waashk/dblp huggingface dataset:
mapping opaque and confined environments using proprioception. mapping opaque and confined environments such as caves and pipes is a challenging problem for mobile robots because sensor information is severely limited to the immediate proximity of the robot due to the extreme environmental conditions. the robot must also be flexible and agile in unstructured environments while still providing accurate pose estimation. this paper presents a solution to mapping a 2-dimensional tube by using only a snake robot's proprioceptive joint angle sensors. we assume that the tube is sufficiently smooth and that we know the tube width. we propose techniques for (1) pose estimation of a snake robot by using a self-posture motion model, (2) correcting error in pose estimation using only the snake's internal configuration over time, and (3) building environmental features using only self-occupancy and contact detection. our goal is to use the minimal amount of sensor information possible to build an accurate spatial map of the environment. we have tested the proposed techniques in simulated environments and experimental results show that they are both effective and efficient for mapping tube environments. we plan to extend these techniques to deal with more complex confined environments beyond single-path tubes.
autonomous driving in a multi-level parking structure. recently, the problem of autonomous navigation of automobiles has gained substantial interest in the robotics community. especially during the two recent darpa grand challenges, autonomous cars have been shown to robustly navigate over extended periods of time through complex desert courses or through dynamic urban traffic environments. in these tasks, the robots typically relied on gps traces to follow pre-defined trajectories so that only local planners were required. in this paper, we present an approach for autonomous navigation of cars in indoor structures such as parking garages. our approach utilizes multi-level surface maps of the corresponding environments to calculate the path of the vehicle and to localize it based on laser data in the absence of sufficiently accurate gps information. it furthermore utilizes a local path planner for controlling the vehicle. in a practical experiment carried out with an autonomous car in a real parking garage we demonstrate that our approach allows the car to autonomously park itself in a large-scale multi-level structure.
task space robot control using an inner pd loop. this paper presents a task-space robot controller composed of two nested loops. the inner loop corresponds to a proportional-derivative joint-position controller and the outer loop consists of a proportional-integral controller fed by task space measurements. the lyapunov method allows concluding closed loop stability and a visual servoing application permits assessing the performance of the proposed controller.
magnetic dipoles for electromagnetic multi-dof actuator design. this paper presents a new method for solving the magnetic forces/torques of a multi-dof spherical actuator that has more controlling inputs than its mechanical dof. unlike methods that based on the lorentz force equation or the maxwell stress tensor, which require computing the volume or surface integrals to derive the forces, the dipole force method presented here offers the magnetic force solution in closed form. we validate the dipole force model against published experimental data, and demonstrate its application in solving the inverse torque model of a multi-dof spherical motor, which computes the required set of maximum current inputs for a given design specifications.
formations on two-layer pursuit systems. the paper studies hierarchical pursuit strategies for groups of mobile agents in the plane. it is shown that fascinating global patterns emerge from simple two-layer pursuit schemes, including rendezvous, uniform circular motion, complex circular motion, concentric circular motion, and concentric logarithmic spiral motion. both rigorous analysis and simulations are provided.
omni-directional steer-by-wire interface for four wheel independent steering vehicle. in this paper, an omni-directional steer-by-wire interface for four wheel independent steering vehicle is presented. the proposed steering interface is an extension of a traditional steering interface that provides three steering inputs. by combination of which, driver can control the vehicle in traditional way or omni-directionally without any mode switching operation. the reservation of the conventional steering behavior makes driver easy to adapt the novel steering interface. the force feedback controller is designed to synchronize the extended steering interface and the orientations of wheels so as to improve vehicle handling. hardware-in-the-loop simulations are conducted to verify the hardware prototype and examine the proposed algorithms.
surveillance of a polygonal area by a mobile searcher from the boundary: searchability testing. we study the surveillance of a polygonal area by a robot, which is equipped with a flashlight and moves along the polygon boundary. its aim is to illuminate any intruder who can move faster than the moving flashlight beam, trying to avoid detection. we propose an o(n)-time algorithm for testing if it is possible for such a robot to always detect any intruder in a given polygon, where n is the number of vertices of the given polygon. this improves upon the best previous time complexity of o(n log n).
