It is well known that the use of multi-rate control techniques have improved the performance of many systems in general, and robotic systems, in particular. The main contribution of this paper is the generalization of the Reference Filtering control strategy from a dual-rate point of view, improving its inherent properties by overcoming the problem of sensor latency. In the paper, we discuss and analyze the improvements introduced by the novel dual-rate reference filtering control strategy in terms of convergence time, reachability and robustness. More specifically, we discuss the capability to solve positioning tasks, when hardware limitations are present with large sampling rates. In addition, a comparison is made between the single-rate and the proposed dual-rate control strategies to prove the advantages of the latter approach. A complete set-up has been prepared for validation, including a six degree of freedom (DOF) industrial manipulator, a smart camera and embedded hardware used as a high level controller.

This paper investigates the vision-based pose stabilization of an electrically driven nonholonomic mobile robot with parametric uncertainties in robot kinematics, robot dynamics, and actuator dynamics. A robust adaptive visual stabilizing controller is proposed with the utilization of adaptive control, backstepping, and dynamic surface control techniques. For the controller design, the idea of backstepping is used and the adaptive control approach is adopted to deal with all uncertainties. We also apply the dynamic surface control method to avoid the repeated differentiations of virtual controllers existing in the backstepping design procedure such that the control development is easier to be implemented. Moreover, to attenuate the effect of disturbances on control performance, smooth robust compensators are exploited. It is proved that all signals in the closed-loop system can be guaranteed to be uniformly ultimately bounded. Finally, simulation results are presented to illustrate the performance of the proposed controller.

The N-3 Revolute-Prismatic-Spherical (N-3RPS) manipulator is a kind of serial-parallel manipulator and has higher stiffness and accuracy compared with serial mechanisms, and a larger workspace compared with parallel mechanisms. The locking mechanism in each joint allows the manipulator to be controlled by only three wires. Modeling the dynamics of this manipulator presents an inherent complexity due to its closed-loop structure and kinematic constraints. In the first part of this paper, the inverse kinematics of the manipulator, which consists of position, velocity, and acceleration, is studied. In the second part, the inverse and forward dynamics of the manipulator is formulated based on the principle of virtual work and link Jacobian matrices. Finally, the numerical example is presented for some trajectories.

Inertia strongly influences the dynamic performance of parallel manipulators, and ignorance of inertia is apt to result in negative phenomena such as vibrations, overshoot, and slow response. This study analyzes the inertia-decoupling characteristic of Stewart platform. Because the inertia matrix of the Stewart platform is usually non-diagonal, inertia coupling occurs between its legs. Herein, decoupling to inertia is implemented, and independent control channels are determined. The influence of decoupled inertia on the control system is analyzed using the Adams simulation software, and the inertia index of the Stewart platform is proposed. Experiments are conducted on a prototype of the Stewart platform to verify the eigenvalue characteristic of decoupled inertia. The distribution of inertia index in the operational workspace is provided, and the influence of dimensional parameters on inertia index is discussed. Finally, dimensional optimization is realized with a set of optimized dimensions for good dynamic performance.

The goal of this research is to develop a low-cost face robot which has a lower degree-of-freedom facial expression mechanism. Many designs of facial robots have been announced and published in the past. Face robots can be classified into two major types based on their respective degrees of freedom. The first type has various facial expressions with higher degrees of freedom, and the second has finite facial expressions with fewer degrees of freedom. Due to the high cost of the higher-degree-of-freedom face robot, most commercial face robot products are designed in the lower-degrees-of-freedom form with finite facial expressions. Therefore, a face robot with a simplified facial expression mechanism is proposed in this research. The main purpose of this research is to develop a device with a lower degree-of-freedom mechanism that is able to generate many facial expressions while keeping one basic mouth shape variation. Our research provides a new face robot example and development direction to reduce costs and conserve energy.

