waashk/dblp huggingface dataset:
dynamic compensating controller for passive haptic manipulators in teleoperation. haptic devices allow a human user to physically interact with the virtual or simulated world by generating real forces to represent interactions in the virtual world. by definition, haptic devices exist in the set of robotic systems whose workspaces must overlap with the workspace of the human. for that reason, safety of the human becomes a central concern when developing both the physical hardware and the control systems for new and novel interfaces. passive haptic devices, ones that display forces to the user by using passive actuators such as brakes, clutches of continuously variable transmissions, address the concerns of stability and safety by using actuators that physically guarantee a bounded output and the safety of the human user. however, a device using passive actuators can only produce a subset of the forces generated by a similar device built around active actuators. the work presented here will explore the use of a passive haptic device specifically with respect to teleoperation and will present a new algorithm for determining feedback that improves the transparency, a dynamic compensating controller. this controller will be implemented in labview on passive hardware and will be compared to two simpler control schemes in two typical teleoperation tasks, shape identification and point to point motion around an obstacle. the results will show that the passive device provides feedback that allows the user to recognize large surface features. furthermore, results will show that the dynamic compensating controller proves especially useful in dynamic situations represented by the motion task.
design and control of underactuated tendon-driven mechanisms. many robotic hands or prosthetic hands have been developed in the last several decades, and many use tendon-driven mechanisms for their transmissions. robotic hands are now built with underactuated mechanisms, which have fewer actuators than degrees of freedom, to reduce mechanical complexity or to realize a biomimetic motion such as flexion of an index finger. the design is heuristic and it is useful to develop design methods for the underactuated mechanisms. this paper classifies mechanisms driven by tendons into three classes, and proposes a design method for them. the two classes are related to underactuated tendon-driven mechanisms, and these have been used without distinction so far. an index finger robot, which has four active tendons and two passive tendons, is developed and controlled with the proposed method.
relative bearing estimation from commodity radios. relative bearing between robots is important in applications like pursuit-evasion [11] and slam [7]. this is also true in sensor networks, where the bearing of one sensor node relative to another has been used for localization [5], [18], [20] and topology control [14], [21], [6]. most systems use dedicated sensors like an ir array or a camera to obtain relative bearing. we study the use of radio signal strength (rss) in commodity radios for obtaining relative bearing. we show that by using the robot's mobility, commodity radios can be used to obtain coarse relative bearing. this measurement can be used for a suite of applications that do not require very precise bearing measurement. we analyze signal strength variations in simulation and experiment and also show an algorithm that uses this coarse bearing computation in a practical setting.
wearable motion capture suit with full-body tactile sensors. this paper presents a system for capturing human movement and tactile data and methods for analyzing this data. we cannot fully capture the essence of motion without tactile information, and sometimes the lack of such information causes critical problems. to achieve a better understanding of motion behavior, we developed a wearable motion capture suit with full-body tactile sensors. we also developed a motion sensor which can estimate its orientation with its inner cpu. we also built a tactile sensor module which can fit many kinds of body shapes. with this system, we can measure a user's movement and tactile information simultaneously. by integrating tactile data with motion data, we can achieve many kinds of meaningful insights. we demonstrate the effectiveness of this system with experiments. we captured two motions: stretching after sitting on a chair and laying down on a bed. by recognizing the contact point from the tactile data and fitting it into the environment, we were able to estimate the motion trajectories.
efficient off-road localization using visually corrected odometry. we describe an efficient, low-cost, low-overhead system for robot localization in complex visual environments. our system augments wheel odometry with visual orientation tracking to yield localization accuracy comparable with "pure" visual odometry at a fraction of the cost. such a system is well-suited to consumer-level robots, small form-factor robots, extraterrestrial rovers, and other platforms with limited computational resources. our system also benefits high-end multiprocessor robots by leaving ample processor time on all camera-computer pairs to perform other critical visual tasks, such as obstacle detection. experimental results are shown for outdoor, off-road loops on the order of 200 meters. comparisons are made with corresponding results from a state-of-the-art pure visual odometer.
