scispace - formally typeset
Search or ask a question

Showing papers in "IEEE Transactions on Robotics in 2012"


Journal ArticleDOI
TL;DR: A vocabulary tree is built that discretizes a binary descriptor space and uses the tree to speed up correspondences for geometrical verification, and presents competitive results with no false positives in very different datasets.
Abstract: We propose a novel method for visual place recognition using bag of words obtained from accelerated segment test (FAST)+BRIEF features. For the first time, we build a vocabulary tree that discretizes a binary descriptor space and use the tree to speed up correspondences for geometrical verification. We present competitive results with no false positives in very different datasets, using exactly the same vocabulary and settings. The whole technique, including feature extraction, requires 22 ms/frame in a sequence with 26 300 images that is one order of magnitude faster than previous approaches.

1,560 citations


Journal ArticleDOI
TL;DR: A simple passive universal gripper, consisting of a mass of granular material encased in an elastic membrane, that can rapidly grip and release a wide range of objects that are typically challenging for universal grippers, such as flat objects, soft objects, or objects with complex geometries is described.
Abstract: We describe a simple passive universal gripper, consisting of a mass of granular material encased in an elastic membrane. Using a combination of positive and negative pressure, the gripper can rapidly grip and release a wide range of objects that are typically challenging for universal grippers, such as flat objects, soft objects, or objects with complex geometries. The gripper passively conforms to the shape of a target object, then vacuum-hardens to grip it rigidly, later utilizing positive pressure to reverse this transition-releasing the object and returning to a deformable state. We describe the mechanical design and implementation of this gripper and quantify its performance in real-world testing situations. By using both positive and negative pressure, we demonstrate performance increases of up to 85% in reliability, 25% in error tolerance, and the added capability to shoot objects by fast ejection. In addition, multiple objects are gripped and placed at once while maintaining their relative distance and orientation. We conclude by comparing the performance of the proposed gripper with others in the field.

574 citations


Journal ArticleDOI
TL;DR: A novel method to fuse observations from an inertial measurement unit (IMU) and visual sensors, such that initial conditions of the inertial integration can be recovered quickly and in a linear manner, thus removing any need for special initialization procedures.
Abstract: In this paper, we present a novel method to fuse observations from an inertial measurement unit (IMU) and visual sensors, such that initial conditions of the inertial integration, including gravity estimation, can be recovered quickly and in a linear manner, thus removing any need for special initialization procedures. The algorithm is implemented using a graphical simultaneous localization and mapping like approach that guarantees constant time output. This paper discusses the technical aspects of the work, including observability and the ability for the system to estimate scale in real time. Results are presented of the system, estimating the platforms position, velocity, and attitude, as well as gravity vector and sensor alignment and calibration on-line in a built environment. This paper discusses the system setup, describing the real-time integration of the IMU data with either stereo or monocular vision data. We focus on human motion for the purposes of emulating high-dynamic motion, as well as to provide a localization system for future human-robot interaction.

415 citations


Journal ArticleDOI
TL;DR: The results demonstrate that the six-degree-of-freedom trajectory of a passive spring-mounted range sensor can be accurately estimated from laser range data and industrial-grade inertial measurements in real time and that a quality 3-D point cloud map can be generated concurrently using the same data.
Abstract: Three-dimensional perception is a key technology for many robotics applications, including obstacle detection, mapping, and localization. There exist a number of sensors and techniques for acquiring 3-D data, many of which have particular utility for various robotic tasks. We introduce a new design for a 3-D sensor system, constructed from a 2-D range scanner coupled with a passive linkage mechanism, such as a spring. By mounting the other end of the passive linkage mechanism to a moving body, disturbances resulting from accelerations and vibrations of the body propel the 2-D scanner in an irregular fashion, thereby extending the device's field of view outside of its standard scanning plane. The proposed 3-D sensor system is advantageous due to its mechanical simplicity, mobility, low weight, and relatively low cost. We analyze a particular implementation of the proposed device, which we call Zebedee, consisting of a 2-D time-of-flight laser range scanner rigidly coupled to an inertial measurement unit and mounted on a spring. The unique configuration of the sensor system motivates unconventional and specialized algorithms to be developed for data processing. As an example application, we describe a novel 3-D simultaneous localization and mapping solution in which Zebedee is mounted on a moving platform. Using a motion capture system, we have verified the positional accuracy of the sensor trajectory. The results demonstrate that the six-degree-of-freedom trajectory of a passive spring-mounted range sensor can be accurately estimated from laser range data and industrial-grade inertial measurements in real time and that a quality 3-D point cloud map can be generated concurrently using the same data.

