waashk/dblp huggingface dataset:
imitation learning with generalized task descriptions. in this paper, we present an approach that allows a robot to observe, generalize, and reproduce tasks observed from multiple demonstrations. motion capture data is recorded in which a human instructor manipulates a set of objects. in our approach, we learn relations between body parts of the demonstrator and objects in the scene. these relations result in a generalized task description. the problem of learning and reproducing human actions is formulated using a dynamic bayesian network (dbn). the posteriors corresponding to the nodes of the dbn are estimated by observing objects in the scene and body parts of the demonstrator. to reproduce a task, we seek for the maximum-likelihood action sequence according to the dbn. we additionally show how further constraints can be incorporated online, for example, to robustly deal with unforeseen obstacles. experiments carried out with a real 6-dof robotic manipulator as well as in simulation show that our approach enables a robot to reproduce a task carried out by a human demonstrator. our approach yields a high degree of generalization illustrated by performing a pick-and-place and a whiteboard cleaning task.
a two-steps next-best-view algorithm for autonomous 3d object modeling by a humanoid robot. a novel approach is presented which aims at building autonomously visual models of unknown objects, using a humanoid robot. previous methods have been proposed for the specific problem of the next-best-view during the modeling and the recognition process. however our approach differs as it takes advantage of humanoid specificities in terms of embedded vision sensor and redundant motion capabilities. in a previous work, another approach to this specific problem was presented which relies on a derivable formulation of the visual evaluation in order to integrate it with our posture generation method. however to get rid of some limitations we propose a new method, formulated using two steps: (i) an optimization algorithm without derivatives is used to find a camera pose which maximizes the amount of unknown data visible, and (ii) a whole robot posture is generated by using a different optimization method where the computed camera pose is set as a constraint on the robot head.
semi-supervised particle filter for visual tracking. in this paper, a semi-supervised particle filter approach is proposed for visual tracking. the combination of semi-supervised learning and particle filter is very natural since the unlabelled samples are generated by particle propagation. in addition, the proposed semi-supervised particle filter can online select different features for robust tracking. to the best knowledge of the authors, this is the first time for the semi-supervised learning technology to be incorporated into the framework of particle filter. finally, the performance of the proposed approach is evaluated using real visual tracking examples.
adaptive output feedback control of uncertain nonholonomic systems with strong nonlinear drifts. in this paper, an adaptive output feedback control strategy is presented to solve the stabilization problem of nonholonomic systems in chained form with strong nonlinear drifts and uncertain parameters using output signals only. the control law is developed using input-state scaling and backstepping techniques. the objective is to design adaptive nonlinear output feedback laws which can steer the closed-loop systems globally converge to the origin, while the estimated parameters remain bounded. an adaptive output feedback controller is proposed for a class of uncertain chained systems. simulation results demonstrate the effectiveness of the proposed controllers.
information retrieval system for human-robot communication - asking for directions. the creation of a robot capable of navigating in unknown urban environments without the use of gps data or prior map knowledge is envisioned in the autonomous city explorer (ace) project. the robot has to retrieve direction information solely by interacting with humans. this work presents a human-robot communication system that enables the robot to ask for directions and store the retrieved route information as internal knowledge. the system incorporates theories from linguistics in a mixed-modalities communication interface. it stores acquired information into a topological route graph which is used to give feedback to the human and to navigate in unknown environments.
evaluation of 3d registration reliability and speed - a comparison of icp and ndt. to advance robotic science it is important to perform experiments that can be replicated by other researchers to compare different methods. however, these comparisons tend to be biased, since re-implementations of reference methods often lack thoroughness and do not include the hands-on experience obtained during the original development process. this paper presents a thorough comparison of 3d scan registration algorithms based on a 3d mapping field experiment, carried out by two research groups that are leading in the field of 3d robotic mapping. the iterative closest points algorithm (icp) is compared to the normal distributions transform (ndt). we also present an improved version of ndt with a substantially larger valley of convergence than previously published versions.
