Showing papers in "IEEE Transactions on Robotics in 2009"

Consensus-Based Decentralized Auctions for Robust Task Allocation

Abstract: This paper addresses task allocation to coordinate a fleet of autonomous vehicles by presenting two decentralized algorithms: the consensus-based auction algorithm (CBAA) and its generalization to the multi-assignment problem, i.e., the consensus-based bundle algorithm (CBBA). These algorithms utilize a market-based decision strategy as the mechanism for decentralized task selection and use a consensus routine based on local communication as the conflict resolution mechanism to achieve agreement on the winning bid values. Under reasonable assumptions on the scoring scheme, both of the proposed algorithms are proven to guarantee convergence to a conflict-free assignment, and it is shown that the converged solutions exhibit provable worst-case performance. It is also demonstrated that CBAA and CBBA produce conflict-free feasible solutions that are robust to both inconsistencies in the situational awareness across the fleet and variations in the communication network topology. Numerical experiments confirm superior convergence properties and performance when compared with existing auction-based task-allocation algorithms.

Temporal-Logic-Based Reactive Mission and Motion Planning

Abstract: This paper provides a framework to automatically generate a hybrid controller that guarantees that the robot can achieve its task when a robot model, a class of admissible environments, and a high-level task or behavior for the robot are provided. The desired task specifications, which are expressed in a fragment of linear temporal logic (LTL), can capture complex robot behaviors such as search and rescue, coverage, and collision avoidance. In addition, our framework explicitly captures sensor specifications that depend on the environment with which the robot is interacting, which results in a novel paradigm for sensor-based temporal-logic-motion planning. As one robot is part of the environment of another robot, our sensor-based framework very naturally captures multirobot specifications in a decentralized manner. Our computational approach is based on first creating discrete controllers satisfying specific LTL formulas. If feasible, the discrete controller is then used to guide the sensor-based composition of continuous controllers, which results in a hybrid controller satisfying the high-level specification but only if the environment is admissible.

A Noninvasive Brain-Actuated Wheelchair Based on a P300 Neurophysiological Protocol and Automated Navigation

Abstract: This paper describes a new noninvasive brain-actuated wheelchair that relies on a P300 neurophysiological protocol and automated navigation. When in operation, the user faces a screen displaying a real-time virtual reconstruction of the scenario and concentrates on the location of the space to reach. A visual stimulation process elicits the neurological phenomenon, and the electroencephalogram (EEG) signal processing detects the target location. This location is transferred to the autonomous navigation system that drives the wheelchair to the desired location while avoiding collisions with obstacles in the environment detected by the laser scanner. This concept gives the user the flexibility to use the device in unknown and evolving scenarios. The prototype was validated with five healthy participants in three consecutive steps: screening (an analysis of three different groups of visual interface designs), virtual-environment driving, and driving sessions with the wheelchair. On the basis of the results, this paper reports the following evaluation studies: 1) a technical evaluation of the device and all functionalities; 2) a users' behavior study; and 3) a variability study. The overall result was that all the participants were able to successfully operate the device with relative ease, thus showing a great adaptation as well as a high robustness and low variability of the system.

Cooperative Robot Control and Concurrent Synchronization of Lagrangian Systems

Abstract: Concurrent synchronization is a regime where diverse groups of fully synchronized dynamic systems stably coexist. We study global exponential synchronization and concurrent synchronization in the context of Lagrangian systems control. In a network constructed by adding diffusive couplings to robot manipulators or mobile robots, a decentralized tracking control law globally exponentially synchronizes an arbitrary number of robots, and represents a generalization of the average consensus problem. Exact nonlinear stability guarantees and synchronization conditions are derived by contraction analysis. The proposed decentralized strategy is further extended to adaptive synchronization and partial-state coupling.