402 citations


Journal ArticleDOI
TL;DR: This paper presents a general navigation system that enables a small-sized quadrotor system to autonomously operate in indoor environments and systematically extend and adapt techniques that have been successfully applied on ground robots.
Abstract: Recently, there has been increased interest in the development of autonomous flying vehicles. However, as most of the proposed approaches are suitable for outdoor operation, only a few techniques have been designed for indoor environments, where the systems cannot rely on the Global Positioning System (GPS) and, therefore, have to use their exteroceptive sensors for navigation. In this paper, we present a general navigation system that enables a small-sized quadrotor system to autonomously operate in indoor environments. To achieve this, we systematically extend and adapt techniques that have been successfully applied on ground robots. We describe all algorithms and present a broad set of experiments, which illustrate that they enable a quadrotor robot to reliably and autonomously navigate in indoor environments.

397 citations


Journal ArticleDOI
TL;DR: This paper is the first to demonstrate via experiments with cable-driven arm exoskeleton (CAREX) that it is possible to achieve desired forces on the hand, i.e., both pull and push, in any direction as required in neural training.
Abstract: Rehabilitation robots are, currently, being explored for training of neural impaired subjects or for assistance of those with weak limbs. Intensive training of neurally impaired subjects, with quantifiable outcomes, is the eventual goal of these robot exoskeletons. Conventional arm exoskeletons for rehabilitation are bulky and heavy. In recent years, the authors have proposed to make lightweight exoskeletons for rehabilitation by replacing the rigid links of the exoskeleton with lightweight cuffs fixed to the moving limb segments of the human arm. Cables are routed through these cuffs, which are driven by motors, to move the limb segments relative to each other. However, a scientific limitation of a cable-driven system is that each cable can only pull but not push. This paper is the first to demonstrate via experiments with cable-driven arm exoskeleton (CAREX) that it is possible to achieve desired forces on the hand, i.e., both pull and push, in any direction as required in neural training. In this research, an anthropomorphic arm was used to bench test the design and control concepts proposed in CAREX. As described in this paper, CAREX was attached to the limb segments of a five degree-of-freedom anthropomorphic arm instrumented with joint sensors. The cuffs of CAREX were designed to have adjustable cable routing points to optimize the “tensioned” workspace of the anthropomorphic arm. Simulation results of force field for training and rehabilitation of the arm are first presented. Experiments are conducted to show the performance of a CAREX force field controller when human subjects pull the end-effector of the anthropomorphic arm to travel on prescribed paths. The human-exoskeleton interface is also presented at the end of this paper to demonstrate the feasibility of CAREX on human arm.

332 citations


Journal ArticleDOI
TL;DR: A nonlinear controller for a vertical take-off and landing (VTOL) unmanned aerial vehicle (UAV) that exploits a measurement optical flow to enable hover and landing control on a moving platform, such as, for example, the deck of a sea-going vessel is presented.
Abstract: This paper presents a nonlinear controller for a vertical take-off and landing (VTOL) unmanned aerial vehicle (UAV) that exploits a measurement optical flow to enable hover and landing control on a moving platform, such as, for example, the deck of a sea-going vessel. The VTOL vehicle is assumed to be equipped with a minimum sensor suite [i.e., a camera and an inertial measurement unit (IMU)], manoeuvring over a textured flat target plane. Two different tasks are considered in this paper. The first concerns the stabilization of the vehicle relative to the moving platform that maintains a constant offset from a moving reference. The second concerns regulation of automatic vertical landing onto a moving platform. Rigorous analysis of system stability is provided, and simulations are presented. Experimental results are provided for a quadrotor UAV to demonstrate the performance of the proposed control strategy.

