Biped walking can be regarded as a global limit cycle whose stability is difficult to verify by only local sensory feedback. This paper presents a control strategy combining global sensory reflex and leg synchronization. The inverted pendulum angle is utilized as global motion feedback to ensure global stability, and joint synchronization between legs is designed to stabilize bifurcations. The proposed strategy can achieve a stable gait and stabilize bifurcations. The robustness of this approach was evaluated against external disturbances. Walking experiments of a biped actuated by pneumatic muscles were conducted to confirm the validity of the proposed method. Instead of tracking predetermined trajectories, this method uses sensory reflexes to activate motor neurons and coincides with the biological idea wherein inessential degrees-of-freedom are barely controlled rather than strictly controlled.

Positioning and navigation data for unmanned surface vehicles (USVs) are extracted using the Global Positioning System (GPS) and the Inertial Navigation System (INS) integrated with an inertial measurement unit (IMU). The integration of quaternion with direction cosine matrix (DCM) with the aim of obtaining high accuracy with complete system independence has been effectively used to supply position and attitude information for autonomous navigation of marine crafts. A DCM integrated with a quaternion provided an advanced technique for precise USV attitude estimation and position determination using low-cost sensors. This paper presents the implementation of an INS developed by the integration of DCM and quaternion.

This paper proposes a novel parallel manipulator with 1 translational and 3 rotational degrees of freedom, which may be designed as the docking equipment for large-scale component assemblage in the aircraft industry. First, the mobility and kinematic analysis of the novel manipulator is performed using the screw theory and the closed-loop vector method. To evaluate the kinematic performance of the manipulator, its workspace is calculated, and the dimensional homogeneous Jacobian matrix of this manipulator is deduced. Mainly based on a nonlinear programming approach, the kinematic dimensional synthesis is performed to optimise the dimensional parameters of this novel parallel manipulator in a prescribed workspace. The results of this paper may lay a solid foundation for the prototype design and manufacture of the novel parallel manipulator.

This paper deals with the design of the control structure of a lower-limbs rehabilitation device in closed muscular chain called Sys-Reeduc. This control structure aims at providing a safe behavior to the user when performing rehabilitation exercises. It is based on two levels. The first level is concerned with the robust trajectory tracking of robotic device and has been the subject of previous studies. Nevertheless, it does not allow, by itself, the user to voluntarily drive the device. Therefore, a trajectory generator constituting the second level is presented in this paper to complete the whole control structure. This high-level control layer is described by a set of dedicated discrete state machines that provide the appropriate sequencing of elementary rehabilitation movements. These elementary movements are dynamically characterized so that clinician may choose the required trajectory parameters to adapt rehabilitation protocols and training to each individual. To realize a complete rehabilitation exercise, the sequence of elementary movements is triggered by thresholds relative to the measurement of the efforts applied by the user on the device. This allows the user to play an active role in its rehabilitation exercises and safely drive the machine at his/her own initiative. The design of the main exercises (isokinetic, isometric, and isotonic) used in the context of lower limbs rehabilitation is described, and simulation results illustrate the effectiveness of the proposed trajectory generator-based control approach.

Joints of space manipulators are usually simplified as torsional springs in modeling motion equations, and the nonlinear behaviors of the reducer in the joints are generally neglected. In this study, a dynamic model of a space manipulator that considers the joints that are transmitted through a typical 2K-H planetary gear reducer is developed using the Lagrangian method. The backlash clearances, gear tooth profile error, and time-variant meshing stiffness are integrated into the process. The simulation results show that the backlash clearances lead to the accumulation of positioning errors in the space manipulator when the joints rotate back and forth. The tooth profile error is the main cause of severe acceleration fluctuations and meshing force impacts. These fluctuations influence torque instability, which may accelerate gear system failure.

Previous research has revealed that foot rotation of the supporting foot in a single support phase could increase walking speed. This paper presents a method for force-controlled bipeds to realize foot rotation by breaking the kinematic contact constraint between the supporting foot and the ground. An inverse dynamics controller is proposed to make the biped model controllable even when the constraint is broken. In addition, a linear inverted pendulum model is extended to make its ZMP adjustable so that the ZMP can be predefined as required. When the planned ZMP is in the toe, the kinematic contact constraint will be broken and foot rotation can be achieved. A walking simulation demonstrates the effectiveness of the proposed method.

