In this work, we propose the development and the corresponding stability analysis of a novel, observer-based output feedback (OFB), tracking controller for rigid-link robot manipulators. Specifically, a model-independent variable-structure-like observer in conjunction with a desired dynamic compensation technique have been utilized to remove the link velocity dependency of the controller formulation. Asymptotic stability of the observer--controller couple is then guaranteed via Lyapunov-based arguments. An adaptive controller extension is also presented to illustrate the expansiveness of the proposed scheme. Experimental studies performed on a two-link planar robot with dynamical uncertainties are included in order to demonstrate the performance and feasibility of the proposed method.

The paper considers the problem of motion planning and posture control of multiple n-link doubly nonholonomic mobile manipulators in an obstacle-cluttered and bounded workspace. The workspace is constrained with the existence of an arbitrary number of fixed obstacles (disks, rods and curves), artificial obstacles and moving obstacles. The coordination of multiple n-link doubly nonholonomic mobile manipulators subjected to such constraints becomes therefore a challenging navigational and steering problem that few papers have considered in the past. Our approach to developing the controllers, which are novel decentralized nonlinear acceleration controllers, is based on a Lyapunov control scheme that is not only intuitively understandable but also allows simple but rigorous development of the controllers. Via the scheme, we showed that the avoidance of all types of obstacles was possible, that the manipulators could reach a neighborhood of their goal and that their final orientation approximated the desired orientation. Computer simulations illustrate these results.

In this paper, the pick and place trajectory planning of a planar 3-RRR parallel manipulator is studied in the presence of joint clearance, which is one of the main sources of error in the positioning accuracy. Joint clearance can be modeled as a massless virtual link, with its direction determined from dynamic analysis. A 3–4–5 interpolating polynomial is used to plan the trajectories for the manipulator in the vertical and horizontal planes, in the presence of clearances. We compare the trajectories with those in the ideal cases, i.e., without clearances at the joints, and demonstrate that one can easily compensate for the errors in the trajectories by appropriate changes of the inputs. A similar method works for the compensation of the errors due to clearances at the joints, in trajectory planning of any parallel manipulator with any running speeds and payloads.

Adding active toe joints to a humanoid robot structure has lots of difficulties such as mounting a small motor and an encoder on the robot feet. Conversely, adding passive toe joints is simple, since it only consists of a spring and a damper. Due to lots of benefits of implementing passive toe joints, mentioned in the literature, the goal of this study is to add passive toe joints to the SURENA III humanoid robot which was designed and fabricated at the Center of Advanced Systems and Technologies (CAST), University of Tehran. To this end, a simple passive toe joint is designed and fabricated, at first. Then, stiffness and damping coefficients are calculated using a vision-based measurement. Afterwards, a gait planning routine for humanoid robots equipped with passive toe joints is implemented. The tip-over stability of the gait is studied, considering the vibration of the passive toe joints in swing phases. The multi-body dynamics of the robot equipped with passive toe joints are presented using the Lagrange approach. Furthermore, system identification routine is adopted to model the dynamic behaviors of the power transmission system. By adding the calculated actuating torques for these two models, the whole dynamic model of the robot is computed. Finally, the performance of the proposed approach is evaluated by several simulations and experimental results. Results show that using passive toe joints reduces energy consumption of ankle and knee joints by 15.3% and 9.0%, respectively. Moreover, with relatively large values of stiffness coefficients, the required torque and power of the knee and hip joints during heel-off motion reduces as the ankle joint torque and power increases.

This paper presents the design, kinematics, dynamics and control of a low-cost parallel rehabilitation robot developed at the Universitat Politècnica de Valencia. Several position and force controllers have been tested to ensure accurate tracking performances. An orthopedic boot, equipped with a force sensor, has been placed over the platform of the parallel robot to perform exercises for injured ankles. Passive, active-assistive and active-resistive exercises have been implemented to train dorsi/plantar flexion, inversion and eversion ankle movements. In order to implement the controllers, the component-based middleware Orocos has been used with the advantage over other solutions that the whole scheme control can be implemented modularly. These modules are independent and can be configured and reconfigured in both configuration and runtime. This means that no specific knowledge is needed by medical staff, for example, to carry out rehabilitation exercises using this low-cost parallel robot. The integration between Orocos and ROS, with a CAD model displaying the actual position of the rehabilitation robot in real time, makes it possible to develop a teleoperation application. In addition, a teleoperated rehabilitation exercise can be performed by a specialist using a Wiimote (or any other Bluetooth device).

Multi-robot formation control has become an important area of research due to its advantages and applications. This paper presents multi-robot formation control using a leader–follower approach without considering the leader's velocity information or estimation. The leader–follower formation is formulated by incorporating the model uncertainties and disturbances. A novel formation controller is presented using integral terminal sliding mode (ITSM) control, which drives the formation tracking error convergence to zero in finite-time. The stability of the close-loop control scheme is verified by using Lyapunov theory. Furthermore, obstacle detection and avoidance are incorporated to avoid collision while maintaining the formation. The effectiveness of the proposed controller is verified and validated using sine and lamniscate curve trajectories. Moreover, the performance of the proposed ITSM formation controller is compared with the standard linear sliding mode (LSM) control.