Powered Ankle--Foot Prosthesis Improves Walking Metabolic Economy

Abstract: At moderate to fast walking speeds, the human ankle provides net positive work at high-mechanical-power output to propel the body upward and forward during the stance period. On the contrary, conventional ankle-foot prostheses exhibit a passive-elastic response during stance, and consequently, cannot provide net work. Clinical studies indicate that transtibial amputees using conventional prostheses have higher gait metabolic rates than normal. Researchers believe that the main cause for these higher rates is due to the inability of conventional prostheses to provide sufficient positive power at terminal stance in the trailing leg to limit heel strike losses of the adjacent leading leg. In this investigation, we evaluate the hypothesis that a powered ankle-foot prosthesis, capable of providing human-like ankle work and power during stance, can decrease the metabolic cost of transport (COT) compared to a conventional passive-elastic prosthesis. To test the hypothesis, a powered prosthesis is built that comprises a unidirectional spring, configured in parallel with a force-controllable actuator with series elasticity. The prosthesis is shown to deliver the high mechanical power and net positive work observed in normal human walking. The rate of oxygen consumption and carbon dioxide production is measured as a determinant of metabolic rate on three unilateral transtibial amputees walking at self-selected speeds. We find that the powered prosthesis decreases the amputee's metabolic COT on average by 14% compared to the conventional passive-elastic prostheses evaluated (Flex-Foot Ceterusreg and Freedom Innovations Sierra), even though the powered system is over twofold heavier than the conventional devices. These results highlight the clinical importance of prosthetic interventions that closely mimic the mass distribution, kinetics, and kinematics of the missing limb.

Mechanics of Precurved-Tube Continuum Robots

Abstract: This paper presents a new class of thin, dexterous continuum robots, which we call active cannulas due to their potential medical applications. An active cannula is composed of telescoping, concentric, precurved superelastic tubes that can be axially translated and rotated at the base relative to one another. Active cannulas derive bending not from tendon wires or other external mechanisms but from elastic tube interaction in the backbone itself, permitting high dexterity and small size, and dexterity improves with miniaturization. They are designed to traverse narrow and winding environments without relying on ldquoguidingrdquo environmental reaction forces. These features seem ideal for a variety of applications where a very thin robot with tentacle-like dexterity is needed. In this paper, we apply beam mechanics to obtain a kinematic model of active cannula shape and describe design tools that result from the modeling process. After deriving general equations, we apply them to a simple three-link active cannula. Experimental results illustrate the importance of including torsional effects and the ability of our model to predict energy bifurcation and active cannula shape.

Vision-Aided Inertial Navigation for Spacecraft Entry, Descent, and Landing

Abstract: In this paper, we present the vision-aided inertial navigation (VISINAV) algorithm that enables precision planetary landing. The vision front-end of the VISINAV system extracts 2-D-to-3-D correspondences between descent images and a surface map (mapped landmarks), as well as 2-D-to-2-D feature tracks through a sequence of descent images (opportunistic features). An extended Kalman filter (EKF) tightly integrates both types of visual feature observations with measurements from an inertial measurement unit. The filter computes accurate estimates of the lander's terrain-relative position, attitude, and velocity, in a resource-adaptive and hence real-time capable fashion. In addition to the technical analysis of the algorithm, the paper presents validation results from a sounding-rocket test flight, showing estimation errors of only 0.16 m/s for velocity and 6.4 m for position at touchdown. These results vastly improve current state of the art for terminal descent navigation without visual updates, and meet the requirements of future planetary exploration missions.

Design and Analysis of a Totally Decoupled Flexure-Based XY Parallel Micromanipulator

Abstract: In this paper, a concept of totally decoupling is proposed for the design of a flexure parallel micromanipulator with both input and output decoupling. Based on flexure hinges, the design procedure for an XY totally decoupled parallel stage (TDPS) is presented, which is featured with decoupled actuation and decoupled output motion as well. By employing (double) compound parallelogram flexures and a compact displacement amplifier, a class of novel XY TDPS with simple and symmetric structures are enumerated, and one example is chosen for further analysis. The kinematic and dynamic modeling of the manipulator are conducted by resorting to compliance and stiffness analysis based on the matrix method, which are validated by finite-element analysis (FEA). In view of predefined performance constraints, the dimension optimization is carried out by means of particle swarm optimization, and a prototype of the optimized stage is fabricated for performance tests. Both FEA and experimental studies well validate the decoupling property of the XY stage that is expected to be adopted into micro-/nanoscale manipulations.