asymptotic stability of teleoperators with variable time-delays. this paper extends the previous results on position tracking for bilateral teleoperators with constant time-delays, reported in nuño et al. ieee trans. robot., vol. 24, no. 3, pp. 753-758, june 2008, to the case of variable time-delays in the teleoperator's communications. the key part is the extension of a previous lemma that is used to prove that p+d or pd+d controllers can stabilize the teleoperator under variable time-delays, and moreover, they provide position tracking. the paper outlines the conditions under which velocities and position errors, of the nonlinear teleoperator, are bounded, and using barbalat's lemma, it is proved asymptotic converge to zero if the local manipulator stands still and the remote manipulator does not interact with the environment. simulations and real experiments validate the proposed schemes. the experiments have been performed using the internet as communication channel between urbana-champaign, usa and barcelona, spain.
identification of robots dynamics with the instrumental variable method. the identification of the dynamic parameters of robot is based on the use of the inverse dynamic model which is linear with respect to the parameters. this model is sampled while the robot is tracking "exciting" trajectories, in order to get an over determined linear system. the linear least squares solution of this system calculates the estimated parameters. the efficiency of this method has been proved through the experimental identification of a lot of prototypes and industrial robots. however, this method needs joint torque and position measurements and the estimation of the joint velocities and accelerations through the pass band filtering of the joint position at high sample rate. so, the observation matrix is noisy. moreover identification process takes place when the robot is controlled by feedback. these violations of assumption imply that the ls solution is biased. the simple refined instrumental variable (sriv) approach deals with this problem of noisy observation matrix and can be statistically optimal. this paper focuses on this technique which will be applied to a 2 degrees of freedom (dof) prototype developed by the irccyn robotic team.
mmm-classification of 3d range data. this paper presents a method for accurately segmenting and classifying 3d range data into particular object classes. object classification of input images is necessary for applications including robot navigation and automation, in particular with respect to path planning. to achieve robust object classification, we propose the idea of an object feature which represents a distribution of neighboring points around a target point. in addition, rather than processing raw points, we reconstruct polygons from the point data, introducing connectivity to the points. with these ideas, we can refine the markov random field (mrf) calculation with more relevant information with regards to determining "related points". the algorithm was tested against five outdoor scenes and provided accurate classification even in the presence of many classes of interest.
open e-puck range & bearing miniaturized board for local communication in swarm robotics. we have designed and built a new open hardware/ software board that lets miniaturized robots communicate and at the same time obtain the range and bearing of the source of emission. the open e-puck range & bearing board improves an existing infrared relative localization/communication software library (libircom) developed for the e-puck robot and based on its on-board infrared sensors. the board allows the robots to have an embodied, decentralized and scalable communication system. its use and capabilities are demonstrated via an alignment experiment.
resonance-based motion control method for multi-joint robot through combining stiffness adaptation and iterative learning control. this paper proposes a new trajectory tracking control method for multi-joint robots by combining stiffness adaptation and iterative learning control. the proposed controller achieves trajectory tracking while optimizing stiffness of elastic elements installed in each joint of the robots. even though the multi-joint robots have nonlinear dynamics and multi degree-of-freedom, the stiffness optimization realizes high energy efficiency as if we utilized resonance. an advantage of the proposed control is to work well without using exact parameter values of the robots. since it seems that adaptive control and iterative learning control have not been used simultaneously, this paper newly proposes a methodology to appropriately combine stiffness adaptation and iterative learning control. this combination enables trajectory tracking and convergence of the stiffness to the optimal one. these properties can not be achieved by our previous controllers.
bayesian network-based behavior control for skilligent robots. a skilligent robot must be able to learn skills autonomously to accomplish a task. "skilligence" is the capacity of the robot to control behaviors reasonably, based on the skills acquired during run-time. behavior control based on bayesian networks is used to control reasonable behaviors. to accomplish this, subgoals are first discovered by clustering similar features of state transition tuples, which are composed of current states, actions, and next states. here, features used in clustering are produced using changes of the states in the state transition tuples. parameters of bayesian networks and utility functions are learned separately using state transition tuples belonging to each subgoal. to select the best action while executing a task, the expected utility of each subgoal is calculated by the expected utility function and the robot chooses the action that maximizes expected utility calculated by the maximum expected utility (meu) function. the meu function is based on the conditional probabilistic distributions of bayesian networks and utility functions. we also propose a method for reconstructing learned networks and increasing subgoals by incremental learning. to show the validities of our proposed methods, a task using dribbling-box-into-a-goal (dbig) and obstacle-avoidance-while-dribbling-box (oawdb) skills is simulated and experimented.