321 citations


Journal ArticleDOI
TL;DR: Design and fabrication methods for the compliant structures of the robot with its axial deformation and position control capability are presented and its feasibility is tested and verified on a synthetic stomach surface by using a magnetically actuated capsule endoscope prototype.
Abstract: This paper proposes a magnetically actuated soft capsule endoscope (MASCE) as a tetherless miniature mobile robot platform for diagnostic and therapeutic medical applications inside the stomach. Two embedded internal permanent magnets and a large external magnet are used to actuate the robot remotely. The proposed MASCE has three novel features. First, its outside body is made of soft elastomer-based compliant structures. Such compliant structures can deform passively during the robot-tissue contact interactions, which makes the device safer and less invasive. Next, it can be actively deformed in the axial direction by using external magnetic actuation, which provides an extra degree of freedom that enables various advanced functions such as axial position control, drug releasing, drug injection, or biopsy. Finally, it navigates in three dimensions by rolling on the stomach surface as a new surface locomotion method inside the stomach. Here, the external attractive magnetic force is used to anchor the robot on a desired location, and the external magnetic torque is used to roll it to another location, which provides a stable, continuous, and controllable motion. The paper presents design and fabrication methods for the compliant structures of the robot with its axial deformation and position control capability. Rolling-based surface locomotion of the robot using external magnetic torques is modeled, and its feasibility is tested and verified on a synthetic stomach surface by using a magnetically actuated capsule endoscope prototype.

298 citations


Journal ArticleDOI
TL;DR: This paper investigates the problem of vision and inertial data fusion with the introduction of a very simple and powerful new method that is able to simultaneously estimate all the observable modes with no need for any initialization or a priori knowledge.
Abstract: This paper investigates the problem of vision and inertial data fusion A sensor assembling that is constituted by one monocular camera, three orthogonal accelerometers, and three orthogonal gyroscopes is considered The first paper contribution is the analytical derivation of all the observable modes, ie, all the physical quantities that can be determined by only using the information in the sensor data that are acquired during a short time interval Specifically, the observable modes are the speed and attitude (roll and pitch angles), the absolute scale, and the biases that affect the inertial measurements This holds even in the case when the camera only observes a single point feature The analytical derivation of the aforementioned observable modes is based on a nonstandard observability analysis, which fully accounts for the system nonlinearities The second contribution is the analytical derivation of closed-form solutions, which analytically express all the aforementioned observable modes in terms of the visual and inertial measurements that are collected during a very short time interval This allows the introduction of a very simple and powerful new method that is able to simultaneously estimate all the observable modes with no need for any initialization or a priori knowledge Both the observability analysis and the derivation of the closed-form solutions are carried out in several different contexts, including the case of biased and unbiased inertial measurements, the case of a single and multiple features, and in the presence and absence of gravity In addition, in all these contexts, the minimum number of camera images that are necessary for the observability is derived The performance of the proposed approach is evaluated via extensive Monte Carlo simulations and real experiments

281 citations


Journal ArticleDOI
TL;DR: In this article, the authors present a set of controllers that enable mobile robots to persistently monitor or sweep a changing environment, where the speed of each robot along its path is controlled to prevent the field from growing unbounded at any location.
Abstract: In this paper, we present controllers that enable mobile robots to persistently monitor or sweep a changing environment. The environment is modeled as a field that is defined over a finite set of locations. The field grows linearly at locations that are not within the range of a robot and decreases linearly at locations that are within range of a robot. We assume that the robots travel on given closed paths. The speed of each robot along its path is controlled to prevent the field from growing unbounded at any location. We consider the space of speed controllers that are parametrized by a finite set of basis functions. For a single robot, we develop a linear program that computes a speed controller in this space to keep the field bounded, if such a controller exists. Another linear program is derived to compute the speed controller that minimizes the maximum field value over the environment. We extend our linear program formulation to develop a multirobot controller that keeps the field bounded. We characterize, both theoretically and in simulation, the robustness of the controllers to modeling errors and to stochasticity in the environment.

253 citations


Journal ArticleDOI
TL;DR: This work presents the automated design and manufacture of static and locomotion objects in which functionality is obtained purely by the unconstrained 3-D distribution of materials and suggests that this approach to design automation opens the door to leveraging the full potential of the freeform multimaterial design space to generate novel mechanisms and deformable robots.
Abstract: We present the automated design and manufacture of static and locomotion objects in which functionality is obtained purely by the unconstrained 3-D distribution of materials. Recent advances in multimaterial fabrication techniques enable continuous shapes to be fabricated with unprecedented fidelity unhindered by spatial constraints and homogeneous materials. We address the challenges of exploitation of the freedom of this vast new design space using evolutionary algorithms. We first show a set of cantilever beams automatically designed to deflect in arbitrary static profiles using hard and soft materials. These beams were automatically fabricated, and their physical performance was confirmed within 0.5-7.6% accuracy. We then demonstrate the automatic design of freeform soft robots for forward locomotion using soft volumetrically expanding actuator materials. One robot was fabricated automatically and assembled, and its performance was confirmed with 15% error. We suggest that this approach to design automation opens the door to leveraging the full potential of the freeform multimaterial design space to generate novel mechanisms and deformable robots.