Singularities have a great influence on kinematics and dynamics of both serial and parallel robots. In order to prevent a robot from entering singular configurations, it needs to measure the “distance” between the robot current configuration and the singular configuration. This paper presents a novel approach based on characteristic angles to measure closeness to singularities. For the problem of inconsistent dimensions in the scalar product of screws, the physical meanings of twists and wrenches are reinterpreted. For the problem of the metric invariant to origin selection, the origin of the screw frame is required to coincide with the origin of the robotic tool frame. The major merit of the proposed metric lies in the identical result of measuring similar mechanisms with different sizes. Moreover, the measurement is insensitive to screw magnitude, since the metric expression is dimensionless. Furthermore, the geometrical meaning of the determinant of a screw matrix is clarified.

In this paper, the forward kinematic analysis of 3-degree-of-freedom planar parallel robots with identical limb structures is presented. The proposed algorithm is based on Study's kinematic mapping (E. Study, “von den Bewegungen und Umlegungen,” Math. Ann.39, 441–565 (1891)), resultant method, and the Gröbner basis in seven-dimensional kinematic space. The obtained solution in seven-dimensional kinematic space of the forward kinematic problem is mapped into three-dimensional Euclidean space. An alternative solution of the forward kinematic problem is obtained using resultant method in three-dimensional Euclidean space, and the result is compared with the obtained mapping result from seven-dimensional kinematic space. Both approaches lead to the same maximum number of solutions: 2, 6, 6, 6, 2, 2, 2, 6, 2, and 2 for the forward kinematic problem of planar parallel robots; 3-RPR, 3-RPR, 3-RRR, 3-RRR, 3-RRP, 3-RPP, 3-RPP, 3-PRR, 3-PRR, and 3-PRP, respectively.

This paper investigates a 6-degree-of-freedom foldable parallel mechanism for the ship-based stabilized platform, which is driven by closed chain linkages. The velocity and acceleration mappings between the moving platform and inputs of the closed chain linkages are deduced in the form of the first- and second-order influence coefficient matrices. The continuous stiffness matrix is deduced; furthermore, the translation and rotational stiffness along any direction are also deduced. With directional stiffness, the singularity of the mechanism is analyzed, and the explanation of the singularity is given from the viewpoint of stiffness. The directions the platform cannot move or lose its constraints are got from directional stiffness.

This paper presents a new approach to accurately track a moving vehicle with a multiview setup of red–green–blue depth (RGBD) cameras. We first propose a correction method to eliminate a shift, which occurs in depth sensors when they become worn. This issue could not be otherwise corrected with the ordinary calibration procedure. Next, we present a sensor-wise filtering system to correct for an unknown vehicle motion. A data fusion algorithm is then used to optimally merge the sensor-wise estimated trajectories. We implement most parts of our solution in the graphic processor. Hence, the whole system is able to operate at up to 25 frames per second with a configuration of five cameras. Test results show the accuracy we achieved and the robustness of our solution to overcome uncertainties in the measurements and the modelling.

An underactuated mechanical system is generally a good test bed for advanced nonlinear controllers and can be applied to design a novel mechanical system with better energy efficiency and good controllability. It has been shown that the dynamics of many underactuated mechanical systems could be transformed into the chained canonical form. To improve the performance of the controllers presented in the literature, a novel controller design method is proposed in this paper. It is shown that the set-point stabilization problem of the second-order chained form systems can be changed into a trajectory-tracking problem based on the nonsmooth Hölder continuous feedback. By designing the tracked trajectory, the presented controller permits the achievement of exponential stability. Some numerical simulations demonstrate the stability of the proposed controller for an underactuated Hovercraft system.