combining planning and motion planning. robotic manipulation is important for real, physical world applications. general purpose manipulation with a robot (eg. delivering dishes, opening doors with a key, etc.) is demanding. it is hard because (1) objects are constrained in position and orientation, (2) many non-spatial constraints interact (or interfere) with each other, and (3) robots may have multi-degree of freedoms (dof). in this paper we solve the problem of general purpose robotic manipulation using a novel combination of planning and motion planning. our approach integrates motions of a robot with other (non-physical or external-to-robot) actions to achieve a goal while manipulating objects. it differs from previous, hierarchical approaches in that (a) it considers kinematic constraints in configuration space (c-space) together with constraints over object manipulations; (b) it automatically generates high-level (logical) actions from a c-space based motion planning algorithm; and (c) it decomposes a planning problem into small segments, thus reducing the complexity of planning.
parallel-distributed model in three-dimensional soft-fingered grasping and manipulation. this paper focuses on three-dimensional grasping and manipulation by robotic fingers with soft fingertips. the authors have proposed two-dimensional parallel-distributed model of a soft fingertip to describe the dependency of its potential energy to the relative orientation between the fingertip and the object. here we extend the previous two-dimensional model to three-dimensional model, incorporating the rotation in three-dimensional space. we formulate the elastic potential energy stored in a soft fingertip due to the contact with the planar surface in three-dimensional space. we sketch the lagrangian of the system consisting of a rigid prism grasped by three fingers with soft fingertips.
active exploration using scheme of autonomous distribution for landmarks. this paper investigates the on-line autonomous distribution for landmarks and the active exploration in environment without or lack of landmarks/features, such as disaster conditions and polar region. in such situation, the robot enters the environment carrying some landmarks and distributes them according to the rules given in this paper. the utility of the landmark distribution is analyzed. then, based on the extended kalman filter (ekf), the active exploration is converted into a problem of multi-objective optimization, in which the objective function includes three aspects, i.e. the accuracy of localization and mapping, the predictive area of the unknown environment that will be explored in next step and the information gain provided by the distributed landmarks respectively. the robot chooses the control input that optimizes the objective function such that accurate localization, high-quality mapping and complete exploration will be realized. and then, the supplementation and the redundancy elimination for landmarks are implemented. at last, a set of simulations is presented to show the effectiveness of our approach.
task-space setpoint control of robots with dual task-space information. in conventional task-space control problem of robots, a single task-space information is used for the entire task. when the task-space control problem is formulated in image space, this implies that visual feedback is used throughout the movement. while visual feedback is important to improve the endpoint accuracy in presence of uncertainty, the initial movement is primarily ballistic and hence visual feedback is not necessary. the relatively large delay in visual information would also make the visual feedback ineffective for fast initial movements. due to limited field of view of the camera, it is also difficult to easure that visual feedback can be used for the entire task. therefore, the task may fail if any of the features is out of view. in this paper, we present a new task-space control strategy that allows the use of dual task-space information in a single controller. we shall show that the proposed task-space controller can transit smoothly from cartesian-space feedback at the initial stage to vision-space feedback at the end stage when the target is near.
morphological design optimization of kinematically redundant manipulators using weighted isotropy measures. kinematically redundant manipulators are coveted for their ability to perform more complex and a greater variety of tasks than their non-redundant counterparts. this increased utility demands that manipulator designs be carefully optimized to achieve the kinematic dexterity required to perform their numerous intended tasks. the optimization of redundant manipulator designs to improve isotropy has been studied at great length, but a vast majority of the work done focuses on planar manipulation tasks and workspaces that, unlike many modern manufacturing environments, offer few or no physical impediments to motion. in this paper we investigate the incorporation of secondary manipulation goals, in particular obstacle avoidance, into the calculation of kinematic isotropy measures. we will use these weighted isotropy measures as a performance metric for redundant manipulators working in obstacle-laden workspaces, and employ the metric as part of an objective function for a global search design optimization problem. the effectiveness of the weighted isotropy design optimization will be demonstrated by increasing the global dexterity of a sub-optimal seven degree-of-freedom manipulator design used for pick-and-place tasks within a small, enclosed workspace.
intelligent power management: promoting power-consciousness in teams of mobile robots. effective robotic autonomy requires an accurate estimation of the remaining power that the robot is carrying. there are a number of methods to estimate the remaining capacity of the robot's batteries. the accuracy of these approaches varies depending upon the chemical composition of the batteries as well as the means by which the monitoring is conducted. in this paper, an overview of various battery capacity estimation methodologies will be presented as well as a discussion of a specific implementation utilized on robotic platforms developed at the center for distributed robotics at the university of minnesota. this approach involves the novel use of fuel-gauging electronics for mobile robotic platforms. experiments were conducted to show the accuracy of this method for both charge and discharge of the polymer lithium-ion batteries in use.