Robot-Aided Neurorehabilitation: A Novel Robot for Ankle Rehabilitation

Abstract: In this paper, we present the design and characterization of a novel ankle robot developed at the Massachusetts institute of technology (MIT). This robotic module is being tested with stroke patients at Baltimore Veterans administration medical center. The purpose of the on-going study is to train stroke survivors to overcome common foot drop and balance problems in order to improve their ambulatory performance. Its design follows the same guidelines of our upper extremity designs, i.e., it is a low friction, backdriveable device with intrinsically low mechanical impedance. Here, we report on the design and mechanical characteristics of the robot. We also present data to demonstrate the potential of this device as an efficient clinical measurement tool to estimate intrinsic ankle properties. Given the importance of the ankle during locomotion, an accurate estimate of ankle stiffness would be a valuable asset for locomotor rehabilitation. Our initial ankle stiffness estimates compare favorably with previously published work, indicating that our method may serve as an accurate clinical measurement tool.

Asymptotically Stable Walking of a Five-Link Underactuated 3-D Bipedal Robot

Abstract: This paper presents three feedback controllers that achieve an asymptotically stable, periodic, and fast walking gait for a 3-D bipedal robot consisting of a torso, revolute knees, and passive (unactuated) point feet. The walking surface is assumed to be rigid and flat; the contact between the robot and the walking surface is assumed to inhibit yaw rotation. The studied robot has 8 DOF in the single support phase and six actuators. In addition to the reduced number of actuators, the interest of studying robots with point feet is that the feedback control solution must explicitly account for the robot's natural dynamics in order to achieve balance while walking. We use an extension of the method of virtual constraints and hybrid zero dynamics (HZD), a very successful method for planar bipeds, in order to simultaneously compute a periodic orbit and an autonomous feedback controller that realizes the orbit, for a 3-D (spatial) bipedal walking robot. This method allows the computations for the controller design and the periodic orbit to be carried out on a 2-DOF subsystem of the 8-DOF robot model. The stability of the walking gait under closed-loop control is evaluated with the linearization of the restricted Poincare map of the HZD. Most periodic walking gaits for this robot are unstable when the controlled outputs are selected to be the actuated coordinates. Three strategies are explored to produce stable walking. The first strategy consists of imposing a stability condition during the search of a periodic gait by optimization. The second strategy uses an event-based controller to modify the eigenvalues of the (linearized) Poincare map. In the third approach, the effect of output selection on the zero dynamics is discussed and a pertinent choice of outputs is proposed, leading to stabilization without the use of a supplemental event-based controller.

Optimized Stochastic Policies for Task Allocation in Swarms of Robots

Abstract: We present a scalable approach to dynamically allocating a swarm of homogeneous robots to multiple tasks, which are to be performed in parallel, following a desired distribution. We employ a decentralized strategy that requires no communication among robots. It is based on the development of a continuous abstraction of the swarm obtained by modeling population fractions and defining the task allocation problem as the selection of rates of robot ingress and egress to and from each task. These rates are used to determine probabilities that define stochastic control policies for individual robots, which, in turn, produce the desired collective behavior. We address the problem of computing rates to achieve fast redistribution of the swarm subject to constraint(s) on switching between tasks at equilibrium. We present several formulations of this optimization problem that vary in the precedence constraints between tasks and in their dependence on the initial robot distribution. We use each formulation to optimize the rates for a scenario with four tasks and compare the resulting control policies using a simulation in which 250 robots redistribute themselves among four buildings to survey the perimeters.