Journal ArticleDOI
TL;DR: To approximately solve the stochastic dynamic programming problem that is associated with DUE planning, a partially closed-loop receding horizon control algorithm is presented whose solution integrates prediction, estimation, and planning while also accounting for chance constraints that arise from the uncertain locations of the robot and obstacles.
Abstract: This paper presents a strategy for planning robot motions in dynamic, uncertain environments (DUEs). Successful and efficient robot operation in such environments requires reasoning about the future evolution and uncertainties of the states of the moving agents and obstacles. A novel procedure to account for future information gathering (and the quality of that information) in the planning process is presented. To approximately solve the stochastic dynamic programming problem that is associated with DUE planning, we present a partially closed-loop receding horizon control algorithm whose solution integrates prediction, estimation, and planning while also accounting for chance constraints that arise from the uncertain locations of the robot and obstacles. Simulation results in simple static and dynamic scenarios illustrate the benefit of the algorithm over classical approaches. The approach is also applied to more complicated scenarios, including agents with complex, multimodal behaviors, basic robot-agent interaction, and agent information gathering.

Journal ArticleDOI
Minkyun Noh1, Seung-Won Kim1, Sung-Min An1, Je-Sung Koh1, Kyu-Jin Cho1 
TL;DR: A robotic design was created to realize the mechanism for the biological catapult with shape memory alloy (SMA) spring actuators and a smart composite microstructure that simulates a flea's leg kinematics with reduced degrees of freedom.
Abstract: Fleas can jump more than 200 times their body length. They do so by employing a unique catapult mechanism: storing a large amount of elastic energy and releasing it quickly by torque reversal triggering. This paper presents a flea-inspired catapult mechanism for miniature jumping robots. A robotic design was created to realize the mechanism for the biological catapult with shape memory alloy (SMA) spring actuators and a smart composite microstructure. SMA spring actuators replace conventional actuators, transmissions, and the elastic element to reduce the size. The body uses a four-bar mechanism that simulates a flea's leg kinematics with reduced degrees of freedom. Dynamic modeling was derived, and theoretical jumping was simulated to optimize the leg design for increased takeoff speed. A robotic prototype was fabricated with 1.1-g weight and 2-cm body size that can jump a distance of up to 30 times its body size.

Journal ArticleDOI
TL;DR: Applying simultaneous shape and goal learning to sequences of motion primitives leads to the novel algorithm PI2 Seq, which is used to address a fundamental challenge in manipulation: improving the robustness of everyday pick-and-place tasks.
Abstract: Physical contact events often allow a natural decomposition of manipulation tasks into action phases and subgoals. Within the motion primitive paradigm, each action phase corresponds to a motion primitive, and the subgoals correspond to the goal parameters of these primitives. Current state-of-the-art reinforcement learning algorithms are able to efficiently and robustly optimize the parameters of motion primitives in very high-dimensional problems. These algorithms often consider only shape parameters, which determine the trajectory between the start- and end-point of the movement. In manipulation, however, it is also crucial to optimize the goal parameters, which represent the subgoals between the motion primitives. We therefore extend the policy improvement with path integrals (PI2) algorithm to simultaneously optimize shape and goal parameters. Applying simultaneous shape and goal learning to sequences of motion primitives leads to the novel algorithm PI2 Seq. We use our methods to address a fundamental challenge in manipulation: improving the robustness of everyday pick-and-place tasks.

