This paper investigates task allocation for multiple robots by applying the game theory-based negotiation approach. Based on the initial task allocation using a contract net-based approach, a new method to select the negotiation robots and construct the negotiation set is proposed by employing the utility functions. A negotiation mechanism suitable for the decentralized task allocation is also presented. Then, a game theory-based negotiation strategy is proposed to achieve the Pareto-optimal solution for the task reallocation. Extensive simulation results are provided to show that the task allocation solutions after the negotiation are better than the initial contract net-based allocation. In addition, experimental results are further presented to show the effectiveness of the approach presented.

In this paper, we propose a decentralized robust control algorithm for modular and reconfigurable robots (MRRs) based on Lyapunov's stability analysis and backstepping techniques. In using decentralized control schemes with robot manipulators, each joint is considered as an independent subsystem, and the dynamical effects from the other links and joints are treated as disturbance. However, there exist many uncertainties due to unmodeled dynamics, varying payloads, harmonic drive (HD) compliance, HD complex gear meshing mechanisms, etc. Also, while the reconfigurability of MRRs is advantageous, modifying the configuration will result in changes to the robot dynamics parameters, thereby making it challenging to tune the control system. All of the above mentioned disturbances in addition to reconfigurability present a challenge in controlling MRRs. The proposed controller is well suited for MRR applications because of its simple structure that does not require the exact knowledge of the dynamic parameters of the configurations. Desired tracking performance can be achieved via tuning a limited set of parameters of the robust controller. If the numbers of degrees of freedom are held constant, these parameters are shown to be relatively independent of the configuration, and can be held constant between changes in configuration. This strategy is novel compared to existing MRR control methods. In order to validate the controller performance, experimental setup and results are also presented.

This paper presents a novel trajectory planning method for a flexible Cartesian robot manipulator in a point-to-point motion. In order to obtain an exact mathematical model, the parameters of the equation of motion are determined from an identification experiment. An artificial neural network is employed to generate the desired base position, and then, a particle swarm optimization technique is used as the learning algorithm, in which the sum of the displacements of the manipulator is chosen as the objective function. We show that the residual vibrations of the manipulator can be suppressed by minimizing the displacement of the manipulator. The effectiveness and validity of the proposed method are demonstrated by comparing the simulation and experimental results.

The purpose of this paper is to present a robust tracking control algorithm for underactuated biped robots capable of self-balancing in the presence of external disturbances. The biped is modeled as a five-link planar robot with four actuators located at hip and knee joints. A sliding mode control law has been developed for the biped to follow a human-like gait trajectory while keeping the torso nearly upright. The control forces are calculated by defining four first-order sliding surfaces as a linear combination of the torso and the four joint tracking errors. The control approach is shown to guarantee that all trajectories will reach and stay on these surfaces during each step, while the walking cycle stability is maintained through a Lyapunov function. The criteria for asymptotic stability of the surfaces are presented and a numerical search method is implemented for the selection of the corresponding surface parameters. The paper further investigates the robustness of the controller in response to disturbances. Numerical simulations demonstrate the tracking stability of the biped's multistep walk and its human-like response to an external disturbance.

This paper presents a cable-driven dexterous manipulator with a large, open lumen. One specific application for the manipulator is the treatment of the degeneration of bone tissue (osteolysis) during a less-invasive hip revision surgery. Rigid tools used in traditional approaches limit the surgeons' ability to comprehensively treat the osteolysis due to the complex geometries of the lesion. The surgical scenario, testing, kinematic modeling, and image-based inverse kinematics are described. Testing shows 94% coverage of a lesion wall; the kinematic model describes manipulator notch positions within 0.15 mm, while the image-based inverse kinematics has 0.36 mm error. This manipulator is potentially useful in treating osteolytic lesions through (1) effective lesion exploration compared to conventional techniques, and (2) rapidly performing inverse kinematics from visual feedback.

In this paper, a Brain–Computer Interface (BCI) control approach for the assistive robotic system FRIEND is presented. The objective of the robot is to assist elderly and persons with disabilities in their daily and professional life activities. FRIEND is presented here from an architectural point of view, that is, as an overall robotic device that includes many subareas of research, such as human–robot interaction, perception, object manipulation and path planning, robotic safety, and so on. The integration of the hardware and software components is described relative to the interconnections between the various elements of FRIEND and the approach used for human–machine interaction. Since the robotic system is intended to be used especially by patients suffering from a high degree of disability (e.g., patients which are quadriplegic, have muscle diseases or serious paralysis due to strokes, or any other diseases with similar consequences for their independence), an alternative non-invasive BCI has been investigated. The FRIEND–BCI paradigm is explained within the overall structure of the robot. The capabilities of the robotic system are demonstrated in three support scenarios, one that deals with Activities of daily living (ADL) and two that are taking place in a rehabilitation workshop. The proposed robot was clinically evaluated through different tests that directly measure task execution time and hardware performance, as well as the acceptance of robot by end-users.

