waashk/dblp huggingface dataset:
performing aggressive maneuvers using iterative learning control. this paper presents an algorithm to iteratively drive a system quickly from one state to another. a simple model which captures the essential features of the system is used to compute the reference trajectory as the solution of an optimal control problem. based on a lifted domain description of that same model an iterative learning controller is synthesized by solving a linear least-squares problem. the non-causality of the approach makes it possible to anticipate recurring disturbances. computational requirements are modest, allowing controller update in real-time. the experience gained from successful maneuvers can be used to significantly reduce transients when performing similar motions. the algorithm is successfully applied to a real quadrotor unmanned aerial vehicle. the results are presented and discussed.
laser-based navigation enhanced with 3d time-of-flight data. navigation and obstacle avoidance in robotics using planar laser scans has matured over the last decades. they basically enable robots to penetrate highly dynamic and populated spaces, such as people's home, and move around smoothly. however, in an unconstrained environment the two-dimensional perceptual space of a fixed mounted laser is not sufficient to ensure safe navigation. in this paper, we present an approach that pools a fast and reliable motion generation approach with modern 3d capturing techniques using a time-of-flight camera. instead of attempting to implement full 3d motion control, which is computationally more expensive and simply not needed for the targeted scenario of a domestic robot, we introduce a "virtual laser". for the originally solely laserbased motion generation the technique of fusing real laser measurements and 3d point clouds into a continuous data stream is 100% compatible and transparent. the paper covers the general concept, the necessary extrinsic calibration of two very different types of sensors, and exemplarily illustrates the benefit which is to avoid obstacles not being perceivable in the original laser scan.
helios carrier: tail-like mechanism and control algorithm for stable motion in unknown environments. mobile platforms when negotiating steps and stairs should be able to control theirs posture in order to avoid sudden tilting or falls. in particular, when considering applications for search and rescue operations where users have a very limited time of operation, the motion on stairs should be automated as much as possible. in this way operators can concentrate on their tasks (i.e. search of survivors and/or exploration of dangerous environments) rather than having to focus on the stability of the vehicle. a simple but very effective mechanism called "tail" is introduced. the mechanical design and its control method is presented together with several tests and experiments carried out with a simple tracked vehicle in real environments.
hand & eye-vergence dual visual servoing to enhance observability and stability. in this paper, we propose a new two-way visual servoing method, named as hand & eye-vergence visual servoing. this idea stems from animal's evolution history, predator have evolved their eye positions to be at the front face and their eyes turn to gaze at the target prey to be suited to triangulation, enhancing the ability to measure precisely the distance to the prey for catching it. this animal's visual tracking includes motion control by visual servoing and triangular eye vergence. our proposed method includes two loops: an outer loop for conventional visual servoing that direct a manipulator toward a target object and an inner loop for active motion of binocular camera for accurate and broad observation of the target object. the effectiveness of the hand & eye-vergence visual servoing is evaluated through simulations incorporated with actual dynamics of 7-dof robot on the view points of how the new idea improved the stability in visual servoing dynamics and the accuracy of hand pose.
flocking control of a mobile sensor network to track and observe a moving target. this paper presents a new approach to flocking control of a mobile sensor network to track a moving target. in our approach, the center of mass (com) of positions and velocities of all mobile sensors in the network (single-com) or the center of mass of position and velocity of each sensor and its neighbors (multi-com) is controlled to track and observe a moving target. in addition, we prove that the com of position and velocity exponentially converges to the moving target in free space. based on this approach, the target is kept at the center of the sensor network. this is of great advantage for sensors to track and observe the target for recognition or identification purposes. in addition, collision-free and velocity matching among mobile sensors are guaranteed in the whole process of the target tracking. we also investigate the stability of our algorithms. the numerical simulations are performed to demonstrate the proposed approach.
a numerical method for choosing motions with optimal excitation properties for identification of biped dynamics - an application to human. identification results dramatically depend on the excitation properties of the motion used to sample the identification model. strategies to define persistent exciting trajectories have been developed for manipulator robots with few dof. however they can not easily be extended to humanoid systems and humans due to the important number of dof; and empirical knowledge is often used to generate and select persistent exciting motions. in this paper we propose a method to choose persistent exciting motions from an existing dataset in order to optimize both the identification results and the computation time. this method is based on the use of the identification model of legged systems obtained from the base-link equations. instead of using well-established consideration on the condition number of the regressor matrix, the method uses a decomposition of the regressor into elementary subregressors and the computation of the condition number for each. a selection rule is then proposed. the overall method is experimentally tested to identify the human body inertial parameters using a data-set of 40 motions. comparative results obtained from different combinations of motions are given.
