This paper presents a model-based approach for the first time to identify the crack location for the hinge-based planar RRR compliant mechanism, a parallel micro-motion stage driven by piezoelectric (PZT) actuators. However, cracks more likely occur on a flexure hinge because it usually undergoes a periodic deformation in service, which eventually compromises mechanism's performance, positioning accuracy for instance. In this work, the pseudo-rigid-body method is used to develop kinematic and dynamic models of the RRR mechanism both in healthy and damaged conditions, where the crack is considered in terms of the rotational compliance of a flexible hinge. The crack location is determined by measuring PZT elongations, which represents the driving toque deviation because of the crack presence. Numerical simulation is conducted to verify the proposed approach, and the results show good match of the identified crack location with the assumed location. Finally, experiments on the RRR mechanism with a prefabricated crack is performed to further validate the proposed models; the experimental results yield a good consistence.

The hyper-redundant manipulators are suitable for working in the constrained on-orbit servicing environment due to the extreme flexibility. However, its modelling and control are very challenging due to the characteristics of non-linearity and strong coupling. In this paper, considering the multi-level mapping among the motors, cables, joints, and end-effector, a proportional derivative (PD) with dynamic feedforward compensation control system is designed. The corresponding control system is divided into five parts: controller, planner, actuator, manipulator, and sensor. The actual control torque consisting of the desired feedforward torque and the feedback torque is generated by the controller. In order to improve the tracking accuracy and maintain rapid response, the torque, which is calculated by the dynamics model of the traditional joint-driven manipulator, is regarded as the desired feedforward torque. The parameters of interest are the angle and velocity of the universal joint and motors. The planner plans and converts the desired parameters of the universal joint to corresponding motors. Combining with the feedback angles and velocities signals of the corresponding motors, the feedback torque can be calculated by the PD control module. Finally, typical cases of six universal joints (12DOFs) manipulators are simulated and experimented. The results demonstrate that the method is very efficient for controlling spatial cable-driven hyper-redundant manipulators.

The purpose of this study is to determine the dynamic load carrying capacity (DLCC) of a manipulator that moves on the specified path using a new closed loop optimal control method. Solution methods for designing nonlinear optimal controllers in a closed-loop form are usually based on indirect methods, but the proposed method is a combination of direct and indirect methods. Optimal control law is given by solving the nonlinear Hamilton–Jacobi–Bellman (HJB) partial differential equation. This equation is complex to solve exactly for complex dynamics, so it is solved numerically using the Galerkin procedure combined with a nonlinear optimization algorithm. To check the performance of the proposed algorithm, the simulation is performed for a fixed manipulator. The results represent the efficiency of the method for tracking the pre-determined path and determining the DLCC. Finally, an experimental test has been done for a two-link manipulator and compare with simulation results.

A time-optimal problem for redundantly actuated robots moving on a specified path is a challenging problem. Although the problem is well explored and there are proposed solutions based on phase plane analysis, there are still several unresolved issues regarding calculation of solution curves. In this paper, we explore the characteristics of the maximum velocity curve and propose an efficient algorithm to establish the solution curve. Then we propose a straightforward method to calculate the maximum or minimum possible acceleration on the path based on the pattern of saturated actuators, which substantially reduces the computational cost. Two numerical examples are provided to illustrate the issues and the solutions.

The article presents the experimental evaluation of an integrated approach for path following and obstacle avoidance, implemented on wheeled robots. Wheeled robots are widely used in many different contexts, and they are usually required to operate in partial or total autonomy: in a wide range of situations, having the capability to follow a predetermined path and avoiding unexpected obstacles is extremely relevant. The basic requirement for an appropriate collision avoidance strategy is to sense or detect obstacles and make proper decisions when the obstacles are nearby. According to this rationale, the approach is based on the definition of the path to be followed as a curve on the plane expressed in its implicit form f(x, y) = 0, which is fed to a feedback controller for path following. Obstacles are modeled through Gaussian functions that modify the original function, generating a resulting safe path which – once again – is a curve on the plane expressed as f′(x, y) = 0: the deformed path can be fed to the same feedback controller, thus guaranteeing convergence to the path while avoiding all obstacles. The features and performance of the proposed algorithm are confirmed by experiments in a crowded area with multiple unicycle-like robots and moving persons.