This paper presents what is termed as the supervoxel normal distributions transform (SV-NDT), a novel three-dimensional (3-D) registration algorithm which improves the performance of the three-dimensional normal distributions transform (3-D NDT) significantly. The 3-D NDT partitions a model scan using a 3-D regular grid. Generating normal distributions using the 3-D regular grid causes considerable information loss because the 3-D regular grid does not use any information pertaining to the local surface structures of the model scan. The best type of surface (the constituent unit of each scan) for modeling with one normal distribution is known to be the plane. The SV-NDT reduces the loss of information using a supervoxel-generating algorithm at the partitioning stage. In addition, it uses the information of the local surface structures from the data scan by replacing the Euclidean distance with a function that uses local geometries as well as the Euclidean distance when each point in the data scan is matched to the corresponding normal distribution. Experiments demonstrate that the use of the supervoxel-generating algorithm increases the modeling accuracy of the normal distributions and that the proposed 3-D registration algorithm outperforms the 3-D NDT and other widely used 3-D registration algorithms in terms of robustness and speed on both synthetic and real-world datasets. Additionally, the effect of changing the function to create correspondences is also verified.

The Tangent Bundle Rapidly Exploring Random Tree (TB-RRT) is an algorithm for planning robot motions on curved configuration space manifolds, in which the key idea is to construct random trees not on the manifold itself, but on tangent bundle approximations to the manifold. Curvature-based methods are developed for constructing tangent bundle approximations, and procedures for random node generation and bidirectional tree extension are developed that significantly reduce the number of projections to the manifold. Extensive numerical experiments for a wide range of planning problems demonstrate the computational advantages of the TB-RRT algorithm over existing constrained path planning algorithms.

This paper presents a method to improve the speed and accuracy rate for space robot visual target recognition based on illumination and affine invariant feature extraction. The method takes illumination changes, strong nonlinear light due to refraction and reflection, target affine transformation and occlusion into consideration, all of which occur on the cabin target surface and affect the target recognition accuracy seriously. In this paper, a method is proposed to capture a same target at multi-viewpoints to establish feature library for high recognition accuracy and speed at any viewpoint. By using an analysis of the light intensity and gray level transformation, we obtain the corrected image which reduce the influence of illumination change. Then the affine moment invariants features of the correction images at multi-viewpoints were extracted and the average feature datum were stored in the library. To verify the validity of the method, a robot vision system provided images, followed by image preprocessing, dynamic local threshold segmentation and feature extraction. These methods were verified on a target recognition system of space robot built for this research. The experimental results showed that the methods were feasible and effective.

Robots running on water have attracted the attention of researchers in the last decades as an alternative to conventional aquatic propulsion mechanisms. Up to now, a large scale robot capable of running on water has not been realized. Bouncing on water is a prerequisite for running on water. For this reason, the development of a water bouncing robot represents a necessary first step. The paper presents the model of a 2-degree-of-freedom water bouncing robot inspired by the pogo-stick, a device for jumping off the ground in a standing position. An analytical model of the impact force between “robot's foot” and water is provided for both water-entry and water-exit phases. Such a model has been integrated in a dynamic simulation of whole robot. The model represents a useful and general framework to gain an insight into the parameters that characterize the efficiency of robot.

This paper deals with the stiffness analysis of multibody systems using the Matrix Structural Analysis—MSA. This methodology allows us to obtain the stiffness matrix of the structure from the stiffness properties of each element. First the MSA method is described and its application is detailed using an L-structure in order to make easy its understanding. Numerical and experimental results obtained for the L-structure and a 6-RSS parallel manipulator, follow to prove the validity of the methodology.

This paper presents adaptive impedance controllers with adaptive sliding mode friction compensation for anthropomorphic artificial hand. A five-fingered anthropomorphic artificial hand with multi-sensory and Field-Programmable Gate Arra (FPGA)-based control hardware and software architecture is designed to fulfill the requirements of the grasping force controller. In order to improve the force-tracking precision, the indirect adaptive algorithm was applied to estimate the parameters of the environment. The generalized momentum-based disturbance observer was applied to estimate the contact force from the torque sensor. Based on the sensors of the finger, an adaptive sliding mode friction compensation algorithm was utilized to improve the accuracy of the position control. The performances of the force-tracking impedance controller and position-based joint impedance control for the five-fingered anthropomorphic artificial hand are analyzed and compared in this paper. Furthermore, the performances of the force-tracking impedance controller with environmental parameters adaptive estimation and without environmental parameters estimation are analyzed and compared. Experimental results prove that accurate force-tracking and stable torque/force response under uncertain environments of unknown stiffness and position can be achieved with the proposed adaptive force-tracking impedance controller with friction compensation on five-finger artificial hand.