analysis of crohn's disease lesions in capsule endoscopy images. capsule endoscopy (ce) is aimed at diagnosing disease in areas of the gastrointestinal (gi) tract beyond the reach of conventional endoscopy. recent work has addressed various methods for reducing the complexity of ce diagnosis and the time needed for analyzing the data. this includes detection of lumen and its contractions, fluids such as blood and intestinal juices, as well as extraneous matter such as food and bubbles. this paper outlines our ongoing work to segment lesions (in particular crohn's disease) and other abnormalities in ce images. in particular, here we describe the data collection and clinical analysis for our project and preliminary results for segmenting abnormal and extraneous images from a set of 10 ce studies.
multiple hypothesis tracking using clustered measurements. this paper introduces an algorithm for tracking targets whose locations are inferred from clusters of observations. this method, which we call mhtc, expands the traditional multiple hypothesis tracking (mht) hypothesis tree to include model hypotheses--possible ways the data can be clustered in each time step--as well as ways the measurements can be associated with existing targets across time steps. we present this new hypothesis framework and its probability expressions and demonstrate mhtc's operation in a robotic solution to tracking neural signal sources.
topological modeling and classification in home environment using sonar gridmap. this paper presents a method of topological representation and classification in home environment using only low-cost sonar sensors. approximate cell decomposition and normalized graph cut are applied to sonar gridmap to extract graphical model of the environment. the extracted model represents spatial relation of the environment appropriately by segmenting several subregions. moreover, node classification is achieved by applying template matching method to a local gridmap. rotational invariant matching is used to obtain candidate location for each node and the true node can be classified by considering detail distance information. the proposed method extracts well-structured topological model of the environment and classification also results in reliable matching even under the uncertain and sparse sonar data. experimental results verify the performance of proposed environmental modeling and classification in real home environment.
singo: a single-end-operative and genderless connector for self-reconfiguration, self-assembly and self-healing. flexible and reliable connection is critical for self-reconfiguration, self-assembly, or self-healing. however, most existing connection mechanisms suffer from a deficiency that a connection would seize itself if one end malfunctions or is out of service. to mitigate this limitation on self-healing, this paper presents a new singo connector that can establish or disengage a connection even if one end of the connection is not operational. we describe the design and the prototype of the connector and demonstrate its performance by both theoretical analysis and physical experimentations.
unsupervised learning of 3d object models from partial views. we present an algorithm for learning 3d object models from partial object observations. the input to our algorithm is a sequence of 3d laser range scans. models learned from the objects are represented as point clouds. our approach can deal with partial views and it can robustly learn accurate models from complex scenes. it is based on an iterative matching procedure which attempts to recursively merge similar models. the alignment between models is determined using a novel scan registration procedure based on range images. the decision about which models to merge is performed by spectral clustering of a similarity matrix whose entries represent the consistency between different models.
rapid pole climbing with a quadrupedal robot. this paper describes the development of a legged robot designed for general locomotion of complex terrain but specialized for dynamical, high-speed climbing of a uniformly convex cylindrical structure, such as an outdoor telephone pole. this robot, the rise v3 climbing machine--mass 5.4 kg, length 70 cm, excluding a 28 cm tail appendage--includes several novel mechanical features, including novel linkage designs for its legs and a non-backdrivable, energy-dense power transmission to enable high-speed climbing. we summarize the robot's design and document a climbing behavior that achieves rapid ascent of a wooden telephone pole at 21 cm/s, a speed previously unachieved--and, we believe, heretofore impossible--with a robot of this scale. the behavioral gait of the robot employs the mechanical design to propel the body forward while passively maintaining yaw, pitch, and roll stability during climbing locomotion. the robot's general-purpose legged design coupled with its specialized ability to quickly gain elevation and park at a vertical station silently with minimal energy consumption suggest potential applications including search and surveillance operations as well as ad hoc networking.
a compact rotational manipulator using shape memory alloy wire actuated flexures. this paper presents the design, fabrication, and control of a rotational manipulator using shape memory alloy (sma) wire actuated flexures. monolithic flexure mechanisms have no friction/backlash and are capable of miniaturization. they are well-suited for tasks that required high precision and packed space. to explore flexure shapes beyond traditional notch hinges and leaf springs, we present a general two-step design method to find the optimal flexure shapes for maximal rotation without yield. the advantages gained from shape variations are shown through a simulation example. we further use a sma wire to drive the flexure. sma exhibits large stroke with high power density and requires low driving voltage. by using versatile sma wire, the rotational range of the manipulator can be significantly increased while the overall size can be kept compact. a feedback pid control algorithm with fuzzy-tuned gains is implemented to precisely control the response of the manipulator. we illustrate its performance by tracking and step response experiments. with the merits shown, we expect this type of manipulator can be utilized in meso to micro scale applications.