Ditch crossing is one of the essential capabilities required for a biped robot in disaster management and search and rescue operations. Present work focuses on crossing a wide ditch with landing uncertainties by an under-actuated planar biped robot with five degrees of freedom. We consider a ditch as wide for a robot when the ankle to ankle stretch required to cross it is at least equal to the leg length of the robot. Since locomotion in uncertain environments requires real-time planning, in this paper, we present a new approach for generating real-time joint trajectories using control constraints not explicitly dependent on time, considering impact, dynamic balance, and friction. As part of the approach, we introduce a novel concept called the point of feasibility for bringing the biped robot to complete rest at the end of ditch crossing. We present a study on the influence of initial posture on landing impact and net energy consumption. Through simulations, we found the best initial postures to efficiently cross a wide ditch of width 1.05 m, with less impact and without singularities. Finally, we demonstrate the advantage of the proposed approach to cross a wide ditch when the surface friction is not same on both sides of the ditch.

Pick-and-place applications need to perform rigid body displacements that combine translations along three independent directions and rotations around one fixed direction (Schoenflies motions). Such displacements constitute a four-dimensional (4-D) subgroup (Schoenflies subgroup) of the 6-D displacement group. The four-degrees of freedom (dof) manipulators whose end effector performs only Schoenflies motions are named Schoenflies-motion generators (SMGs). The most known SMGs are the serial robots named SCARA. In the literature, parallel manipulators (PMs) have also been proposed as SMGs. Here, a novel single-loop SMG of type 2PRPU is studied. Its position analysis, singularity loci and workspace are addressed to provide simple analytic and geometric tools that are useful for the design. The proposed single-loop SMG is not overconstrained, its actuators are on or near the base and its end effector can perform a complete rotation. These features solve the main drawbacks that parallel SMG architectures have in general and make the proposed SMG a valid design alternative.

Saturation nonlinearities, among the known challenges in control engineering, are ubiquitous in robotic systems and can lead to stability and performance degradation. In this paper, an adaptive dynamic surface impedance (ADSI) control approach is developed for an n-link robotic manipulator by employing self-recurrent wavelet neural networks (SRWNNs) in order to overcome the saturation effect. The proposed control approach is inspired by the theory of dynamic surface control (DSC) and SRWNNs. As a novel application of the dynamic surface method to obtain a simple structure, the target impedance is formulated in the state–space, and effective dynamic surfaces are defined to track the desired impedance behavior. In fact, DSC is used to force the robot manipulator to track the desired impedance, while the robot interacts with an environment. In addition, SRWNNs are applied to approximate the parametric uncertainties and external disturbances in the robot dynamical model. Self-feedback neurons are embedded as memory units in SRWNNs to model the sudden dynamic jumps of the environment. Using Lyapunov's method, an ADSI controller is designed, and adaptation laws are induced to guarantee the stability of the closed-loop system. Finally, simulations are conducted to verify the proper performance of the proposed approach for removing the saturation effect and tracking the target impedance. It is worth noting that the simulation results indicate the robustness of the controller against uncertainties and external disturbances.

In this paper, we present a new leader–follower type solution to the translational maneuvering problem for formations of multiple, non-holonomic wheeled mobile robots. The solution is based on the graph that models the coordination among the robots being a spanning tree. Our control law incorporates two types of position errors: individual tracking errors and coordination errors for leader–follower pairs in the spanning tree. The control ensures that the robots globally acquire a given planar formation while the formation as a whole globally tracks a desired trajectory, both with uniformly ultimately bounded errors. The control law is first designed at the kinematic level and then extended to the dynamic level. In the latter, we consider that parametric uncertainty exists in the equations of motion. These uncertainties are accounted for by employing an adaptive control scheme. The main contributions of this work are that the proposed control scheme minimizes the number of control links and global position measurements, and accounts for the uncertain vehicle dynamics. The proposed formation maneuvering controls are demonstrated experimentally and numerically.