waashk/dblp huggingface dataset:
adequate motion simulation and collision detection for soccer playing humanoid robots. in this paper a humanoid robot simulator based on the multi-robot simulation framework (murosimf) is presented. among the unique features of this simulator is the scalability in the level of physical detail in both the robot's motion and sensing systems. it facilitates the development of control software for humanoid robots which is demonstrated for several scenarios from the robocup humanoid robot league. different requirements exist for a humanoid robot simulator. e.g., testing of algorithms for motion control and postural stability require high fidelity of physical motion properties whereas testing of behavior control and role distribution for a robot team requires only a moderate level of detail for real-time simulation of multiple robots. to meet such very different requirements often different simulators are used which makes it necessary to model a robot multiple times and to integrate different simulations with high-level robot control software. murosimf provides the capability of exchanging the simulation algorithms used for each robot transparently, thus allowing a trade-off between computational performance and fidelity of the simulation. it is therefore possible to choose different simulation algorithms which are adequate for the needs of a given simulation experiment, for example, motion simulation of humanoid robots based on kinematical, simplified dynamics or full multi-body system dynamics algorithms. in this paper also the sensor simulation capabilities of murosimf are revised. the methods for motion simulation and collision detection and handling are presented in detail including an algorithm which allows the real-time simulation of the full dynamics of a 21 dof humanoid robot. merits and drawbacks of the different algorithms are discussed in the light of different simulation purposes. the simulator performance is measured and illustrated in various examples, including comparison with experiments of a physical humanoid robot.
adaptive jacobian position/force tracking control of free-flying manipulators. this paper solves the problem of position/force tracking control of a free-flying space manipulator with uncertain kinematics and dynamics. a free-flying manipulator interacting with an uncertain compliant surface is considered. to cope with the uncertainties arising from free-flyer's kinematics, dynamics and surface stiffness and position, an adaptive jacobian controller is devised. the convergence of the force and position tracking errors is proved based on lyapunov stability analysis. numerical simulation is presented to show the performance of the controller.
repetitive motion of redundant robots planned by three kinds of recurrent neural networks and illustrated with a four-link planar manipulator's straight-line example. in this paper, a dual neural network, lvi (linear variational inequalities)-based primal-dual neural network and simplified lvi-based primal-dual neural network are presented for online repetitive motion planning (rmp) of redundant robot manipulators (with a four-link planar manipulator as an example). to do this, a drift-free criterion is exploited in the form of a quadratic performance index. in addition, the repetitive-motion-planning scheme could incorporate the joint physical limits such as joint limits and joint velocity limits simultaneously. such a scheme is finally reformulated as a quadratic program (qp). as qp real-time solvers, the aforementioned three kinds of neural networks all have piecewise-linear dynamics and could globally exponentially converge to the optimal solution of strictly-convex quadratic-programs. furthermore, the neural-network based rmp scheme is simulated based on a four-link planar robot manipulator. computer-simulation results substantiate the theoretical analysis and also show the effective remedy of the joint angle drift problem of robot manipulators.
collaborative coverage using a swarm of networked miniature robots. we study distributed coverage of environments with unknown extension using a team of networked miniature robots analytically and experimentally. algorithms are analyzed by incrementally raising the abstraction level starting from physical robots, to realistic and discrete event system (des) simulation. the realistic simulation is calibrated using sensor and actuator noise characteristics of the real platform and serves for calibration of the des microscopic model. the proposed algorithm is robust to positional noise and communication loss, and its performance gracefully degrades for communication and localization failures to a lower bound, which is given by the performance of a non-coordinated, randomized solution. results are validated by real robot experiments with miniature robots of a size smaller than 2 cmx2 cmx3 cm in a boundary coverage case study. trade-offs between the abilities of the individual platform, required communication, and algorithmic performance are discussed.
observer-based dynamic walking control for biped robots. this article presents a novel observer-based control system to achieve reactive motion generation for dynamic biped walking. the proposed approach combines a feedback controller with an online generated feet pattern to assure a stable gait. using the desired speed of the robot, a preview control system derives the dynamics of the robot's body, and thereby the trajectory of its center of mass, to ensure a zero moment point (zmp) movement, which results in a stable execution of the calculated step pattern. extending the control system by an observer, based on this knowledge and the measured sensor values, compensates for errors in the model parameters and disturbances encountering while walking.
