. in the first experiment we measure the capability of the human hand in terms of absolute force detection. the second experiment takes into account the time required by the neuro-muscular-skeletal system to stabilize the hand displacement in the presence of an external force. in the third one, a task of surface detection is involved to measures the smallest penetration depth that can be used to reliably perceive the contact surface. these perceptual factors are evaluated to build a perceptual model of a surface detection task. results show the effectiveness of our model, which can be useful in applications where it is crucial to be aware of the interplay among perceptual factors.
an adaptive-scale robust estimator for motion estimation. although ransac is the most widely used robust estimator in computer vision, it has certain limitations making it ineffective in some situations, such as the motion estimation problem, in which uncertainty on the image features changes according to the capturing conditions. the greatest problem is that the threshold used by ransac to detect inliers cannot be changed adaptively; instead it is fixed by the user. an adaptive scale algorithm must therefore be applied in such cases. in this paper, we propose a new adaptive scale robust estimator that adaptively finds the best solution with the best scale to fit the inliers, without the need for predefined information. our new adaptive scale estimator matches the residual probability density from an estimate and the standard gaussian probability density function to find the best inlier scale. our algorithm is evaluated in several motion estimation experiments under varying conditions and the results are compared with several of the latest adaptive-scale robust estimators.