mixed reality simulation for mobile robots. mobile robots are increasingly entering the real and complex world of humans in ways that necessitate a high degree of interaction and cooperation between human and robot. complex simulation models, expensive hardware setup, and a highly controlled environment are often required during various stages of robot development. there is a need for robot developers to have a more flexible approach for conducting experiments and to obtain a better understanding of how robots perceive the world. mixed reality (mr) presents a world where real and virtual elements co-exist. by merging the real and the virtual in the creation of an mr simulation environment, more insight into the robot behaviour can be gained, e.g. internal robot information can be visualised, and cheaper and safer testing scenarios can be created by making interactions between physical and virtual objects possible. robot developers are free to introduce virtual objects in an mr simulation environment for evaluating their systems and obtain a coherent display of visual feedback and realistic simulation results. we illustrate our ideas using an mr simulation tool constructed based on the 3d robot simulator gazebo.
experiments with a zigbee wireless communication system for self-reconfiguring modular robots. the problem of designing reliable low-cost communications systems to support decentralized algorithms is a major research challenge in self-reconfiguring modular robotics. in this paper we evaluate a communication system based on zigbee, a wireless ad-hoc mesh networking standard. we present a 15-node system prototype and results from an experiment of 300 trials that measures system performance on a benchmark task. the benchmark we chose is the connectivity problem - how to maintain connectivity in the module graph during the disconnections and reconnections that occur during reconfiguration. we also provide full implementation details in pseudocode for our connectivity algorithm. our results show that, despite its inherent scalability limitations, a zigbee wireless system is feasible as a simple, low-cost communication system for self-reconfiguring modular robots.
reachability-guided sampling for planning under differential constraints. rapidly-exploring random trees (rrts) are widely used to solve large planning problems where the scope prohibits the feasibility of deterministic solvers, but the efficiency of these algorithms can be severely compromised in the presence of certain kinodynamics constraints. obstacle fields with tunnels, or tubes are notoriously difficult, as are systems with differential constraints, because the tree grows inefficiently at the boundaries. here we present a new sampling strategy for the rrt algorithm, based on an estimated feasibility set, which affords a dramatic improvement in performance in these severely constrained systems. we demonstrate the algorithm with a detailed look at the expansion of an rrt in a swingup task, and on path planning for a nonholonomic car.
a riemannian-geometry approach for dynamics and control of object manipulation under constraints. a riemannian-geometry approach for control and stabilization of dynamics of object manipulation under holonomic or non-holonomic (but pfaffian) constraints is presented. first, position/force hybrid control of an endeffector of a multijoint redundant (or nonredundant) robot under a nonholonomic constraint is reinterpreted in terms of "submersion" in riemannian geometry. a force control signal constructed in the image space spanned from the constraint gradient can be regarded as a lifting in the direction orthogonal to the kernel space. by means of the riemannian distance on the constraint submanifold, stability on a manifold for a redundant system under holonomic constraints is discussed. second, control and stabilization of dynamics of two-dimensional object grasping and manipulation by using a pair of multi-joint robot fingers are tackled, when a rigid object is given with arbitrary shape. then, it is shown that rolling contact constraint induce the euler equation of motion in an implicit function form, in which constraint forces appear as wrench vectors affecting on the object. the riemannian metric can be introduced in a natural way on a constraint submanifold induced by rolling contacts. a control signal called "blind grasping" is defined and shown to be effective in stabilization of grasping without using the details of information of object shape and parameters or external sensing. the concept of stability of the closed-loop system under constraints is renewed in order to overcome the degrees-of-freedom redundancy problem. an extension of dirichlet-lagrange's stability theorem to a system of dof-redundancy under constraints is presented by using a morse-lyapunov function.