a virtual machine-based approach for fast and flexible reprogramming of modular robots. modular robot programming spans a number of issues ranging from high-level coordination to controller distribution and update in individual modules. the latter issue has received little attention from the research community though in our experience it is one of the main factors hindering agile development and experimentation with physical robots: reprogramming tens or hundreds of modules can be a major overhead in the development process and cannot be done with traditional approaches without restarting the robot, which impedes updating a running system. we propose a solution based on a virtual machine design shaped around three core concepts: the context of a module and its role in the ensemble, the reactive nature of robot controllers, and control programs decomposable into subparts that can be dynamically and separately redefined. we show that by incorporating those concepts into the design we are able to both achieve program conciseness (thus providing fast and efficient code distribution) and program expressiveness (thus providing versatility to represent diverse control algorithms). the virtual machine is programmed in a high-level role-oriented language that allows the programmer to declaratively specify how programs are deployed in the modular robot. our approach enables fast and incremental on-line updates, allowing the programmer to interactively experiment with the physical robots. we show how this design lends itself to an efficient implementation targeting typical resource-constrained modular robotic hardware by illustrating our prototype implementation for the atron self-reconfigurable robot.
path following for an omnidirectional mobile robot based on model predictive control. in this paper, the path following problem of an omnidirectional mobile robot has been studied. given the error dynamic model derived from the robot state vector and the path state vector, model predictive control (mpc) is employed to design the control law, which can deal explicitly with the rate of progression of a virtual vehicle to be followed along the path. the distinct advantage over other control strategies is that input and system constraints are able to be handled straight forwardly in the optimization problem so that the robot can travel safely with a high velocity. unlike nonholonomic mobile robots, omnidirectional mobile robots, which we focus on in this paper, have simultaneously and independently controlled rotational and translational motion capabilities. then, our purposed mpc controller was validated by experiments with a real omnidirectional mobile robot.
geo-contextual priors for attentive urban object recognition. mobile vision services have recently been proposed for the support of urban nomadic users. while camera phones with image based recognition of urban objects provide intuitive interfaces for the exploration of urban space and mobile work, similar methodology can be applied to vision in mobile robots and autonomous aerial vehicles. a major issue for the performance of the service - involving indexing into a huge amount of reference images - is ambiguity in the visual information. we propose to exploit geo-information in association with visual features to restrict the search within a local context. in a mobile image retrieval task of urban object recognition, we determine object hypotheses from (i) mobile image based appearance and (ii) gps based positioning, and investigate the performance of bayesian information fusion with respect to benchmark geo-referenced image databases (tsg-20, tsg-40). this work specifically proposes to introduce position information as geo-contextual priors for geo-attention based object recognition to better prime the vision task. the results from geo-referenced image capture in an urban scenario prove a significant increase in recognition accuracy (> 10%) when using the geo-contextual information in contrast to omitting geo-information, the application of geo-attention is capable to improve accuracy by further > 5%.
object inherent dynamics based motion control in human-robot cooperative task system. in this paper we address a robot motion control scheme for a human-robot cooperative task. from the viewpoint of improving the operative efficiency of the cooperative task, we designed a novel robot control system, in which inherent dynamics of the target task and the object is conserved. the proposed control scheme differs widely from an ordinary impedance control scheme in that the inherent dynamics of the target task and the object is substituted by impedance characteristics. under the proposed control scheme, the dynamics of the target task and that of the robot motion are uncoupled and independent. the proposed control system enables the human operator to carry out the cooperative task intuitively by only considering the inherent dynamics of the target task and the object. to confirm the effectiveness of the proposed control system, an experiment base on a peg insertion task involving human-robot cooperation is carried out. the experimental results show that the proposed control scheme is effective for cooperative tasks requiring precision.
the autonomous city explorer (ace) project - mobile robot navigation in highly populated urban environments. one of the greatest challenges nowadays in robotics is the advancement of robots from industrial tools to companions and helpers of humans, operating in natural, populated environments. in this respect, the autonomous city explorer (ace) project aims to combine the research fields of autonomous mobile robot navigation and human robot interaction. a robot has been created that is capable of navigating in an unknown, highly populated, urban environment, based only on information extracted through interaction with passers-by and its local perception capabilities. this paper describes the algorithms and architecture that make up the navigation subsystem of ace. more specifically, the algorithms used for simultaneous localization and mapping (slam), path planning in dynamic environments and behavior selection are presented, as well as the system architecture that integrates them to a complete working system. results from an extended field experiment, where the robot navigated autonomously through the downtown city area of munich, are analyzed and show that the robot is capable of long-term, safe navigation in real-world settings.