local voronoi decomposition for multi-agent task allocation. we propose a local voronoi decomposition (lvd) algorithm which is able to perform a robust and online task allocation for multiple agents based purely on local information. because only local information is required in determining each agent's voronoi region, each agent can then make its decision in a distributive fashion based on its allocated voronoi region. these voronoi regions eliminates the occurrence of agents executing instantaneous overlapping tasks. as our method does not require a pre-processing of the map, it is also able to work well in a dynamically changing map with changing number of agents. we will show our proof of concept in the problem of exploration in an unknown environment. in our experimental evaluation, we show that our method significantly outperforms the competing algorithms: ants algorithm and the brick&mortar algorithm. our results also show that our method is near the theoretical best solution.
optimal control of a space manipulator for detumbling of a target satellite. robotic capture of a tumbling target-satellite means that the space robot's hand and the target grapple point arrive at a rendezvous point with the same velocity and then the chase vehicle mechanically connects into the target using a grapple device. this paper is focused on optimal control of the space manipulator in the postcapture phase so as to bring the tumbling non-cooperative satellite to rest in minimum time while ensuring that the magnitude of the interaction torque between the manipulator and target remains below a prescribed value. first, we seek fast detumbling maneuvers of the target satellite subjected to the torque restriction. the theory of optimal control and pontryagin's principle are applied to obtain a closed-form solution for the optimal path planning problem, giving a great deal of insight: the vector of the interaction torque is aligned opposite to the direction of the instantaneous angular momentum vector. second, a coordination control for combined system of the space robot and the target satellite, which acts as the manipulator payload, is developed so that the robot tracks the optimal path while regulating the attitude of the chase vehicle to a desired value. a preliminary illustrative example is appended.
planning and control of a teleoperation system for research in minimally invasive robotic surgery. this paper introduces the planning and control software of a teleoperation system for research in minimally invasive robotic surgery. it addresses the problem of how to organize a complex system with 41 degrees of freedom as a flexible configurable platform. robot setup planning, force feedback control and nullspace handling with three robotic arms are considered. the planning software is separated into sequentially executed planning and registration procedures. an optimal setup is first planned in virtual reality and then adapted to variations in the operating room. the real time control system is structured in hierarchical layers. functions are arranged in the layers with respect to their domain and maximum response time. the design is flexible and expandable while performance is maintained. structure, functionality and implementation of planning and control are described. the prototypic robotic system provides intuitive bimanual bilateral teleoperation within the planned working space.
robust edge extraction for swissranger sr-3000 range images. this paper presents a new method for extracting object edges from range images obtained by a 3d range imaging sensor--the swissranger sr-3000. in range image preprocessing stage, the method enhances object edges by using surface normal information; and it employs the hough transform to detect straight line features in the normal-enhanced range image (neri). due to the noise in the sensor's range data, a neri contains corrupted object surfaces that may result in unwanted edges and greatly encumber the extraction of linear features. to alleviate this problem, a singular value decomposition (svd) filter is developed to smooth object surfaces. the efficacy of the edge extraction method is validated by experiments in various environments.
ca: controlled conservative advancement for continuous collision detection of polygonal models. we present a simple and fast algorithm to perform continuous collision detection between polygonal models undergoing rigid motion for interactive applications. our approach can handle all triangulated models and makes no assumption about the underlying geometry and topology. the algorithm uses the notion of conservative advancement (ca), originally developed for convex polytopes [1], [2]. we extend this formulation to general models using swept sphere volume hierarchy and present a compact formulation to compute the motion bounds along with a novel controlling scheme. we have implemented the algorithm and highlight its performance on various benchmarks. in practice, our algorithm can perform continuous collision queries in few milli-seconds on models composed of tens of thousands of triangles.
model-reference based wave-variable force control. internal friction, backlash and structural compliance within a robot makes force control a tricky noncolocated control problem. traditional force controllers are typically tuned for a specific environment and invariably have instability problems when contacting stiffer environments. this paper presents a new force controller designed to use control effort to compensate for energy losses due to friction without modifying the robots underlying passive dynamics. the controller uses a lossless model of the robot's inertia to predict the robot's motion in real time based on the wave-variables flowing between robot and environment. the model motion is used as a desired input for a wave-variable based controller. to calculate the wave variables the controller uses measurements of both the contact force and the acceleration at the end-effector. the resulting controller is compared analytically and experimentally to more traditional controllers.