probabilistic action planning for active scene modeling in continuous high-dimensional domains. in active perception systems for scene recognition the utility of an observation is determined by the information gain in the probability distribution over the state space. the goal is to find a sequence of actions which maximizes the system knowledge at low resource costs. most current approaches focus either on optimizing the determination of the payoff neglecting the costs or develop sophisticated planning strategies for simple reward models. this paper presents a probabilistic framework which provides an approach for sequential decision making under model and state uncertainties in continuous and high-dimensional domains. the probabilistic planner, realized as a partially observable markov decision process (pomdp), reasons by considering both, information theoretic quality criteria of probability distributions and control action costs. in an experimental setting an autonomous service robot uses active perception techniques for efficient object recognition in complex multi-object scenarios, facing the difficulties of object occlusion. due to the high demand on real time applicability the probability distributions are represented by mixtures of gaussian to allow fast, parametric computation.
encoding molecular motions in voxel maps. understanding life at the atomic level requires the development of new methodologies, able to overcome the limitations of available experimental and computational techniques for the analysis of processes involving molecular motions. with this goal in mind, we develop new methods, combining robotic path planning algorithms and molecular modeling techniques, for computing large-amplitude motions. this paper builds on these new methods, and introduces voxel maps as a computational tool to encode and to represent such motions. voxel maps can be used to represent relative motions of two molecules, as well as conformational changes in macromolecules. we investigate several applications and show results that illustrate the interest of such representation. in particular, voxel maps are used to display channels into proteins, to analyze protein-ligand specificity, and to represents protein loop and domain motions.
mechatronic design of a fast and long range 4 degrees of freedom humanoid neck. this paper describes the mechatronic design of a humanoid neck. to research human machine interaction, the head and neck combination should be able to approach the human behavior as much as possible. we present a novel humanoid neck concept that is both fast, and has a long range of motion in 4 degrees of freedom (dofs). this enables the head to track fast objects, and the neck design is suitable for mimicking expressions. the humanoid neck features a differential drive design for the lower 2 dofs resulting in a low moving mass and the ability to use strong actuators. the performance of the neck has been optimized by minimizing backlash in the mechanisms, and by using gravity compensation. two cameras in the head are used for scanning and interaction with the environment.
safe longitudinal platoons of vehicles without communication. this paper deals with the platooning problem that can be defined as the automatic following of a manned driven vehicle by a convoy of automatic ones. different approaches have been proposed so far. some require the localisation of each vehicle and a communication infrastructure, others called near-to-near approach only needs vehicle on-board sensors. however, to our knowledge, they do not provide any proof of non collision. we propose a novel near-to-near longitudinal platooning building a collision-free platooning whatever the number of vehicles. the model is derived from the study of the most dangerous interaction between two vehicles, i.e. considering the maximum acceptable acceleration when the previous vehicles brakes at maximum capacity. collision avoidance of this model is proved. finally, we show that this model can be combined to existing ones, keeping this collision-free property while allowing more various behaviors.
nonlinear, large-strain pzt actuators using controlled structural buckling. buckling is a highly nonlinear and singular phenomenon in thin beams, and is usually an undesired characteristic that must be prevented from occurring in engineered systems. buckling, however, can be a useful mechanism for gaining extremely large displacement amplification, since a tiny displacement in the axial direction of the beam may lead to a large defection in the middle of the beam. this paper presents a novel large-strain piezoelectric actuator exploiting the buckling of a structure with imbedded pzt stacks. although the free displacement of a pzt stack is only 0.1% of the stack length, the buckling mechanism, controlled with an effective algorithm and strategically placed redirecting stiffness, can produce a large bi-polar displacement that is approximately 150 times larger than the original pzt displacement. furthermore, the structural buckling produces a pronounced nonlinearity in output impedance; the effective stiffness viewed from the output port varies as a function of output displacement, which can be a useful property for those applications where actuator stiffness needs to vary.
a stochastically stable solution to the problem of robocentric mapping. this paper provides a novel solution for robocentric mapping using an autonomous mobile robot. the robot dynamic model is the standard unicycle model and the robot is assumed to measure both the range and relative bearing to the landmarks. the algorithm introduced in this paper relies on a coordinate transformation and an extended kalman filter like algorithm. the coordinate transformation considered in this paper has not been previously considered for robocentric mapping applications. moreover, we provide a rigorous stochastic stability analysis of the filter employed and we examine the conditions under which the mean-square estimation error converges to a steady-state value.
motion planning for a golf swing robot based on reverse time symmetry and pgctc control. a new golf swing robot performing high-speed golf swings has been developed by the authors. this paper deals with the motion planning problem of the golf swing. at first, the reverse time symmetry and single pendulum inherences in manipulator dynamics are introduced. then, by utilizing the first inherence, the rest-to-point motion planning problem for the backswing and downswing is transformed into a reverse time symmetric point-to-rest motion planning problem. finally, based on the second inherence, a proportional plus gravity and coupling torque compensation (pgctc) control scheme is developed to solve both the reverse time symmetric point-to-rest motion planning problem for the backswing and downswing and the forward time point-to-rest problem for the follow-through. simulation shows the effect of the proposed method.