roadmap-based stealth navigation for intercepting an invader. this paper deals with the stealth target-interception problem based on the active prediction planning execution (appe) strategy. in order to cope with the evasive feature of the invader, we make the robot move stealthily by hiding behind obstacles. we adopt a roadmap-based decoupled approach, which plans the path and the trajectory separately by developing new concept; the detection map. simulation results demonstrate the efficiency of the proposed algorithm. it has an enough practical running time to be applied to the real-time situation.
design and implementation of a 9-axis inertial measurement unit. we report on a 9-axis inertial measurement unit (imu) which utilizes 3-axis angular velocity measurements from rate gyros and 6-axis linear acceleration measurements from three 2-axis accelerometers. this system is capable of deriving linear acceleration, angular acceleration and angular velocity via simple matrix operations, and it also releases the requirement of accelerometer installation at the center of mass as in the traditional imu. an optimal configuration of the system is proposed based on the analysis of rigid body dynamics and matrix theory. we performed error analyses, including position, orientation, and sensor noise, and we also report the results of experimental evaluation. we believe the analysis presented in this paper would benefit the practical design of imus in the future.
fir position profiles using an infinitely continuous kernel. large and fragile systems may require motion trajectories with the highest attainable degree of smoothness. this paper introduces a method to create infinitely continuous motion profiles based on convolving an infinitely continuous fir kernel with an underlying rate-limited position profile. conventional motion profiling is limited to blending polynomial between linear segments. due to the issues of controlling unwanted inflections and the computing of the polynomial coefficient, blending polynomials are usually limited to third order with special cases up to seventh order. beyond third order, closed form equations do not exists for the coefficients, requiring a set of equations to be solved for each blend. with third order polynomials the highest derivative that can be controlled is jerk. while maximum jerk can be controlled, change in jerk is instantaneous. this inherent instantaneous change in jerk can send shock waves though a system with the possibility of causing damage. the infinitely continuous profiles introduced in this paper overcomes all the shortcomings of polynomial blending. with fir smoothing of an underlying rate-limited position profile, only a single kernel is needed to be computed off-line before motion starts. the entire process of motion generation consists of rate-limiting desired position updates and then filtering them with an infinitely continuous fir kernel. the output is an infinitely continuous profile that allows real-time updates of velocity. two methods are introduced to create the kernels. in the first method the duration of the kernel is minimized for a given maximum value of any derivative. in the second method the maximum value of any derivative is minimized for a given kernel duration. the use of the convolution instead of polynomial fitting to create profiles is simpler, eliminates special cases, and allows real-time updates of velocity while producing maximally smooth profiles.
synchronous eeg brain-actuated wheelchair with automated navigation. this paper describes a new non-invasive brain-actuated wheelchair that relies on a p300 neurophysiological protocol and automated navigation. in operation, the subject faces a screen with a real-time virtual reconstruction of the scenario, and concentrates on the area of the space to reach. a visual stimulation process elicits the neurological phenomenon and the eeg signal processing detects the target area. this target area represents a location that is given to the autonomous navigation system, which drives the wheelchair to the desired place while avoiding collisions with the obstacles detected by the laser scanner. the accuracy of the brain-computer interface is above 94% and the flexibility of the sensor-based motion system allows for navigation in non-prepared and populated scenarios. the prototype has been validated with five healthy subjects in three experimental sessions: screening (an analysis of three different interfaces and its implications on the performance of the users), virtual environment driving (training and instruction of the users) and driving sessions with the wheelchair (driving tests along pre-established circuits). on the basis of the results, this paper reports a technical evaluation of the device and a variability study. all the users were able to successfully use the device with relative ease showing a great adaptation.
generic nonlinear model of reduced scale uavs. this paper proposes, through a survey of models of several uav-structures, a generic nonlinear model for reduced scale aerial robotic vehicles (6 dof). dynamics of an aircraft and some vtol uav (quadricopter, ducted fan and classical helicopter) are illustrated. this generic model focuses only on the key physical efforts acting on the dynamics in order to be sufficiently simple to design a controller. the small body forces expression which can introduce a zero dynamics is then discussed.