Optimal Design of a 4-DOF Parallel Manipulator: From Academia to Industry

Abstract: This paper presents an optimal design of a parallel manipulator aiming to perform pick-and-place operations at high speed and high acceleration. After reviewing existing architectures of high-speed and high-acceleration parallel manipulators, a new design of a 4-DOF parallel manipulator is presented, with an articulated traveling plate, which is free of internal singularities and is able to achieve high performances. The kinematic and simplified, but realistic, dynamic models are derived and validated on a manipulator prototype. Experimental tests show that this design is able to perform beyond the high targets, i.e., it reaches a speed of 5.5 m/s and an acceleration of 165 m/s2. The experimental prototype was further optimized on the basis of kinematic and dynamic criteria. Once the motors, gear ratio, and several link lengths are determined, a modified design of the articulated traveling plate is proposed in order to reach a better dynamic equilibrium among the four legs of the manipulator. The obtained design is the basis of a commercial product offering the shortest cycle times among all robots available in today's market.

A Unified Approach to Integrate Unilateral Constraints in the Stack of Tasks

Abstract: The control approaches based on the task function formalism, and particularly those structured as a prioritized hierarchy of tasks, enable complex behaviors with elegant properties of robustness and portability to be built. However, it is difficult to consider a straightforward integration of tasks described by unilateral constraints in such frameworks. Indeed, unilateral constraints exhibit irregularities that prevent the insertion of unilateral tasks at any priority level, other than the lowest, of a hierarchy. In this paper, we present an original method to generalize the hierarchy-based control schemes to account for unilateral constraints at any priority level. We develop our method first for task sequencing using only the kinematics description; then, we expand it to the task description, using the operational space formulation. The method applies in robotics and computer graphics animation. Its practical implementation is exemplified by realizing a real-manipulator visual servoing task and a humanoid avatar reaching task; both experiments are achieved under the unilateral constraints of joint limits.

A New Mechanism for Mesoscale Legged Locomotion in Compliant Tubular Environments

Abstract: We present design and experimental performance results for a novel mechanism for robotic legged locomotion at the mesoscale (from hundreds of microns to tens of centimeters). The new mechanism is compact and strikes a balance between conflicting design objectives, exhibiting high foot forces and low power consumption. It enables a small robot to traverse a compliant, slippery, tubular environment, even while climbing against gravity. This mechanism is useful for many mesoscale locomotion tasks, including endoscopic capsule robot locomotion in the gastrointestinal tract. It has enabled fabrication of the first legged endoscopic capsule robot whose mechanical components match the dimensions of commercial pill cameras (11 mm diameter by 25 mm long). A novel slot-follower mechanism driven via lead screw enables the mechanical components of the capsule robot to be as small while simultaneously generating 0.63 N average propulsive force at each leg tip. In this paper, we describe kinematic and static analyses of the lead screw and slot-follower mechanisms, optimization of design parameters, and experimental design and tuning of a gait suitable for locomotion. A series of ex vivo experiments demonstrate capsule performance and ability to traverse the intestine in a manner suitable for inspection of the colon in a time period equivalent to standard colonoscopy.

Vision-Based, Distributed Control Laws for Motion Coordination of Nonholonomic Robots

Abstract: In this paper, we study the problem of distributed motion coordination among a group of nonholonomic ground robots. We develop vision-based control laws for parallel and balanced circular formations using a consensus approach. The proposed control laws are distributed in the sense that they require information only from neighboring robots. Furthermore, the control laws are coordinate-free and do not rely on measurement or communication of heading information among neighbors but instead require measurements of bearing, optical flow, and time to collision, all of which can be measured using visual sensors. Collision-avoidance capabilities are added to the team members, and the effectiveness of the control laws are demonstrated on a group of mobile robots.

Biologically Inspired Mobile Robot Vision Localization

Abstract: We present a robot localization system using biologically inspired vision. Our system models two extensively studied human visual capabilities: (1) extracting the ldquogistrdquo of a scene to produce a coarse localization hypothesis and (2) refining it by locating salient landmark points in the scene. Gist is computed here as a holistic statistical signature of the image, thereby yielding abstract scene classification and layout. Saliency is computed as a measure of interest at every image location, which efficiently directs the time-consuming landmark-identification process toward the most likely candidate locations in the image. The gist features and salient regions are then further processed using a Monte Carlo localization algorithm to allow the robot to generate its position. We test the system in three different outdoor environments-building complex (38.4 m times 54.86 m area, 13 966 testing images), vegetation-filled park (82.3 m times 109.73 m area, 26 397 testing images), and open-field park (137.16 m times 178.31 m area, 34 711 testing images)-each with its own challenges. The system is able to localize, on average, within 0.98, 2.63, and 3.46 m, respectively, even with multiple kidnapped-robot instances.