An underactuated mechanism is presented as a new finger design for improving grasp adaptability of LARM Hand fingers. Underactuation is discussed as a feasible solution through several design structures for finger adaptability to shape and size of objects to be grasped. The proposed underactuated solution for a new LARM finger is characterized through simulation results in ADAMS environment for operation feasibility and performance.

We present a novel framework for collision free assisted navigation of a semi-autonomous vehicle in complex unknown environments with moving and steady obstacles. In the proposed system, a semi-autonomous vehicle is guided by a human operator and an automatic reactive navigator. The autonomous reactive navigation block takes control from the human operator in situations where there is the danger of collision with obstacle. A mathematically rigorous analysis of the proposed approach is provided. The performance of the proposed assisted navigation system is demonstrated via experiments with a real semi-autonomous hospital bed and extensive computer simulations.

In this paper, we study the kinematic effects of number of legs in 6-DOF UPS parallel manipulators. A group of 3-, 4-, and 6-legged mechanisms are evaluated in terms of the kinematic performance indices, workspace, singular configurations, and forward kinematic solutions. Results show that the optimum number of legs varies due to priorities in kinematic measures in different applications. The non-symmetric Wide-Open mechanism enjoys the largest workspace, while the well-known Gough–Stewart (3–3) platform retains the highest dexterity. Especially, the redundantly actuated 4-legged mechanism has several important advantages over its non-redundant counterparts and different architectures of Gough–Stewart platform. It has dramatically less singular configurations, a higher manipulability, and at the same time less sensitivity. It is also shown that the forward kinematic problem has 40, 16, and 1 solution(s), respectively for the 6-, 3-, and the 4-legged mechanisms. Superior capabilities of the 4-legged mechanism make it a perfect candidate to be used in more challenging 6-DOF applications in assembly, manufacturing, biomedical, and space technologies.

FastSLAM 2.0 is a popular framework which uses a Rao-Blackwellized particle filter to solve the simultaneous localization and mapping problem. The sampling process is one of the most important phases in the FastSLAM 2.0 framework. Its estimation accuracy depends heavily on a correct prior knowledge about the control and observation noise statistics (the covariance matrices Q and R). Without the correct prior knowledge about these matrices, the estimation accuracy of the robot path and landmark positions may degrade seriously. However in many applications, the prior knowledge is unknown, or these noises are non-stationary. In this paper, these covariance matrices are supposed to be dynamic and denoted as Qt and Rt. Since there are noises, time-adjacent observations are inconsistent with each other. This inconsistency can reflect the real value of the covariance matrices. By the inconsistency, an extra step is introduced to the FastSLAM 2.0 framework. This step makes Qt and Rt match with their real value by using a particle swarm optimization method based on fractional calculus and alpha stable distribution (FC&ASD-PSO). Both simulation and experimental results show that the proposed algorithm improves the accuracy by the more accurate estimation on the noise covariance matrices.

This paper presents a generalization of the Compressed Extended Kalman Filter (CEKF) by introducing the definition of the compressed operation for Bayesian estimation processes and the definition of the Generalized Compressed Kalman Filter (GCKF). The GCKF extends the original definition of the CEKF, formerly introduced for treating a family of estimation problems, such as the Simultaneous Localization and Mapping (SLAM). The new proposed approach, the GCKF, is capable of treating problems that are more general than those of the original CEKF, such as estimation processes that involve certain stochastic Partial Differential Equation (SPDE) models. In addition to solving the SLAM and multi-agent SLAM problem in an efficient way, the GCKF can be applied to more general cases. As a proof of the capabilities of the new method for solving practical estimation problems, a multi-agent SLAM process is presented in the experimental section of this paper.

In reality, clearances in the joints are inevitable due to tolerances, and defects arising from design and manufacturing. Therefore, poor dynamic performance, reduction in components component lifetimes and generation of undesirable vibrations result in impacts of mating parts in the clearance joint. In this study, the dynamic behavior of a planar mechanism with revolute joints, in the presence of clearances is investigated. A continuous contact force model, based on elastic Hertz theory together with a dissipative term, is used to evaluate the contact forces here. Moreover, using a contact model, the effects of working speed and clearance size on the dynamic characteristics of a planar mechanical system are analyzed and compared. Furthermore, numerical results for a 3RRR planar parallel manipulator with six revolute clearance joints are presented.

This paper presents a method to calculate the fusing rule among three reactive behaviors, Wall Following, Corridor Following and Door Crossing, from place characterization for robot navigation. The technique is supported by a local grid of the closest area to the robot, which is built from sonar readings. The contour of this grid is extracted, represented by its FFT and, finally, it is reduced to a short feature vector with a principal component analysis (PCA). This feature vector is used to decide the fusing rule among the three behaviors. The algorithm is very fast in terms of its time performance, being then valid to be used in robot navigation, since the robot would rapidly react to new situations. It has also been successfully tested in simulated and real environments, with a Pioneer robot equipped with eight frontal sonar sensors, both in manually driven tasks and autonomous navigation tasks, proving its feasibility and effectiveness.