Journal ArticleDOI
TL;DR: A constructive method is derived that allows the determination of all the possible distributions of freed degrees of freedom across different fixation mechanisms and provides formal proofs of global isostaticity.
Abstract: When developing robotic exoskeletons, the design of physical connections between the device and the human limb to which it is connected is a crucial problem. Indeed, using an embedment at each connection point leads to uncontrollable forces at the interaction port, induced by hyperstaticity. In practice, these forces may be large because in general the human limb kinematics and the exoskeleton kinematics differ. To cope with hyperstaticity, the literature suggests the addition of passive mechanisms inside the mechanism loops. However, empirical solutions that are proposed so far lack proper analysis and generality. In this paper, we study the general problem of connecting two similar kinematic chains through multiple passive mechanisms. We derive a constructive method that allows the determination of all the possible distributions of freed degrees of freedom across different fixation mechanisms. It also provides formal proofs of global isostaticity. Practical usefulness is illustrated through two examples with conclusive experimental results: a preliminary study made on a manikin with an arm exoskeleton controlling the movement (passive mode) and a larger campaign on ten healthy subjects performing pointing tasks with a transparent robot (active mode).

Journal ArticleDOI
TL;DR: The experimental results showed that the subjects successfully controlled the humanoid robot in the indoor maze and reached the goal by using the proposed asynchronous EEG-based active BCI system.
Abstract: The brain-computer interface (BCI) technique is a novel control interface to translate human intentions into appropriate motion commands for robotic systems. The aim of this study is to apply an asynchronous direct-control system for humanoid robot navigation using an electroencephalograph (EEG), based active BCI. The experimental procedures consist of offline training, online feedback testing, and real-time control sessions. The amplitude features from EEGs are extracted using power spectral analysis, while informative feature components are selected based on the Fisher ratio. The two classifiers are hierarchically structured to identify human intentions and trained to build an asynchronous BCI system. For the performance test, five healthy subjects controlled a humanoid robot navigation to reach a target goal in an indoor maze by using their EEGs based on real-time images obtained from a camera on the head of the robot. The experimental results showed that the subjects successfully controlled the humanoid robot in the indoor maze and reached the goal by using the proposed asynchronous EEG-based active BCI system.

Journal ArticleDOI
TL;DR: An adaptive control algorithm is proposed to guarantee task-space synchronization of networked robotic manipulators in the presence of dynamic uncertainties and time-varying communication delays.
Abstract: Passivity-based control has emerged as an important paradigm for synchronization of networked robotic systems. Despite the practical utility of task-space algorithms, the previous results focused on joint-space synchronization and were primarily derived for kinematically identical manipulators. Hence, in this paper, the problem of task-space synchronization of (possibly redundant) heterogeneous robotic systems is studied. By exploiting passivity-based synchronization results that are developed previously, an adaptive control algorithm is proposed to guarantee task-space synchronization of networked robotic manipulators in the presence of dynamic uncertainties and time-varying communication delays. To demonstrate the efficacy of the proposed framework, numerical simulations and experiments are conducted with redundant and nonredundant manipulators, respectively.

Journal ArticleDOI
TL;DR: A rigorous analysis of the system stability and steady-state characteristics and validate performance through human/hardware-in-the-loop simulations by considering a heterogeneous fleet of unmanned aerial vehicles (UAVs) and unmanned ground vehicles as a case study and provides an experimental validation with four quadrotor UAVs.
Abstract: In this paper, a novel decentralized control strategy for bilaterally teleoperating heterogeneous groups of mobile robots from different domains (aerial, ground, marine, and underwater) is proposed. By using a decentralized control architecture, the group of robots, which is treated as the slave side, is made able to navigate in a cluttered environment while avoiding obstacles, interrobot collisions, and following the human motion commands. Simultaneously, the human operator acting on the master side is provided with a suitable force feedback informative of the group response and of the interaction with the surrounding environment. Using passivity-based techniques, we allow the behavior of the group to be as flexible as possible with arbitrary split and join events (e.g., due to interrobot visibility/packet losses or specific task requirements) while guaranteeing the stability of the system. We provide a rigorous analysis of the system stability and steady-state characteristics and validate performance through human/hardware-in-the-loop simulations by considering a heterogeneous fleet of unmanned aerial vehicles (UAVs) and unmanned ground vehicles as a case study. Finally, we also provide an experimental validation with four quadrotor UAVs.