Self-Aligning Exoskeleton Axes Through Decoupling of Joint Rotations and Translations

Abstract: To automatically align exoskeleton axes to human anatomical axes, we propose to decouple the joint rotations from the joint translations. Decoupling can reduce setup times and painful misalignment forces, at the cost of increased mechanical complexity and movement inertia. The decoupling approach was applied to the Dampace and Limpact exoskeletons.

Configuration Tracking for Continuum Manipulators With Coupled Tendon Drive

Abstract: Robotic control of flexible devices can enhance and simplify many medical procedures. We present a method for controlling a tendon-driven continuum manipulator by means of specifying the shape configuration. The basis for control is a linear beam configuration model that transforms beam configuration to tendon displacement by modeling internal loads of the compliant system. An essential aspect of this model is the inclusion of both the mechanical and geometrical coupling among serial articulating sections. Important capabilities of this model are the general forward kinematics and the decoupled inverse kinematics that allow for independent control of multiple sections. Tracking results are presented for a cardiac catheter with two articulating sections.

A Synchronization Approach to Trajectory Tracking of Multiple Mobile Robots While Maintaining Time-Varying Formations

Abstract: In this paper, we present a synchronization approach to trajectory tracking of multiple mobile robots while maintaining time-varying formations. The main idea is to control each robot to track its desired trajectory while synchronizing its motion with those of other robots to keep relative kinematics relationships, as required by the formation. First, we pose the formation-control problem as a synchronization control problem and identify the synchronization control goal according to the formation requirement. The formation error is measured by the position synchronization error, which is defined based on the established robot network. Second, we develop a synchronous controller for each robot's translation to guarantee that both position and synchronization errors approach zero asymptotically. The rotary controller is also designed to ensure that the robot is always oriented toward its desired position. Both translational and rotary controls are supported by a centralized high-level planer for task monitoring and robot global localization. Finally, we perform simulations and experiments to demonstrate the effectiveness of the proposed synchronization control approach in the formation control tasks.

Stability Analysis for Prioritized Closed-Loop Inverse Kinematic Algorithms for Redundant Robotic Systems

Abstract: Stability analysis of priority-based kinematic control algorithms for redundant robotic systems is approached in this paper. Starting from the classical applications in position control of manipulators, the kinematic-based approaches have lately been applied to, e.g., visual servoing and quadruped or multirobot coordination control. A common approach consists in the definition of several tasks properly combined in priority. In this paper, by resorting to a Lyapunov-based stability discussion for several prioritized inverse kinematics algorithms, sufficient conditions for the control gains and the tasks' design are given for the regulation problem. Two case studies show the practical implementation of the results.

Robotic Cell Injection System With Position and Force Control: Toward Automatic Batch Biomanipulation

Abstract: Biological cell injection is laborious work that requires lengthy training and suffers from a low success rate. In this paper, a robotic cell-injection system for automatic injection of batch-suspended cells is proposed. To facilitate the process, these suspended cells are held and fixed to a cell array by a specially designed cell-holding device, and injected one by one through an ldquoout-of-planerdquo cell-injection process. A micropipette equipped with a polyvinylidene fluoride microforce sensor to measure real-time injection force is integrated in the proposed system. Through calibration, an empirical relationship between the cell-injection force and the desired injector pipette trajectory is obtained in advance. Then, after decoupling the out-of-plane cell injection into a position control in the X - Y horizontal plane and an impedance control in the Z -axis, a position and force control algorithm is developed to control the injection pipette. The depth motion of the injector pipette, which cannot be observed by microscope, is indirectly controlled via the impedance control, and the desired force is determined from the online X - Y position control and cell calibration results. Finally, experimental results demonstrate the effectiveness of the proposed approach.