Several static and dynamic stability criteria have been defined in the course of walking-robot history. Nevertheless, previous work on the classification of stability criteria for statically stable walking machines (having at least four legs) reveals that there is no stability margin that accurately predicts robot stability when inertial and manipulation effects are significant. In such cases, every momentum-based stability margin fails. The use of an unsuitable stability criterion yields unavoidable errors in the control of walking robots. Moreover, inertial and manipulation effects usually appear in the motion of these robots when they are used for services or industrial applications. A new stability margin that accurately measures robot stability considering dynamic effects arising during motion is proposed in this paper. The new stability margin is proven to be the only exact stability margin when robot dynamics and manipulation forces exist. Numerical comparison has been conducted to support the margin's suitability. Stability-level curves are also presented on the basis of a suitable stability margin to control the trajectory of the center of gravity during the support phase.

We address general filtering problems on the Euclidean group SE(3). We first generalize, to stochastic nonlinear systems evolving on SE(3), the particle filter of Liu and West for simultaneous estimation of the state and covariance. The filter is constructed in a coordinate-invariant way, and explicitly takes into account the geometry of SE(3) and P(n), the space of symmetric positive definite matrices. Some basic results for bilinear systems on SE(3) with linear and quadratic measurements are also derived. Three examples—GPS attitude estimation, needle tip location, and vision-based robot end-effector pose estimation—are presented to illustrate the framework.

A genetic algorithm for the path planning problem of a mobile robot which is moving and picking up loads on its way is presented. Assuming a findpath problem in a graph, the proposed algorithm determines a near-optimal path solution using a bit-string encoding of selected graph vertices. Several simulation results of specific task-oriented variants of the basic path planning problem using the proposed genetic algorithm are provided. The results obtained are compared with ones yielded by hill-climbing and simulated annealing techniques, showing a higher or at least equally well performance for the genetic algorithm.

There is a high demand for developing effective controllers to perform fast and accurate operations for either flexible link manipulators (FLMs) or rigid link manipulators (RLMs). Thus, this paper is beneficial for such vast field, and it is also advantageous and indispensable for researchers who are interested in robotics to have sufficient knowledge about various controllers of FLMs and RLMs as the controllers’ concepts are elaborated in detail. The paper concentrates in critically reviewing classical controllers, intelligent controllers, robust controllers, and hybrid controllers for both FLMs and RLMs. The advantages and disadvantages of the aforementioned control methods are summarized in this paper; it also has a detailed comparison for the controllers in terms of the design difficulty, performance, and the suitability for controlling FLMs or RLMs.

Psychophysiological measurements, which serve as objective indicators of psychological state, have recently been introduced into human–robot interaction. However, their usefulness in haptic interaction is uncertain, since they are influenced by physical workload. This study analyses psychophysiological responses to a haptic task with three different difficulty levels and two different levels of physical load. Four physiological responses were recorded: heart rate, skin conductance, respiratory rate and skin temperature. Results show that mean respiratory rate, respiratory rate variability and skin temperature show significant differences between difficulty levels regardless of physical load and can be used to estimate cognitive workload in haptic interaction.

Robotic technology can be used in several ways to benefit people with disabilities. This paper describes the mounting of a robotic arm to a powered wheelchair to assist disabled users in daily activities. Although there are many potential benefits for the disabled user, there are also very strong requirements and compromises, which must be considered in integrating the robotic arm with the wheelchair. This paper focuses on how these integration issues have been addressed.

A computational algorithm is developed to find a dynamic motion trajectory of a mobile manipulator with flexible links and joints that will allow the robot to carry a maximum load between two specified end positions. A compact form of the linearized state space dynamic equations is organized as well as constraint equations. Then, the problem of finding a maximum load carrying capacity on flexible mobile manipulators is formulated as a trajectory optimization problem.

This paper presents theoretical and experimental investigations into the dynamic modelling and characterisation of a flexible manipulator system. A constrained planar single-link flexible manipulator is considered. A dynamic model of the system is developed based on finite element methods. The flexural and rigid dynamics of the system as well as inertia effects and structural damping are accounted in the model. Performance of the algorithm in describing the dynamic behaviour of the system is assessed in comparison to an experimental test-rig. Experimental results are presented for validation of the developed finite element model in the time and frequency domains.