Journal ArticleDOI
TL;DR: This paper considers both the design of open-loop trajectories with optimal properties and of distributed control laws converging to optimal trajectories, and develops a constant factor approximation algorithm for the minimum refresh time trajectory for a cyclic graph.
Abstract: The subject of this paper is the patrolling of an environment with the aid of a team of autonomous agents. We consider both the design of open-loop trajectories with optimal properties and of distributed control laws converging to optimal trajectories. As performance criteria, the refresh time and the latency are considered, i.e., respectively, time gap between any two visits of the same region and the time necessary to inform every agent about an event occurred in the environment. We associate a graph with the environment, and we study separately the case of a chain, tree, and cyclic graph. For the case of chain graph, we first describe a minimum refresh time and latency team trajectory and propose a polynomial time algorithm for its computation. Then, we describe a distributed procedure that steers the robots toward an optimal trajectory. For the case of tree graph, a polynomial time algorithm is developed for the minimum refresh time problem, under the technical assumption of a constant number of robots involved in the patrolling task. Finally, we show that the design of a minimum refresh time trajectory for a cyclic graph is NP-hard, and we develop a constant factor approximation algorithm.

Journal ArticleDOI
Qingsong Xu1
TL;DR: An enhanced model-predictive control (EMPC) scheme is presented for positioning control of a novel parallel-kinematic XY micropositioning system, which has a motion range larger than 10 mm along with a compact structure.
Abstract: Flexure-based micropositioning systems with a large workspace are attractive for a variety of precision engineering applications. In this paper, a new idea of multistage compound parallelogram flexure is proposed for the mechanism design of a novel parallel-kinematic XY micropositioning system, which has a motion range larger than 10 mm along with a compact structure. The established quantitative models and the stage performances are validated by conducting finite-element analysis (FEA) and experimental studies. Moreover, an enhanced model-predictive control (EMPC) is presented for positioning control of the system, which has a nonminimum-phase plant. It is shown that the EMPC is capable of producing a low magnitude of output tracking error by imposing an appropriate suppression on the control effort. Simulation and experimental studies reveal that the EMPC scheme outperforms the conventional proportional-integral-derivative (PID) and MPC methods in terms of transient response speed and steady-state accuracy. The idea that is presented in this paper is extendable to design and control of other micro-/nanopositioning systems with either minimum- or nonminimum-phase plants.

Journal ArticleDOI
TL;DR: A computational framework for automatic deployment of a robot with sensor and actuator noise from a temporal logic specification over a set of properties that are satisfied by the regions of a partitioned environment is described.
Abstract: We describe a computational framework for automatic deployment of a robot with sensor and actuator noise from a temporal logic specification over a set of properties that are satisfied by the regions of a partitioned environment. We model the motion of the robot in the environment as a Markov decision process (MDP) and translate the motion specification to a formula of probabilistic computation tree logic (PCTL). As a result, the robot control problem is mapped to that of generating an MDP control policy from a PCTL formula. We present algorithms for the synthesis of such policies for different classes of PCTL formulas. We illustrate our method with simulation and experimental results.

Journal ArticleDOI
TL;DR: A combined prediction and motion-planning scheme for robotic capturing of a drifting and tumbling object with unknown dynamics using visual feedback, using a Kalman filter to estimate the states and a set of dynamics parameters of the object needed for long-term prediction of the motion from noisy measurements of a vision system.
Abstract: Visually guided robotic capturing of a moving object often requires long-term prediction of the object motion not only for a smooth capture but because visual feedback may not be continually available, e.g., due to vision obstruction by the robotic arm, as well. This paper presents a combined prediction and motion-planning scheme for robotic capturing of a drifting and tumbling object with unknown dynamics using visual feedback. A Kalman filter estimates the states and a set of dynamics parameters of the object needed for long-term prediction of the motion from noisy measurements of a vision system. Subsequently, the estimated states, parameters, and predicted motion trajectories are used to plan the trajectory of the robot's end-effector to intercept a grapple fixture on the object with zero relative velocity (to avoid impact) in an optimal way. The optimal trajectory minimizes a cost function, which is a weighted linear sum of travel time, distance, cosine of a line-of-sight angle (object alignment for robotic grasping), and a penalty function acting as a constraint on acceleration magnitude. Experiments are presented to demonstrate the robot-motion planning scheme for autonomous grasping of a tumbling satellite. Two robotics manipulators are employed: One arm drifts and tumbles the mockup of a satellite, and the other arm that is equipped with a robotic hand tries to capture a grapple fixture on the satellite using the visual guidance system.