Image-Based Visual Servo Control of the Translation Kinematics of a Quadrotor Aerial Vehicle

Abstract: In this paper, we investigate a range of image-based visual servo control algorithms for regulation of the position of a quadrotor aerial vehicle. The most promising control algorithms have been successfully implemented on an autonomous aerial vehicle and demonstrate excellent performance.

Kinematic Modeling and Analysis of Skid-Steered Mobile Robots With Applications to Low-Cost Inertial-Measurement-Unit-Based Motion Estimation

Abstract: Skid-steered mobile robots are widely used because of their simple mechanism and high reliability. Understanding the kinematics and dynamics of such a robotic platform is, however, challenging due to the complex wheel/ground interactions and kinematic constraints. In this paper, we develop a kinematic modeling scheme to analyze the skid-steered mobile robot. Based on the analysis of the kinematics of the skid-steered mobile robot, we reveal the underlying geometric and kinematic relationships between the wheel slips and locations of the instantaneous rotation centers. As an application example, we also present how to utilize the modeling and analysis for robot positioning and wheel slip estimation using only low-cost strapdown inertial measurement units. The robot positioning and wheel slip-estimation scheme is based on an extended Kalman filter (EKF) design that incorporates the kinematic constraints for accuracy enhancement. The performance of the EKF-based positioning and wheel slip-estimation scheme are also presented. The estimation methodology is tested and validated experimentally on a robotic test bed.

Vision-Based Localization for Leader–Follower Formation Control

Abstract: This paper deals with vision-based localization for leader-follower formation control. Each unicycle robot is equipped with a panoramic camera that only provides the view angle to the other robots. The localization problem is studied using a new observability condition valid for general nonlinear systems and based on the extended output Jacobian. This allows us to identify those robot motions that preserve the system observability and those that render it nonobservable. The state of the leader-follower system is estimated via the extended Kalman filter, and an input-state feedback control law is designed to stabilize the formation. Simulations and real-data experiments confirm the theoretical results and show the effectiveness of the proposed formation control.

Two-Dimensional Contact and Noncontact Micromanipulation in Liquid Using an Untethered Mobile Magnetic Microrobot

Abstract: This paper presents the manipulation of microspheres under water by use of an untethered electromagnetically actuated magnetic microrobot (Mag-muBot), with dimensions 250 times 130 times 100 mum3. Manipulation is achieved by two means: contact and noncontact pushing modes. In contact manipulation, the Mag-muBot is used to physically push the microspheres. In noncontact manipulation, the fluid flow generated by the translation of the Mag-muBot is used to push the microspheres. Modeling of the system is performed, taking into account micrometer-scale surface forces and fluid drag effects to determine the motion of a sphere within a robot-generated fluid flow. Fluid drag models for free-stream flow and formulations for near-wall flow are both analyzed and compared with the experiments, in which pushing of two sphere sizes, i.e., 50 and 230 mum diameters, is characterized in a controlled, robot-generated flow. Dynamic simulations are provided using the developed physical models to capture this behavior. We find that the near-wall physical models are, in general, in agreement with the experiment, and free-stream models overestimate microsphere motion.

A Hybrid Motion Classification Approach for EMG-Based Human–Robot Interfaces Using Bayesian and Neural Networks

Abstract: In a human-robot interface, the prediction of motion, which is based on context information of a task, has the potential to improve the robustness and reliability of motion classification to control prosthetic devices or human-assisting manipulators. This paper proposes a task model using a Bayesian network (BN) for motion prediction. Given information of the previous motion, this task model is able to predict occurrence probabilities of the motions concerned in the task. Furthermore, a hybrid motion classification framework has been developed based on the BN motion prediction. Besides the motion prediction, electromyogram (EMG) signals are simultaneously classified by a probabilistic neural network (NN). Then, the motion occurrence probabilities are combined with the NN classifier's outputs to generate motion commands for control. With the proposed motion classification framework, it is expected that classification performance can be enhanced so that motion commands can be more robust and reliable. Experiments have been conducted with four subjects to demonstrate the feasibility of the proposed methods. In these experiments, forearm motions are classified with EMG signals considering a cooking task. Finally, robot manipulation experiments were carried out to verify the proposed human interface system with a task of taking meal. The experimental results indicate that the proposed methods improved the robustness and stability of motion classification.