dam wall detection and tracking using a mechanically scanned imaging sonar. in dam inspection tasks, an underwater robot has to grab images while surveying the wall meanwhile maintaining a certain distance and relative orientation. this paper proposes the use of an msis (mechanically scanned imaging sonar) for relative positioning of a robot with respect to the wall. an imaging sonar gathers polar image scans from which depth images (range & bearing) are generated. depth scans are first processed to extract a line corresponding to the wall (with the hough transform), which is then tracked by means of an ekf (extended kalman filter) using a static motion model and an implicit measurement equation associating the sensed points to the candidate line. the line estimate is referenced to the robot fixed frame and represented in polar coordinates (ρ&θ) which directly corresponds to the actual distance and relative orientation of the robot with respect to the wall. the proposed system has been tested in simulation as well as in water tank conditions.
a relative frame representation for fixed-time bundle adjustment in sfm. a successful approach in the recovery of video-rate structure from motion is to allow the camera to keep track of its position in every frame assuming the recovered set of scene landmarks is fixed in 3d, and then to use the poses in a subset of separated frames, or keyframes, to initialise further landmark structure. the landmark structure and keyframe poses are optimised in a bundle adjustment. unfortunately this monolithic bundle adjustment has cubic complexity. this paper shows how representing landmarks and camera poses in relative frames, and by temporarily removing certain measurements, introduces a conditional indepedence which allows the bundle adjustment to be split into two parts. one "local" part involves the most recent keyframes and associated landmarks, and runs in constant time. the other "global" part deals with older keyframes and structure, and runs, as ever, in cubic time. three important outcomes are: (i) the fixed-time local adjustment allows exploratory map-building to keep pace with camera pose tracking; (ii) it produces statistically consistent results; and (iii) referencing to relative frames means that any update in positions from the global adjustment are immediately incorporated in the local fixed-time adjustment. the relative frame approach is applied to the parallel tracking and mapping method for structure from motion, and its results shown to be identical, and the exploratory map building phase shown to maintain fixed time performance.
on the complexity and consistency of ukf-based slam. this paper addresses two key limitations of the unscented kalman filter (ukf) when applied to the simultaneous localization and mapping (slam) problem: the cubic, in the number of states, computational complexity, and the inconsistency of the state estimates. in particular, we introduce a new sampling strategy that minimizes the linearization error and whose computational complexity is constant (i.e., independent of the size of the state vector). as a result, the overall computational complexity of ukf-based slam becomes of the same order as that of the extended kalman filter (ekf) when applied to slam. furthermore, we investigate the observability properties of the linear-regression-based model employed by the ukf, and propose a new algorithm, termed the observability-constrained (oc)-ukf, that improves the consistency of the state estimates. the superior performance of the oc-ukf compared to the standard ukf and its robustness to large linearization errors are validated by extensive simulations.
modeling and motion stability analysis of skid-steered mobile robots. skid-steered mobile robots are widely used because of the simplicity of mechanism and high reliability. however, understanding of the kinematics and dynamics of such a robotic platform is challenging due to the complex wheel/ground interactions and kinematic constraints. in this paper, we attempt to develop a kinematic and dynamic modeling scheme to analyze the skid-steered mobile robot. we model wheel/ground interaction and analyze the robot motion stability. as an application example, we present how to utilize the kinematic and dynamic modeling and analysis for robot localization and slip estimation using only low-cost strapdown inertial measurement units (imu). the extended kalman filter (ekf)-based localization scheme incorporates the kinematic constraints. the performance of the ekf-based localization and slip estimation scheme are presented. the estimation methodology is tested and validated on a robotic testbed.
insect powered micro air vehicles. in this paper we present successful navigation of a mechanically linked insect moth-pair, using light-weight and low-power actuators, demonstrating insect powered micro air vehicles (mavs). these mavs can fly for long periods of time, consuming only a small fraction(1%) of power compared to purely mechanical mavs. we demonstrate strategies for harnessing the high energy-density biofuel and high efficiency muscle actuators of insects using tissue-embedded and externally attached miniature insect generated momentum redirectors. commercial off-the-shelf tail motor, a rudder that exploits flow behind the insect wings, and a steering mechanism that misaligns the thrust directions of two insects were all separately used to control yaw of the hawkmoth, manduca sexta, in tethered flight. untethered flight control of two hawkmoths over 60 m was achieved using a 6 gm backpack, including a 3 gram helium balloon to keep the backpack airborne, for over 5 to 30 minutes of flight time.