Journal ArticleDOI
TL;DR: Methods to control multiple untethered magnetic microrobots (called Mag-μBots), with all dimensions under 1 mm, without the need for a specialized surface are proposed, which has potential applications in areas such as microfluidic systems and biomanipulation.
Abstract: In this paper, we propose methods to control multiple untethered magnetic microrobots (called Mag-μBots), with all dimensions under 1 mm, without the need for a specialized surface. We investigate sets of Mag-μBots that are geometrically designed to respond uniquely to the same applied magnetic fields. By controlling the magnetic field waveforms, individual and subgroups of Mag-μBots are able to locomote in a parallel but dissimilar fashion. The control of geometrically dissimilar Mag-μBots and a group of identically fabricated Mag-μBots are investigated, and control strategies are developed for 1-D and 2-D motion. This is accomplished by learning the velocity response of each microrobot to various control signals and using the uniqueness of each microrobot response to achieve independent control. The effect of high-level control parameters are investigated in simulation and in experiments, and the simultaneous independent global positioning of two and three microrobots is demonstrated in 2-D space. As this control method is accomplished without the use of a specialized surface, it has potential applications in areas such as microfluidic systems and biomanipulation.

Journal ArticleDOI
TL;DR: A computational framework for automatic synthesis of control and communication strategies for a robotic team from task specifications that are given as regular expressions about servicing requests in an environment by using a technique inspired by linear temporal logic model checking.
Abstract: We present a computational framework for automatic synthesis of control and communication strategies for a robotic team from task specifications that are given as regular expressions about servicing requests in an environment. We assume that the location of the requests in the environment and the robot capacities and cooperation requirements to service the requests are known. Our approach is based on two main ideas. First, we extend recent results from formal synthesis of distributed systems to check for the distributability of the task specification and to generate local specifications, while accounting for the service and communication capabilities of the robots. Second, by using a technique that is inspired by linear temporal logic model checking, we generate individual control and communication strategies. We illustrate the method with experimental results in our robotic urban-like environment.

Journal ArticleDOI
TL;DR: A simple control strategy for the compensation of these nonlinear effects and the control of the force that is applied by the tendon to the load is proposed and experimentally verified.
Abstract: In this paper, we deal with several aspects related to the control of tendon-based actuation systems for robotic devices. In particular, the problems that are considered in this paper are related to the modeling, identification, and control of tendons sliding on curved pathways, subject to friction and viscoelastic effects. Tendons made in polymeric materials are considered, and therefore, hysteresis in the transmission system characteristic must be taken into account as an additional nonlinear effect because of the plasticity and creep phenomena typical of these materials. With the aim of reproducing these behaviors, a viscoelastic model is used to model the tendon compliance. Particular attention has been given to the friction effects arising from the interaction between the tendon pathway and the tendon itself. This phenomenon has been characterized by means of a LuGre-like dynamic friction model to consider the effects that cannot be reproduced by employing a static friction model. A specific setup able to measure the tendon's tension in different points along its path has been designed in order to verify the tension distribution and identify the proper parameters. Finally, a simple control strategy for the compensation of these nonlinear effects and the control of the force that is applied by the tendon to the load is proposed and experimentally verified.

Journal ArticleDOI
TL;DR: This paper presents a kinodynamic motion planner, i.e., Kinodynamic Motion Planning by Interior-Exterior Cell Exploration (KPIECE), which is specifically designed for systems with complex dynamics, where integration backward in time is not possible, and speed of computation is important.
Abstract: This paper presents a kinodynamic motion planner, i.e., Kinodynamic Motion Planning by Interior-Exterior Cell Exploration (KPIECE), which is specifically designed for systems with complex dynamics, where integration backward in time is not possible, and speed of computation is important. A grid-based discretization is used to estimate the coverage of the state space. The coverage estimates help the planner detect the less-explored areas of the state space. An important characteristic of this discretization is that it keeps track of the boundary of the explored region of the state space and focuses exploration on the less covered parts of this boundary. Extensive experiments show that KPIECE provides significant computational gain over existing state-of-the-art methods and allows us to solve some harder, previously unsolvable problems. For some problems, KPIECE is shown to be up to two orders of magnitude faster than existing methods and use up to 40 times less memory. A shared memory parallel implementation is presented as well. This implementation provides better speedup than an embarrassingly parallel implementation by taking advantage of the evolving multicore technology.