Control of Nonholonomic Mobile Robots Based on the Transverse Function Approach

Abstract: The problem of stabilizing reference trajectories - also referred to as the trajectory tracking problem - for nonholonomic mobile robots is revisited. Theoretical difficulties and impossibilities that set inevitable limits to what is achievable with feedback control are surveyed, and properties of kinematic control models are recalled, with a focus on controllable driftless systems that are invariant on a Lie group. This geometric framework takes advantage of ubiquitous symmetry properties involved in the motion of mechanical bodies. The transverse function approach, a control design method developed by the authors for the past few years, is reviewed. A salient feature of this approach, which singles it out of the abundant literature devoted to the subject, is the obtention of feedback laws that unconditionally achieve the practical stabilization of arbitrary reference trajectories, including fixed points and nonadmissible trajectories. This property is complemented with novel results showing how the more common property of asymptotic stabilization of a large class of admissible trajectories can also be granted with this type of control. Application to unicycle-type and car-like vehicles is presented and illustrated via simulations. Complementary issues (transient maneuvers monitoring, extensions of the approach to systems that are not invariant on a Lie group, etc.) are also addressed with the concern of practicality.

Computation of Independent Contact Regions for Grasping 3-D Objects

Abstract: Precision grasp synthesis has received a lot of attention in past few last years. However, real mechanical hands can hardly assure that the fingers will precisely touch the object at the computed contact points. The concept of independent contact regions (ICRs) was introduced to provide robustness to finger positioning errors during an object grasping: A finger contact anywhere inside each of these regions assures a force-closure grasp, despite the exact contact position. This paper presents an efficient algorithm to compute ICRs with any number of frictionless or frictional contacts on the surface of any 3-D object. The proposed approach generates the independent regions by growing them around the contact points of a given starting grasp. A two-phase approach is provided to find a locally optimal force-closure grasp that serves as the starting grasp, considering as grasp quality measure the largest perturbation wrench that the grasp can resist, independently of the perturbation direction. The proposed method can also be applied to compute ICRs when several contacts are fixed beforehand. The approach has been implemented, and application examples are included to illustrate its performance.

Online Segmentation and Clustering From Continuous Observation of Whole Body Motions

Abstract: This paper describes a novel approach for incremental learning of human motion pattern primitives through online observation of human motion. The observed time series data stream is first stochastically segmented into potential motion primitive segments, based on the assumption that data belonging to the same motion primitive will have the same underlying distribution. The motion segments are then abstracted into a stochastic model representation and automatically clustered and organized. As new motion patterns are observed, they are incrementally grouped together into a tree structure, based on their relative distance in the model space. The tree leaves, which represent the most specialized learned motion primitives, are then passed back to the segmentation algorithm so that as the number of known motion primitives increases, the accuracy of the segmentation can also be improved. The combined algorithm is tested on a sequence of continuous human motion data that are obtained through motion capture, and demonstrates the performance of the proposed approach.

Compliant Terrain Adaptation for Biped Humanoids Without Measuring Ground Surface and Contact Forces

Abstract: This paper reports the applicability of our passivity-based contact force control framework for biped humanoids. We experimentally demonstrate its adaptation to unknown rough terrain. Adaptation to uneven ground is achieved by optimally distributed antigravitational forces applied to preset contact points in a feedforward manner, even without explicitly measuring the external forces or the terrain shape. Adaptation to unknown inclination is also possible by combining an active balancing controller based on the center-of-mass (CoM) measurements with respect to the inertial frame. Furthermore, we show that a simple impedance controller for supporting the feet or hands allows the robot to adapt to low-friction ground without prior knowledge of the ground friction. This presentation includes supplementary experimental videos that show a full-sized biped humanoid robot balancing on uneven ground or time-varying inclination.