This paper proposes a robot navigation scheme using wireless visual sensors deployed in an environment. Different from the conventional autonomous robot approaches, the scheme intends to relieve massive on-board information processing required by a robot to its environment so that a robot or a vehicle with less intelligence can exhibit sophisticated mobility. A three-state snake mechanism is developed for coordinating a series of sensors to form a reference path. Wireless visual sensors communicate internal forces with each other along the reference snake for dynamic adjustment, react to repulsive forces from obstacles, and activate a state change in the snake body from a flexible state to a rigid or even to a broken state due to kinematic or environmental constraints. A control snake is further proposed as a tracker of the reference path, taking into account the robot's non-holonomic constraint and limited steering power. A predictive control algorithm is developed to have an optimal velocity profile under robot dynamic constraints for the snake tracking. They together form a unified solution for robot navigation by distributed sensors to deal with the kinematic and dynamic constraints of a robot and to react to dynamic changes in advance. Simulations and experiments demonstrate the capability of a wireless sensor network to carry out low-level control activities for a vehicle.

In the human body there are many joints whose functions are very similar to revolute joints. To avoid the complexity of these joints, they are usually substituted by revolute joints in many humanoid robots. Revolute joints have purely rotational motion along their fixed axis, while real joints in the human body have Instantaneous Rotational Axis (IRA) due to their configuration. Substitution of this kind of human joints with revolute (hinge) joints in robots changes the kinematics of joints. Knowing the exact characteristics of the moving axis of rotation in human joints is a prerequisite for the kinematic study of a joint. Here the main geometrical difference between these kinds of joints in humans and their simplified (hinge-like) models in robots is described. Then, as a case study, the mechanism of the three joints of the index finger are compared with their hinge-like model using a multi-body code to understand when revolute joints can be substituted for anthropometric joints in hand exoskeletons and robotic hands. Furthermore, the position of IRA and its distance from the center of the condyle of the joint are presented. The concept and the results can be extended for other fingers and all similar joints, and can be used in humanoid robots, hand exoskeletons and robotic hands.

A novel rigid-body control design methodology for 6-degree-of-freedom (dof) parallel kinematic mechanisms (PKMs) is proposed. The synchronous control of PKM joints is addressed through a novel formulation of contour and lag errors. Robust performance as a control specification is addressed. A convex combination controller design approach is applied to address the problem of simultaneously satisfying multiple closed-loop specifications. The applied dynamic modeling approach allows the design methodology to be extended to 6-dof spatial PKMs. The methodology is applied to the design of a 6-dof PKM-based meso-milling machine tool and simulations are conducted.

A robot mapping procedure using a modified speeded-up robust feature (SURF) is proposed for building persistent maps with visual landmarks in robot simultaneous localization and mapping (SLAM). SURFs are scale-invariant features that automatically recover the scale and orientation of image features in different scenes. However, the SURF method is not originally designed for applications in dynamic environments. The repeatability of the detected SURFs will be reduced owing to the dynamic effect. This study investigated and modified SURF algorithms to improve robustness in representing visual landmarks in robot SLAM systems. Many modifications of the SURF algorithms are proposed in this study including the orientation representation of features, the vector dimension of feature description, and the number of detected features in an image. The concept of sparse representation is also used to describe the environmental map and to reduce the computational complexity when using extended Kalman filter (EKF) for state estimation. Effective procedures of data association and map management for SURFs in SLAM are also designed to improve accuracy in robot state estimation. Experimental works were performed on an actual system with binocular vision sensors to validate the feasibility and effectiveness of the proposed algorithms. The experimental examples include the evaluation of state estimation using EKF SLAM and the implementation of indoor SLAM. In the experiments, the performance of the modified SURF algorithms was compared with the original SURF algorithms. The experimental results confirm that the modified SURF provides better repeatability and better robustness for representing the landmarks in visual SLAM systems.

In order to obtain a more human-like walking and less energy consumption, a it foot rotation phase is considered in the single support phase of a 3D biped robot, in which the stance heel lifts from the ground and the stance foot rotates about the toe. Since there is no actuation at the toe, a walking phase of the robot is composed of a fully actuated phase and an under-actuated phase. The objective of this paper is to present an asymptotically stable walking controller that integrates these two phases. To get around the under-actuation issue, a strict monotonic parameter of the robot is used to describe the reference trajectory instead of using the time parameter. The overall control law consists of a zero moment point (ZMP) controller, a swing ankle rotation controller and a partial joint angles controller. The ZMP controller guarantees that the ZMP follows the desired ZMP. The swing ankle rotation controller assures a flat-foot impact at the end of the swinging phase. Each of these controllers creates two constraints on joint accelerations. In order to determine all the desired joint accelerations from the control law, a partial joint angles controller is implemented. A word “partial” emphasizes the fact that not all the joint angles can be controlled. The outputs controlled by a partial joint angles controller are defined as a linear combination of all the joint angles. The most important question addressed in this paper is how this linear combination can be defined in order to ensure walking stability. The stability of the walking gait under closed-loop control is evaluated with the linearization of the restricted Poincaré map of the hybrid zero dynamics. Finally, simulation results validate the effectiveness of the control law even in presence of initial errors and modelling errors.