toward a human-like biped robot with compliant legs. conventional models of bipedal walking generally assume rigid body structures, while elastic material properties seem to play an essential role in nature. on the basis of a novel theoretical model of bipedal walking, this paper investigates a model of biped robot which makes use of minimum control and elastic passive joints inspired from the structures of biological systems. the model is evaluated in simulation and a physical robotic platform by analyzing the kinematics and ground reaction force. the experimental results show that, with a proper leg design of passive dynamics and elasticity, an attractor state of human-like walking gait patterns can be achieved through extremely simple control without sensory feedback. the detailed analysis also explains how the dynamic human-like gait can contribute to adaptive biped walking.
conflict-free scheduling and routing of automated guided vehicles in mesh topologies. many storing and manufacturing systems tend to use automated guided vehicles (agv) for speed, quality and safety as transporting objects. in this paper an integrated algorithm for scheduling and routing of agvs in mesh-like systems is presented. the main characteristics of the scheduling algorithm are as follows: (1) prediction and prevention of conflicts, (2) arbitrary choice for agvs to traverse shortest path from source to destination, (3) effect of priority policies to the scheduling result, and (4) no theoretical limitation on the number of participated agvs. the proposed greedy algorithm for routing reduces the average number of conflicts and is closely related to the scheduling algorithm. we will also present mathematical and statistical models for the analysis of the algorithms.
optimization of grasping forces in handling of brittle objects. this paper deals with the optimization of grasping brittle objects with a multi-fingered robot hand under general constraints such as finger deformability and object positioning tolerances. first, a general formulation describing hyperstatic grasping is presented. then an optimization criterion based on the minimization of squeezing forces and torques is introduced. and finally results of numerical simulation for grasping with a special three-fingered gripper are presented.
timed trajectory generation using dynamical systems: application to a puma arm. we present an attractor based dynamics that autonomously generates trajectories with stable timing (limit cycle solutions), stably adapted to changing online sensory information. autonomous differential equations are used to formulate a dynamical layer with either stable fixed points or a stable limit cycle. a neural competitive dynamics switches between these two regimes according to sensorial context and logical conditions. the corresponding movement states are then converted by simple coordinate transformations and an inverse kinematics controller into spatial positions of a robot arm. movement initiation and termination is entirely sensor driven. in this article, the dynamic architecture was changed in order to cope with unreliable sensor information by including this information in the vector field. we apply this architecture to generate timed trajectories for a puma arm which must catch a moving ball before it falls over a table, and return to a reference position thereafter. sensory information is provided by a camera mounted on the ceiling over the robot. a flexible behavior is achieved. flexibility means that if the sensorial context changes such that the previously generated sequence is no longer adequate, a new sequence of behaviors, depending on the point at which the changed occurred and adequate to the current situation emerges. the evaluation results illustrate the stability and flexibility properties of the dynamical architecture as well as the robustness of the decision-making mechanism implemented.
singularity avoidance for acrobots based on fuzzy-control strategy. this paper presents a fuzzy-control method for the motion control of an acrobot. first, an explanation is given of the singularity that arises when a motion control law based on a lyapunov function has an integrated control objective for energy and posture. then, a fuzzy controller is designed that solves the singularity problem through regulation of a design parameter in the control law. finally, an additional fuzzy controller is designed that improves the control performance through regulation of another design parameter in the control law. simulation results demonstrate the effectiveness of this integrated fuzzy-control strategy.
robot motion description and real-time management with the harmonic motion description protocol. we describe the harmonic motion description protocol (hmdp), that can serve as a part in tools for rapid prototyping of behaviors in a hybrid simulation real robot environment. in particular, we are focusing on the robocup 3d soccer simulation league server that is currently evolving rapidly, and becomes a more and more useful open source, general purpose simulation environment for physical multiagent systems. hmdp uses harmonic functions to describe motions. it allows for superposition of motions and is therefore capable of describing parametric motions. thus, typical open loop motions (walking on spot, forward, turning, standing up) of small humanoid robots are readily available and can be optimized by hand. in conjunction with the hmdp some software tools and a small real-time motion generator (called motion machine) have been developed. the current implementation is very flexible to use and can easily be implemented in rather small embedded systems.