Journal ArticleDOI
TL;DR: The planner, which is applied into “robot handing over an object” scenarios, breaks the human centric interaction that depends mostly on human effort and allows the robot to take initiative by computing automatically where the interaction takes place, thus decreasing the cognitive weight of interaction on human side.
Abstract: With recent advances in safe and compliant hardware and control, robots are close to finding their places in our homes. As the safety barrier between humans and robots is beginning to fade, the necessity to design pertinent robot behavior in human environments is becoming a crucial step. In order to obtain a safe, comfortable, and socially acceptable interaction, the robot should be engineered from top to bottom by considering the presence of the human. In this paper, we present a manipulation planning framework and its implementation human-aware manipulation planner. This planner generates paths not only safe but comfortable and “socially acceptable” as well by reasoning explicitly on human's kinematics, vision field, posture, and preferences. The planner, which is applied into “robot handing over an object” scenarios, breaks the human centric interaction that depends mostly on human effort and allows the robot to take initiative by computing automatically where the interaction takes place, thus decreasing the cognitive weight of interaction on human side.

Journal ArticleDOI
TL;DR: An event-based iterative closest point algorithm to track a microgripper's position at a frequency of 4 kHz is introduced, using an asynchronous address event representation silicon retina and a conventional frame-based camera.
Abstract: Micromanipulation systems have recently been receiving increased attention. Teleoperated or automated micromanipulation is a challenging task due to the need for high-frequency position or force feedback to guarantee stability. In addition, the integration of sensors within micromanipulation platforms is complex. Vision is a commonly used solution for sensing; unfortunately, the update rate of the frame-based acquisition process of current available cameras cannot ensure-at reasonable costs-stable automated or teleoperated control at the microscale level, where low inertia produces highly unreachable dynamic phenomena. This paper presents a novel vision-based microrobotic system combining both an asynchronous address event representation silicon retina and a conventional frame-based camera. Unlike frame-based cameras, recent artificial retinas transmit their outputs as a continuous stream of asynchronous temporal events in a manner similar to the output cells of a biological retina, enabling high update rates. This paper introduces an event-based iterative closest point algorithm to track a microgripper's position at a frequency of 4 kHz. The temporal precision of the asynchronous silicon retina is used to provide a haptic feedback to assist users during manipulation tasks, whereas the frame-based camera is used to retrieve the position of the object that must be manipulated. This paper presents the results of an experiment on teleoperating a sphere of diameter around 50 μm using a piezoelectric gripper in a pick-and-place task.

Journal ArticleDOI
TL;DR: A novel joining method that is based on the modification of the original dynamic movement primitive formulation can reproduce the target trajectory with high accuracy regarding both the position and the velocity profile and produces smooth and natural transitions in position space, as well as in velocity space.
Abstract: The generation of complex movement patterns, in particular, in cases where one needs to smoothly and accurately join trajectories in a dynamic way, is an important problem in robotics. This paper presents a novel joining method that is based on the modification of the original dynamic movement primitive formulation. The new method can reproduce the target trajectory with high accuracy regarding both the position and the velocity profile and produces smooth and natural transitions in position space, as well as in velocity space. The properties of the method are demonstrated by its application to simulated handwriting generation, which are also shown on a robot, where an adaptive algorithm is used to learn trajectories from human demonstration. These results demonstrate that the new method is a feasible alternative for joining of movement sequences, which has a high potential for all robotics applications where trajectory joining is required.

Journal ArticleDOI
TL;DR: In this paper, a potential-field-based controller is developed to drive every pair of particles to the assigned array, while preventing collisions between particles, using integrated robotics and holographic optical tweezers technologies.
Abstract: Significant demand for both accuracy and productivity in batch manipulation of microparticles highlights the need to develop an automatic arraying approach to placing groups of particles into a predefined array with right pairs. This paper presents our latest effort to achieve this objective using integrated robotics and holographic optical tweezers technologies, where holographic optical tweezers function as special robot end-effectors to manipulate the microparticles. Based on the physical dynamics of trapping, a potential-field-based controller is developed to drive every pair of particles to the assigned array, while preventing collisions between particles. The significance of the proposed controller lies in the capability of driving two groups of particles into a common array in right pair and controlling the interdistances between the particles in pairs. Experiments are performed to demonstrate the effectiveness of the proposed approach.