It is a challenging task for a human operator to manipulate a robot from a remote distance, especially in an unknown environment. Excellent teleoperation provides the human operator with a sense of telepresence, mainly including real-world vision, haptic perception, etc. This paper presents a novel virtual environment building method using the red–green–blue (RGB) colour information, the surface normal feature-based 3D-point-cloud registration method and the weighted sliding-average least-square-method-based real-world dynamic modelling for teleoperation. The experiments prove the method to be an accurate and effective means of teleoperation.

In this paper, a closed-form dynamic model of flexible manipulators is developed, based on the Newton–Euler formulation of motion equations of flexible links and on the adoption of the spatial vector notation. The proposed model accounts for two main innovations with respect to the state of the art: it is obtained in closed form with respect to the joints and modal coordinates (including the quadratic velocity terms) and motion equations of the whole manipulator can be computed for any arbitrary shape of the links and any possible link cardinality starting from the output of several commercial (finite element analysis) FEA codes. The Newton–Euler formulation of motion equations in terms of the joint and elastic variables greatly improves the simulation performances and makes the model suitable for real-time control and active vibration damping. The model has been compared with literature benchmarks obtained by the classical multibody approach and further validated by comparison with experiments collected on an experimental manipulator.

This paper proposes a computational model for selecting a suitable interlocutor of socially interactive robots in a situation interacting with multiple persons. To support this, a hybrid approach incorporating gaze control criteria and perceptual measurements for social cues is applied to the robot. For the perception part, representative non-verbal behaviors indicating human-interaction intent are designed based on the psychological analysis of human–human interaction, and these behavioral features are quantitatively measured by core perceptual components including visual, auditory, and spatial modalities. In addition, each aspect of recognition performance is improved through temporal confidence reasoning as a post-processing step. On the other hand, two factors of the physical space and conversational intimacy are tactically applied to the model calculation as a way of strengthening social gaze control effect of the robot. Interaction experiments with performance evaluation are given to verify that the proposed model is suitable to assess intended behaviors of individuals and perform gaze behavior about multiple persons. By showing a success rate of 93.3% in human decision-making criteria, it confirms a potential to establish socially acceptable gaze control in multiple-person interaction.

With rapid development of methods for dynamic systems modeling, those with less computation effort are becoming increasingly attractive for different applications. This paper introduces a new form of Kane's equations expressed in the matrix notation. The proposed form can efficiently lead to equations of motion of multi-body dynamic systems particularly those exposed to large number of nonholonomic constraints. This approach can be used in a recursive manner resulting in governing equations with considerably less computational operations. In addition to classic equations of motion, an efficient matrix form of impulse Kane formulations is derived for systems exposed to impulsive forces.

This paper presents an efficient approach for planning collision-free and dynamically feasible trajectories that enable a mobile robot to carry out tasks specified as regular languages over workspace regions. A sampling-based tree search is conducted over the feasible motions and over an abstraction obtained by combining the automaton representing the regular language with a workspace decomposition. The abstraction is used to partition the motion tree into equivalence classes and estimate the feasibility of reaching accepting automaton states from these equivalence classes. The partition is continually refined to discover new ways to expand the search. Comparisons to related work show significant speedups.

The neck is an important part of the body that connects the head to the torso, supporting the weight and generating the movement of the head. In this paper, a cable-driven parallel platform with a pneumatic muscle active support (CPPPMS) is presented for imitating human necks, where cable actuators imitate neck muscles and a pneumatic muscle actuator imitates spinal muscles, respectively. Analyzing the stiffness of the mechanism is carried out based on screw theory, and this mechanism is optimized according to the stiffness characteristics. While taking the dynamics of the pneumatic muscle active support into consideration as well as the cable dynamics and the dynamics of the Up-platform, a dynamic modeling approach to the CPPPMS is established. In order to overcome the flexibility and uncertainties amid the dynamic model, a sliding mode controller is investigated for trajectory tracking, and the stability of the control system is verified by a Lyapunov function. Moreover, a PD controller is proposed for a comparative study. The results of the simulation indicate that the sliding mode controller is more effective than the PD controller for the CPPPMS, and the CPPPMS provides feasible performances for operations under the sliding mode control.

Several non-holonomic Dubins-car-like robots travel over paths with bounded curvatures in a plane that contains an a priori unknown region. The robots are anonymous to one another and do not use communication facilities. Any of them has access to the current minimum distance to the region and can determine the relative positions and orientations of the other robots within a finite and given visibility range. We present a distributed navigation and guidance strategy under which every robot autonomously converges to the desired minimum distance to the region with always respecting a given safety margin, the robots do not collide with one another and do not get into clusters, and the entire team ultimately sweeps over the respective equidistant curve at a speed exceeding a given threshold, thus forming a kind of a sweeping barrier at the perimeter of the region. Moreover, this strategy provides effective sub-uniform distribution of the robots over the equidistant curve. Mathematically rigorous justification of the proposed strategy is offered; its effectiveness is confirmed by extensive computer simulations and experiments with real wheeled robots.