strategy of approach for seizure of an assistive mobile manipulator. in assistive robotics, a manipulator arm constitutes one possible solution for restoring some manipulation functions to victims of upper limb disabilities. the aim of this paper is to present a global strategy of approach of an assistive mobile manipulator (manipulator arm mounted on a mobile base). a manipulability criterion is defined to deal with the redundancy of the system. the aim is to keep the arm manipulable, i.e. capable of moving by itself. the strategy is based on human-like behaviour to help the disabled operator to understand the action of the robot. when the robot is far from its objective, only the mobile base moves, thus avoiding obstacles if necessary. when the objective is close to the robot, both mobile base and arm move and redundancy can be used to maximise a manipulability criterion. all the situations are tested separately and a global mission is realised in which all the previous situations are encountered. the partial results obtained with the real robot consolidate the results of simulation. this paper does not propose an autonomous path planning and navigation of the mobile arm but an assistance to the user for remote controlling it.
probabilistic instantaneous model-based signal processing applied to localization and tracking. in this paper, a probabilistic approach for estimating time and space-variant parameters of a system, based on sequentially received discrete-time signal values, is presented. the system description is the solution of a linear partial differential equation (pde). the pde describes for example the wave propagation of an acoustic wave in a localization system. the solution of the pde is given by a time-variant and space-variant impulse response. this impulse response is characterized by the time and space-variant parameters in order to track an object, which emits for example an acoustic signal. for estimating the position of the object in an instantaneous way a bayesian approach has to be used, which considers the dynamic behavior of the parameters in a system model and uncertainties in a stochastic manner by means of probability density functions. hence, the new approach provides a probabilistic instantaneous model-based signal processing, where the sequentially measured signal values are processed directly and known reference signal sequences are interpreted as part of a time-variant nonlinear measurement equation.
multi-robot task allocation through vacancy chain scheduling. modeling the effects of robot interaction in multi-robot systems, i.e., the group dynamics, is difficult due to the complexity of such interactions. this article formalizes the concept of group dynamics in the framework of scheduling and presents a proof that multi-robot task allocation (mrta), in systems with significant performance effects from group dynamics, is an np-complete problem. as a way of dealing with this complexity we have developed vacancy chain scheduling (vcs), a new formal model of mrta inspired by a resource distribution process commonly found in nature. vcs is also the foundation of a new mrta algorithm which relies on optimal allocation patterns to emerge from the stigmergic effects of robot interactions. we present experimental evidence of the validity of the vcs model from high-fidelity simulations. the experimental results validate the vcs model by reliably producing the predicted allocation patterns in both homogeneous and heterogeneous groups of robots. the evidence also supports our claim that vcs is a feasible solution for a restricted class of mrta problems.
coordinated pursuer control using particle filters for autonomous search-and-capture. in a real-world pursuit-evasion (pe) game, the pursuers often have a limited field-of-view of the evaders and thus are required to search for and detect the evaders before capturing them. this paper presents a unified framework and control algorithm using particle filters (pfs) for the coordination of multiple pursuers to search for and capture multiple evaders given the ability of pf to estimate highly non-gaussian densities prevalent in search problems. the pursuer control problem is formulated as a stochastic control problem where global objectives function of both searching and capturing are common. to take the evaders' actions into account, an action measure (am) is defined over the evaders' pds is used to represent the probability that the evader may transit each state in the pd. the global objective functions for search and capture are then decomposed into local objective functions for unification through objective priority weights. coordination between the pursuers takes place through the multi-sensor update where the observation likelihoods of all pursuers are used in the pf update stage. the control actions of each pursuer are then determined individually, based on the updated pds given the objective weights, action measures as well as evader importance weights in the case of multiple evaders. the proposed algorithm is tested in three scenarios for its effectiveness. in addition, a parametric study on the average capture time against the initial variances of the target state uncertainty is conducted to test for robustness. results show that the pursuers are able to capture all the evaders in each case with the capture time for the second and last scenario differing by only 2.9% implying firstly that under the proposed algorithm, the capture time is not proportional to the increase in the number of evaders and also suggested robustness and potential scalability of the proposed algorithm.