In this paper, a novel control scheme is proposed to guarantee position and force tracking in nonlinear teleoperation systems subject to varying communication delays. Stability and tracking performance of the teleoperation system are proved using a proposed Lyapunov–Krasovskii functional. To show its effectiveness, the teleoperation controller is simulated on a pair of planar 2-DOF (degree of freedom) robots and experimented on a pair of 3-DOF PHANToM Premium 1.5A robots connected via a communication channel with time-varying delays. Both the planar robots in simulations and the PHANToM robots in experiments possess nonlinear dynamics.

With the increasing demands for versatile robotic platforms capable of performing a variety of tasks in diverse and uncertain environments, the needs for adaptable robotic structures have been on the rise. These requirements have led to the development of modular reconfigurable robotic systems that are composed of a numerous self-sufficient modules. Each module is capable of establishing rigid connections between multiple modules to form new structures that enable new functionalities. This allows the system to adapt to unknown tasks and environments. In such structures, coupling between modules is of crucial importance to the overall functionality of the system. Over the last two decades, researchers in the field of modular reconfigurable robotics have developed novel coupling mechanisms intended to establish rigid and robust connections, while enhancing system autonomy and reconfigurability. In this paper, we review research contributions related to robotic coupling mechanism designs, with the aim of outlining current progress and identifying key challenges and opportunities that lay ahead. By presenting notable design approaches to coupling mechanisms and the most relevant efforts at addressing the challenges of sensorization, misalignment tolerance, and autonomous reconfiguration, we hope to provide a useful starting point for further research into the field of modular reconfigurable robotics and other applications of robotic coupling.

In this paper a new prosthetic hand is presented that closely approximates the grasping abilities of a human hand. A large variety of different objects can be grasped reliably and the movements of the hand appear to natural. This five-finger hand has 15 degrees of freedom driven by small sized flexible fluidic actuators. The drives are within the fingers allowing a very compact and lightweight hand. Also, a concept for the control of different grasp types is presented. The characteristics of the new hand are illustrated.

This paper presents a control law for the tracking of a cyclic reference path by an under-actuated biped robot. The robot studied is a five-link planar biped. The degree of under-actuation is one during the single support phase. The control law is defined in such a way that only the geometric evolution of the biped configuration is controlled, but not the temporal evolution. To achieve this objective, we consider a parametrized control. When a joint path is given, a five degree of freedom biped in single support becomes similar to a one degree of freedom inverted pendulum. The temporal evolution during the geometric tracking is completely defined and can be analyzed through the study of a model with one degree of freedom. Simple analytical conditions, which guarantee the existence of a cyclic motion and the convergence towards this motion, are deduced. These conditions are defined on the reference trajectory path. The analytical considerations are illustrated with some simulation results.

This paper concerns the presentation and analysis of a type of three translational degrees of freedom (DoFs) parallel cube-manipulator. The parallel manipulators are the topology architectures of the DELTA robot and Tsai's manipulator, respectively, which have three translational DoFs. In the design, the three actuators are arranged according to the Cartesian coordinate system, which means that the actuating directions are normal to each other, and the joints connecting to the moving platform are located on three sides of a cube, for such reason we call this type of manipulator the parallel cube-manipulator. The kinematics problems, singularity, workspace, compliance characteristic of the manipulator are investigated in the paper. The analysis results show that the manipulators have the advantages of no singularities in the workspace, relatively more simple forward kinematics, and existence of a compliance center. The parallel cube-manipulator can be applied to the fields of micro-motion manipulators, remote center compliance (RCC) devices, assembly, and so on.

A new approach to the control of indirect simultaneous positioning of deformable objects is presented. Many manufacturing processes that deal with deformable objects such as clothes and rubber sheets involve a positioning of multiple points on a deformable object. The multiple points should be guided simultaneously to the desired locations. Moreover, these positioned points cannot be manipulated directly. This operation is referred to as indirect simultaneous positioning. In this article, we will propose a new control law for indirect simultaneous positioning of a deformable object based on its uncertain model and will show the robustness of the proposed control law. First, a simplified physical model of a deformable object is developed for its positioning operation. Second, indirect simultaneous positioning of an extensible object is formulated. Based on a linearized model of an extensible object, we will propose a novel control law for indirect simultaneous positioning. Next, we will prove the robustness of the proposed control law theoretically. Finally, experimental results will show the robustness of our proposed control law against the discrepancy between a real fabric and its uncertain model.