This paper formulates a new scalable algorithm for motion planning and control of multiple point-mass robots. These autonomous robots are designated to move safely to their goals in a priori known workspace cluttered with fixed and moving obstacles of arbitrary positions and sizes. The control laws proposed for obstacle and collision avoidance and target convergence ensure that the equilibrium point of the given system is asymptotically stable. Computer simulations with the proposed technique and applications to a team of two planar (RP) manipulators working together in a common workspace are presented. Also, the robustness of the system in the presence of noise is verified through simulations.

The issue of the operation method for dual-arm rescue construction machinery is investigated in this paper. To increase its operational efficiency and to save more time at rescue sites, some operating strategies of the human arm are employed to design a novel operation method for construction machinery. On the basis of that, a novel and anthropomorphic task-motion planning and performing framework for rescue construction machinery is established. Firstly, the main tasks construction machinery encounter are summarized, and then, these tasks are decomposed to several manipulation and movement sequences. Finally, several frequently used movements, which consist of some basic movement elements, are designed to be intuitive movement primitives coordinating related movement elements simultaneously to improve the operational efficiency, which forms a novel operation method for rescue construction machinery. Additionally, in order to avoid the potential collision between the dual arms, a self-collision avoidance surveillance method is proposed to guarantee the safety of the novel operation method. An application case is presented to introduce the proposed method specifically, and a typical simulation of a dual-arm grip-and-cut task is carried out to verify the feasibility and effectiveness of the framework.

Characters encountered in daily environments provide valuable information to human beings and potentially to automated machines. This paper describes the use of character information by robots working in daily environments. Our robot system finds and reads character strings by virtue of a recognition module that detects character candidates as closed contours in an image. The closed-contour-based method enables detection of various character strings observed from different viewpoints. To cope with tiny and distant characters, the image processing is collaborated with a camera system having a mechanical gaze adjustment. By combining the detection result with an optical character reader, the autonomous robot can provide daily assistance to humans.

In this paper, a novel scheme is presented to conquer the motion-planning problem for autonomous space robots. Minimizing the consumed energy of atomic batteries within the daily planetary missions of robot on the planet is taken into account, i.e., utilization of the generated solar power by its embedded photocells leads to saving energy of batteries for night missions. Aforementioned objective could be acquired by appropriate interaction of motion planning paradigm with shadows of obstacles. Modeling of the shadow with the proposed artificial potential field leads to generalize the concept of potential fields not only for static and dynamic obstacles but also for being confronted with the intrinsic time-variant phenomena such as shadows. With due attention to the noticeable computational complexity of the introduced strategy, fuzzy techniques are applied to optimize the sampling times effectively. To accomplish this objective, a smart control scheme based on the fuzzy logic is mounted to the primitive version of algorithm. Regarding the need to identify some structural parameters of obstacles, PIONEER™ mobile robot is designed as a test bed for the verification of simulated results. Investigation on empirical accomplishments shows that the goal-oriented definition of Time–Variant Artificial Potential Fields is able to resolve the motion-planning problem in planetary applications.

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.

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.

Recently, small-sized compact electric vehicles have been in demand for short-distance travel in urban areas, although battery charging in electric vehicles present in the market is still problematic. Borrowing from the concept of a mobile inverted pendulum system, in this paper, a two-wheel robotic vehicle system is implemented and controlled as the future personal transportation device called the TransBOT. The TransBOT has two driving modes: a regular vehicle mode, where stable contact on the ground is maintained by two wheels and two casters, and the balancing mode, which maintains the stable posture with two wheels on the ground. The two-wheel balancing mechanism can be used as a transportation vehicle in narrow and busy urban areas. Gain scheduling control methods based on linear controllers are used for different drivers. In addition, desired balancing angles are specified for the different sizes of drivers in order to have a stable balancing control performance. These desired balancing angle values have been found by empirical studies. Experimental studies with drivers of different weights, as well as indoor and outdoor driving tasks, were conducted to ensure the feasibility of TransBOT.