two-time scale control and observer design for trajectory tracking of two cooperating robot manipulators moving a flexible beam. in this paper, we present two-time scale control design for trajectory tracking of two cooperating planar rigid robots moving a flexible beam, which does not require vibration measurement for the beam. first, the kinematics and dynamics of the robots and the object are derived. then, using the relations between different forces acting on the object by the manipulators' end-effectors, dynamics equations of the robots and the object are combined. the resulting equations show that the coupled dynamics including beam vibration and the rigid motion take place in two different time domains. by applying two-time scale control theory on the combined dynamics, a composite control scheme is elaborated which makes the beam orientation and its center of mass position track a desired trajectory while suppressing the beam vibration. for the controller algorithm, first a slow controller is utilized for the slow (rigid) subsystem and then a fast stabilizing controller is considered for the fast (flexible) subsystem. to avoid requiring measurement of beam vibration for the fast control law, a linear observer is also designed. the simulation results show the efficiency of the proposed control scheme.
self-calibrated visual servoing with respect to axial-symmetric 3d objects. a self-calibrated approach to visual servoing with respect to non-planar targets modeled through a pair of coaxial circles plus one point is discussed. full calibration data (fixed internal parameters) are obtained from two views, and used to recover the euclidean structure of an auxiliary virtual plane associated to the target, together with the relative pose of the camera. pose disambiguation is achieved without requiring any real third view of the target. the approach benefits of an off-line planning strategy by which the camera follows a 3d helicoidal path around an arbitrarily chosen axis. a convenient choice for the helicoidal axis is found to be that of the target axis itself. simulation results demonstrate that the approach is robust with respect to noise both in the off-line and on-line control phases.
comparison of different gaits with rotation of the feet for a planar biped. fast human walking includes a phase where the stance heel rises from the ground and the stance foot rotates about the stance toe. this phase where the biped becomes under-actuated is not present during the walk of humanoid robots. the objective of this study is to determine if this phase is useful to reduce the energy consumed in the walking. in order to study the efficiency of this phase, six cyclic gaits are presented for a planar biped robot. the simplest cyclic motion is composed of successive single support phases with flat stance foot on the ground. the most complex cyclic motion is composed of single support phases that include a sub-phase of rotation of the stance foot about the toe and of finite time double support phase. for the synthesis of these walking gaits, optimal motions with respect to the torque cost, are defined by taking into account given performances of actuators. it is shown that for fast motions a foot rotation sub-phase is useful to reduce the criteria cost. in the optimization process, under-actuated phase (foot rotation phase), fully-actuated phase (flat foot phase) and over-actuated phase (double support phase) are considered.
autonomous collaborative environment for project-based learning. the importance of integrating different disciplines of information science and technology is growing for the realization of an information system which works robustly in the real world. such a system should be achieved by integrating different disciplines, since it is difficult to cover all areas in information science and technology by only one person or group. in order to support collaboration, the autonomous collaborative environment for project- based learning was developed. the environment comprises the workshop ''a hundred hour workshop'' and the community site ''ws100h.net''. novel interdisciplinary technology, fusion of recognition and parallel computation was successfully developed whose collaboration process was autonomous.
fitness functions in evolutionary robotics: a survey and analysis. this paper surveys fitness functions used in the field of evolutionary robotics (er). evolutionary robotics is a field of research that applies artificial evolution to generate control systems for autonomous robots. during evolution, robots attempt to perform a given task in a given environment. the controllers in the better performing robots are selected, altered and propagated to perform the task again in an iterative process that mimics some aspects of natural evolution. a key component of this process-one might argue, the key component-is the measurement of fitness in the evolving controllers. er is one of a host of machine learning methods that rely on interaction with, and feedback from, a complex dynamic environment to drive synthesis of controllers for autonomous agents. these methods have the potential to lead to the development of robots that can adapt to uncharacterized environments and which may be able to perform tasks that human designers do not completely understand. in order to achieve this, issues regarding fitness evaluation must be addressed. in this paper we survey current er research and focus on work that involved real robots. the surveyed research is organized according to the degree of a priori knowledge used to formulate the various fitness functions employed during evolution. the underlying motivation for this is to identify methods that allow the development of the greatest degree of novel control, while requiring the minimum amount of a priori task knowledge from the designer.
control and simulation of a tensegrity-based mobile robot. tensegrity structures can provide a new approach to the construction of mobile robots with different shapes and properties that usual robots, wheeled or legged, do not have. tensegrity are light, deformable structures that may be able to adapt their form to unconstrained environments. the main issue of this paper is twofold, first, to derive appropriate and general dynamic equations of motion to study the movement of such structures in the space; second to demonstrate, by means of simulation, that a tensegrity structure can execute any desired trajectory path by actuating some or all of its elements.