development of robot hand aiming at nursing care services to humans. this paper describes a multi-joint robot finger with soft compliant mechanism for safe and comfortable nursing-care services. in proposed mechanism, we utilize 2 different types of elastic elements at fingertip and mp joint (metacarpa-phalangeal joint), respectively, so as to realize soft and stable contact with human body. at fingertip, a hemisphere shaped silicone gum cushion is mounted, while eight cylindrical cushions are placed between the motor and the link inside mp joint. these cushions deform easily and, as a result, absorb external forces exerted from multiple directions. furthermore the amplitudes and the directions of applied forces can be estimated with the information of changes in the pressure of each cushion.we examined the fundamental characteristics and performance of this finger module through several experiments.
optimum design and investigation on diffuser polymethylmethacrylate (pmma) peristaltic micropumps. utilizing micro-electro-mechanical-systems (mems) techniques and a solvent-assisted bonding process, a new generation of diffuser peristaltic polymethylmethacrylate (pmma) micropumps was optimized and fabricated. the main purpose of this study is to compare the performance of optimized and un-optimized micopump which have the same diffuser throat/inlet area (i.e. 16000 µm2). furthermore, an additional optimized design which has smaller diffuser inlet area was considered to validate and analyze the effect of diffuser inlet area to the micropump performance. the experimental results were validated by comparing with previous generation which had not been optimized the diffuser element. specifically, the experimental results showed that, with similar diffuser element inlet area (i.e. 160000 µm2), with and without optimized micropumps yield maximum flow rates of 246.4 µl/min and 194.8 µl/min, respectively. furthermore, it is shown that the back pressure in the optimized micropump is 6.9 kpa, while that in the un-optimized pump is 5.69 kpa. the effect of diffuser element throat/inlet area to pump flow rate and back pressure was investigated by comparing the experimental results of two optimized designs, one with 80 µm × 80 µm and the other with 127 µm × 127 µm cross-sectional area. the results indicated that, the design with larger inlet area gave higher flow rate. however, the rate of reduction in the maximum flow rate with increasing backpressure increases at the higher inlet area design, which is due to the greater pressure dissipation/loss associated with a larger channel cross-sectional area.
accurate 3d ground plane estimation from a single image. accurate localization of landmarks in the vicinity of a robot is a first step towards solving the slam problem. in this work, we propose algorithms to accurately estimate the 3d location of the landmarks from the robot only from a single image taken from its on board camera. our approach differs from previous efforts in this domain in that it first reconstructs accurately the 3d environment from a single image, then it defines a coordinate system over the environment, and later it performs the desired localization with respect to this coordinate system using the environment's features. the ground plane from the given image is accurately estimated and this precedes segmentation of the image into ground and vertical regions. a markov random field (mrf) based 3d reconstruction is performed to build an approximate depth map of the given image. this map is robust against texture variations due to shadows, terrain differences, etc. a texture segmentation algorithm is also applied to determine the ground plane accurately. once the ground plane is estimated, we use the respective camera's intrinsic and extrinsic calibration information to calculate accurate 3d information about the features in the scene.
where to go: interpreting natural directions using global inference. an important component of human-robot interaction is that people need to be able to instruct robots to move to other locations using naturally given directions. when giving directions, people often make mistakes such as labelling errors (e.g., left vs. right) and errors of omission (skipping important decision points in a sequence). furthermore, people often use multiple levels of granularity in specifying directions, referring to locations using single object landmarks, multiple landmarks in a given location, or identifying large regions as a single location. the challenge is to identify the correct path to a destination from a sequence of noisy, possibly erroneous directions. in our work we cast this problem as probabilistic inference: given a set of directions, an agent should automatically find the path with the geometry and physical appearance to maximize the likelihood of those directions. we use a specific variant of a markov random field (mrf) to represent our model, and gather multi-granularity representation information using existing large tagged datasets. on a dataset of route directions collected in a large third floor university building, we found that our algorithm correctly inferred the true final destination in 47 out of the 55 cases successfully followed by humans volunteers. these results suggest that our algorithm is performing well relative to human users. in the future this work will be included in a broader system for autonomously constructing environmental representations that support natural human-robot interaction for direction giving.