dynamic modeling and analysis of pitch motion of a basilisk lizard inspired quadruped robot running on water. a quadrupedal robot inspired by the basilisk lizard was developed and modeled with a 3-d real time simulation. due to the robot's geometry, leg motion, and water interactions, the net pitch moment at the center of mass is not zero making pitch motion unstable. this paper introduces two types of tails, passive and active, to stabilize pitch motion and analyzes the advantages and disadvantages of each. it is shown in simulation that a purely passive tail can stabilize pitch motion and lead to a steady state robot pitch angle in the absence of disturbances. it is further shown that an active tail can compensate for disturbances and correct any drift in the robot body pitch angle due to changes in robot running speed.
crawling by body deformation of tensegrity structure robots. in this paper, we describe the design of a deformable robot with a tensegrity structure that can crawl and we show the results of experiments showing the ability of these robots to crawl. we first describe a tensegrity structure, composed of struts and cables, and its characteristics. we next explain the principle of crawling by robot body deformation, followed by a classification of the methods by which a body can be deformed and the contact conditions of the robot through the cable-graph of the tensegrity structure. we also describe topological transition graphs that can visualize crawling from each initial contact condition. we then discuss the characteristics of the proposed robot in terms of design freedom. finally, we show experimentally that the prototype of a tensegrity robot can crawl.
attractiveeye: augmented gaze representation for "what is the robot looking at?". this paper describes a novel approach that can be used to determine the focal object that a robot is looking at and introduces the unique robotic eye, attractiveeye. humans have the visual input mechanism but do not have the output mechanism concerning the visual signal except gestures. attractiveeye can communicate information regarding the color of an object by changing its color to match that of the object. thus, from the color of this robot, we can determine the focal object that it is looking at. we carry out a human-robot interaction experiment to show that human-robot interaction can be made easier by using attractiveeye.
experimental validation of model-based thruster fault detection for underwater vehicles. this paper describes a model-based thruster fault detection scheme for an autonomous underwater vehicle. for a vehicle equipped with servo motor based marine thrusters, the velocity and current feedback from the motor controllers can be used to derive two independent thrust approximations. the difference between the two models reveals the presence of fault conditions, and quantifies the error of the output thrust relative to the desired reference. the method is proven effective through experimental validation.
design of man-machine cooperative nonholonomic two-wheeled vehicle based on impedance control and time-state control. this paper presents a new control methodology for a nonholonomic electric two-wheeled vehicle wherein the autonomous and man-machine cooperative controls are synthesized. in the proposed control scheme, the 'autonomous control' and the 'man-machine cooperative control' are designed by synthesizing time-state control and impedance control. the time-state controller tries to reduce the machine's deviation from the guideline, the impedance controller, on the other hand, generates power to assist the operator's maneuver. furthermore, experimental results are shown to demonstrate the usefulness of the proposed strategy.
muscle tension database for contact-free estimation of human somatosensory information. contact-free estimation of the human somatosensory information is an essential skill for robots working in daily environments. the main objective of this paper is to develop a method for estimating muscle tensions without any sensors attached to the body. muscle tension is an important information for evaluating physical load during motions. existing approaches utilizing optimization techniques and/or electromyography (emg) signals are not appropriate due to lack of physiological validity or usage of electrodes. in this paper, we propose to use a database of muscle tension distribution for obtaining physiologically realistic muscle tensions only from motion data. using such database instead of direct emg measurement is justified by the fact that muscle tension distribution is relatively highly correlated even among different subjects. for each new motion frame, we search for a similar entry in the database and use the corresponding muscle tension distribution to estimate the current muscle tensions. we demonstrate that the muscle tensions obtained by this approach is much closer to the result using the emg data than that using pure numerical optimization, even when the database is constructed from other person's data.
autonomous map construction using three-dimensional feature descriptors. autonomous robotic mapping has been an open research topic for more than twenty years. the primary objective of the robotic mapping problem is to design methods that can guide a robot around an environment and allow it to create a map of what has been sensed. most automatic mapping algorithms rely on robot pose estimation to fuse map data together. this paper demonstrates that through feature extraction using spin-histograms, the pose of the robot can be estimated accurately enough for an iterative closest point (icp) algorithm to register overlapping data sets. by eliminating consideration for points according to curvature and saliency, the spin-histogram matching process can improve in both accuracy and computation time. in combination with a global registration algorithm known as simultaneous matching, this process can obtain a fully autonomous registration process.