development of a prosthetic arm: experimental validation with the user and an adapted software. in the world of upper limb prostheses, few companies propose different kinds of hand, wrist and elbow prostheses but their control is often difficult to understand by the patients. we have decided to develop new myoelectric prosthetic arm (elbow, wrist and hand) by axing our development on the use of new technologies and user centered design methodology. in this paper, we are explaining the different kinds of prostheses currently manufactured their advantages and their drawbacks. then, we explain our designing choices of the prosthesis and the movements it can realize. we detail the control chosen to simplify the use and the instrument of the product by the patient. in the last part, an adapted software is developed and used to validate experimentally the practice by the patient.
mouth gesture and voice command based robot command interface. in this paper we present a voice command and mouth gesture based robot command interface which is capable of controlling three degrees of freedom. the gesture set was designed in order to avoid head rotation and translation, and thus relying solely in mouth movements. mouth segmentation is performed by using the normalized a* component, as in [1]. the gesture detection process is carried out by a gaussian mixture model (gmm) based classifier. after that, a state machine stabilizes the system response by restricting the number of possible movements depending on the initial state. voice commands are modeled using a hidden markov model (hmm) isolated word recognition scheme. the interface was designed taking into account the specific pose restrictions found in the davinci assisted surgery command console.
dynamic stability of variable stiffness running. humans and animals adapt their leg impedance during running for both internal (e.g. loading) and external (e.g. surface) changes. in this paper we examine the relationship between leg stiffness and the speed and stability of dynamic legged locomotion. we utilize a torque-driven reduced-order model of running based on a successful family of running robots to show how optimal clock-driven controllers can interact with variably compliant limbs to adapt to changing operating conditions. we show that the leg stiffness adaptation gives, in general, better results than simply optimizing the gait controller and nearly as good as the co-optimization of controller and leg stiffness.
collision avoidance in dynamic environments: an ics-based solution and its comparative evaluation. this paper presents ics-avoid, a collision avoidance scheme based upon the concept of inevitable collision state (ics), ie a state for which, no matter what the future trajectory of the robotic system is, a collision eventually occurs. by design, ics-avoid can handle dynamic environments since ics do take into account the future behaviour of moving objects. ics-avoid is designed to keep the system away from ics. by doing so, motion safety is guranteed (by definition a robotic system in a non-ics state has at least one collision-free trajectory that it can use). to demonstrate the efficiency of ics-avoid, it has been extensively compared with two state-of-the-art collision avoidance schemes: the first one is built upon the dynamic window approach and the second one on the velocity obstacle concept. the results obtained show that, when provided with the same amount of information about the future evolution of the environment, ics-avoid outperforms the other two schemes. the first reason for this has to do with the extent to which each collision avoidance scheme reasons about the future. the second reason has to do with the ability of each collision avoidance scheme to find a safe control if one exists. ics-avoid is the only one which is complete in this respect thanks to the concept of safe control kernel.
localization with multi-modal vision measurements in limited gps environments using gaussian sum filters. a gaussian sum filter (gsf) with component extended kalman filters (ekf) is proposed as an approach to localize an autonomous vehicle in an urban environment with limited gps availability. the gsf uses vehicle relative vision-based measurements of known map features coupled with inertial navigation solutions to accomplish localization in the absence of gps. the vision-based measurements are shown to have multi-modal measurement likelihood functions that are well represented as a weighted sum of gaussian densities and the gsf is ideally suited to accomplish recursive bayesian state estimation for this problem. a sequential merging technique is used for gaussian mixture condensation in the posterior density approximation after fusing multi-modal measurements in the gsf to maintain mixture size over time. the representation of the posterior density with the gsf is compared over a common dataset against a benchmark particle filter solution. the expectation-maximization (em) algorithm is used offline to determine the representational efficiency of the particle filter in terms of an effective number of gaussian densities. the gsf with vision-based vehicle relative measurements is shown to remain converged using 37 minutes of recorded data from the cornell university darpa urban challenge (duc) autonomous vehicle in an urban environment that includes a 32 minute gps blackout.