This paper proposes a new effective kinematics method based on the dynamic visual window (DVW) for a surgical robot that is equipped with two instrument arms and one laparoscope arm, to enable doctors to achieve operations with their visual habits under the laparoscopic visual environment. The problem of the consistency principle between the doctor's operations under the visual window's feedback and the master–slave operations of the surgical robot is solved. The kinematics models of the surgical robotic arms are established, and the new kinematics methods based on the DVW of the laparoscope and instrument arms are proposed according to their inverse kinematics with respect to the visual coordinate system. Finally, the proposed kinematics method is verified by simulation experiments based on the theoretical algorithm and the mechanism model; the multiple sets of the simulation data are presented to illustrate the correctness and feasibility of the new method in this research.

Navigating along a set of programmed points in a completely unknown environment is a challenging task which mostly depends on the way the robot perceives and symbolizes the environment and decisions it takes in order to avoid the obstacles while it intends to reach subsequent goals. Tenacity and Traversability (T2)1-based strategies have demonstrated to be highly effective for reactive navigation, extending the benefits of the artificial Potential Field method to complex situations, such as trapping zones or mazes. This paper presents a new approach for reactive mobile robot behavior control which rules the actions to be performed to avoid unexpected obstacles while the robot executes a mission between several defined sites. This new strategy combines the T2 principles to escape from trapping zones together with additional criteria based on the Nearness Diagram (ND)13 strategy to move in cluttered or densely occupied scenarios. Success in a complete set of experiments, using a mobile robot equipped with a single camera, shows extensive environmental conditions where the strategy can be applied.

This paper presents a novel global path planning method for mobile robots. An improved grid map, called three-dimensional-like map, is developed to represent the global workspace area. The new environment model includes not only contour information of obstacles but also artificial height information. Based on this new model, a simple but efficient obstacle avoidance algorithm is developed to solve robot path planning problems in static environment. The proposed algorithm only requires simple distance calculations and several comparison operations. In addition, unlike other algorithms, the proposed algorithm only needs to deal with some obstacles instead of all. The research results show that this method is computationally efficient and can be used to find an optimal or near optimal path.

Due to the growing use of Atomic Force Microscope (AFM) nanorobots in the moving and manipulation of cylindrical nanoparticles (carbon nanotubes and nanowires) and the fact that these processes cannot be simultaneously observed, a computer simulation of the involved forces for the purpose of predicting the outcome of the process becomes highly important. So far, no dynamic 3D model that shows changes in these forces in the course of process implementation has been presented. An algorithm is used in this paper to show in 3D, the manner by which the dynamic forces vary in the mentioned process. The presented model can simulate the forces exerted on the probe tip during the manipulation process in three directions. Because of the nonlinearity of the presented dynamic model, the effective parameters have been also studied. To evaluate the results, the parameters of the 3D case (cylindrical model) are gradually reduced and it is transformed into a 2D model (disk model); and we can observe a good agreement between the results of the two simulations. Next, the simulation results are compared with the experimental results, indicating changes in lateral force. With the help of the offered dynamic model, the cantilever deformation and the forces interacting between probe tip and particle can be determined from the moment the probe tip contacts the nanoparticle to when the nanoparticle dislodges from the substrate surface.

In this study, kinematic analysis of 6-DOF RSS parallel manipulator using Denavit Hartenbeng (D-H) method is investigated. In addition, in order to improve the proposed method, determination of all the active and passive angles, required to obtain Jacobian and complete dynamic model of manipulator, is also achieved. The effects of dynamic models of 6-DOF RSS parallel manipulator with its actuators on trajectory tracking control are studied in detail. Feedback dynamic compensation terms of motor-mechanism coupling system that is needed to compute torque control are obtained through both a single link approximation model and a complete dynamic model. The complete model is derived by taking account of the interaction between the input links and coupler links of the manipulator. Simulations showed that obtaining complete model of manipulator by means of D-H method and using computed control law could improve the quality of trajectory tracking control of parallel manipulator.