This paper introduces the design and the optimization of a probe holder robot for tele-echography applications. To define its kinematic architecture, an approach based on motion capture of an expert's gestures during ultrasound examinations was proposed. The medical gestures analyzed consisted of ultrasound probe movements and were used to characterize the kinematic specifications of the proposed manipulator. The selected architecture was a Spherical Parallel Mechanism (SPM) with 3 degrees of freedom (DoF) and its optimal synthesis was performed using real-coded Genetic Algorithms (GA). The optimization criteria and constraints were established thanks to the collaboration of medical experts and were successively formulated and solved using mono-objective and multi-objective functions.

A distributed control mechanism for ground moving nonholonomic robots is proposed. It enables a group of mobile robots to autonomously manage formation shapes while navigating through environments with obstacles. The mechanism consists of two stages, with the first being formation control that allows basic formation shapes to be maintained without the need of any inter-robot communication. It is followed by obstacle avoidance, which is designed with maintaining the formation in mind. Every robot is capable of performing basic obstacle avoidance by itself. However, to ensure that the formation shape is maintained, formation scaling is implemented. If the formation fails to hold its shape when navigating through environments with obstacles, formation morphing has been incorporated to preserve the interconnectivity of the robots, thus reducing the possibility of losing robots from the formation.

The algorithm has been implemented on a nonholonomic multi-robot system for empirical analysis. Experimental results demonstrate formations completing an obstacle course within 12 s with zero collisions. Furthermore, the system is capable of withstanding up to 25% sensor noise.

We present a novel motorized semi-autonomous mobile hospital bed guided by a human operator and a reactive navigation algorithm. The proposed reactive navigation algorithm is launched when the sensory device detects that the hospital bed is in the potential danger of collision. The semi-autonomous hospital bed is able to safely and quickly deliver critical neurosurgery (head trauma) patients to target locations in dynamic uncertain hospital environments such as crowded hospital corridors while avoiding en-route steady and moving obstacles. We do not restrict the nature or the motion of the obstacles, meaning that the shapes of the obstacles may be time-varying or deforming and they may undergo arbitrary motions. The only information available to the navigation system is the current distance to the nearest obstacle. Performance of the proposed navigation algorithm is verified via theoretical studies. Simulation and experimental results also confirm the performance of the reactive navigation algorithm in real world scenarios.

Spinal surgery is considered a high-risk surgery. To improve the accuracy, stability, and safety of such operations, we report the development of a novel six-degrees-of-freedom Robotic Spinal Surgical System that can assist surgeons in performing transpedicular surgery, one of the most common spinal surgeries. After optimization performed using Response Surface Methodology, the largest available workspace of the robot is determined and is found to easily cover the entire operation area. Cooperative control and navigation-based active control are implemented for different processes of the operation. We propose a hybrid control approach based on the speed and torque interface at the joint level. In this mode, the robot is compliant in Cartesian space, benefitting both the accuracy and efficiency of the operation. A comprehensive assessment index, combining the subjective and objective criteria in terms of positioning and operation efficiency, is proposed to compare the performance of cooperative control in speed mode, torque mode, and hybrid control mode. Active fine adjustment experiments are carried out to verify the positioning accuracy, and the results are found to satisfy the requirements of operation. As an application example, a pedicle screw insertion experiment is performed on a pig vertebral bone, demonstrating the effectiveness of our system.