In this paper, we develop a model predictive control (MPC) scheme for robots to follow a virtual leader. The stability of this control scheme is guaranteed by adding a terminal state penalty to the cost function and a terminal state region to the optimization constraints. The terminal state region is found by analyzing the stability. Also a terminal state controller is defined for this control scheme. The terminal state controller is a virtual controller and is never used in the control process. Two virtual leader-following formation models are studied. Simulations on different formation patterns are provided to verify the proposed control strategy.

A new neural network (NN) control technique for robot manipulators is introduced in this paper. The fundamental robot control technique is the model-based computed-torque control which is subjected to performance degradation due. to model uncertainty. NN controllers have been traditionally used to generate a compensating joint torque to account for the effects of the uncertainties. The proposed NN control approach is conceptually different in that it is aimed at prefiltering the desired joint trajectories before they are used to command the computed-torque-controlled robot system (the plant) to counteract performance degradation due to plant uncertainties. In this framework, the NN controller serves as the inverse model of the plant, which can be trained on-line using joint tracking error. Several variations of this basic technique is introduced; Back-propagation training algorithms for the NN controller have been developed. Simulation results have demonstrated the excellent tracking performance of the proposed control technique.

Virtual reference is defined as the signal for a closed-loop System so that the response tracks the desired path perfectly. It is proposed to obtain a virtual reference signal suitable for a manipulator to track a predetermined trajectory using repetitive operations. Thus the algorithm ensures that the difference between the desired and the manipulator trajectories will become negligible as the number of operations approaches infinity if the manipulator is compensated for properly by local feedback. This algorithm uses a dual System to recursively improve the reference signal. Such a System has the advantage of being simple to design. The derivation of this algorithm is based on functional analysis. The effectiveness is confirmed by two experimental results.

Cooperative manipulators have uncertainties in their structure; therefore, an optimal sliding mode control method is derived from a combination of the sliding mode control (SMC) and the state-dependent Riccati equation (SDRE) technique. This proposed combination is applied to a class of non-linear closed-loop systems. One of the distinguished features of this control method is its robustness toward uncertainty. Due to the lack of optimality in the SMC method, in this paper, a robust and optimal method is presented by considering the SDRE in design of the sliding surface. Due to the fact that cooperative manipulators have been used for carrying loads, the percentage of load distributions between each manipulator has been derived to increase the dynamic load carrying capacity (DLCC). The proposed control structure is implemented on a Scout robot with two manipulators in cooperative mode, theoretically and practically using LabVIEW software; and the results were compared by considering the uncertainty in its structure. In comparison with the SDRE, the proposed method increased the DLCC almost 10% in the Scout case.

A method is presented that compensates for manipulator end-point errors in order to achieve very high position accuracy. The measured end-point error is decomposed into generalized geometric and elastic error parameters that are used in an analytical model to calibrate the system as a function of its configuration and the task loads, including any payload weight. The method exploits the fundamental mechanics of serial manipulators to yield a non-iterative compensation process that only requires the identification of parameters that are function only of one variable. The resulting method is computationally simple and requires far less measured data than might be expected. The method is applied to a six degrees-of-freedom (DOF) medical robot that positions patients for cancer proton therapy to enable it to achieve very high accuracy. Experimental results show the effectiveness of the method.

In this paper, a simple and convenient method – Recursive Matrix method – is proposed for kinematic and dynamic analysis of all types of complex manipulators. After addressing the principle of the method, an example – a 3-DOF parallel manipulator with prismatic actuators – is demonstrated for the efficiency of the method in solving kinematic and dynamic problems of complex manipulators. With the inverse kinematic solutions, the inverse dynamic problem is solved with the virtual powers method. Matrix relations and graphs of the acting forces and powers for all actuators are analysis and determined. It is shown that the proposed method is an effective mean for kinematic and dynamic modelling of parallel mechanisms.

In this paper, we present the design, static analysis, simulation, and implementation of a novel design for a naturally stable climbing robot that has been inspired from human pole/tree climbers. The other benefits of this robot, besides being naturally stable, are its simple design, ease of control, light weight, simple mechanism, and fast climbing speed. The robot consists of three wheels, two free and one active wheel, which enable the robot to climb or descend poles. The free wheels are almost frictionless, while the active wheel has enough friction to be able to apply force on the pole for stable climbing or descending. The wheels are designed in V-shape such that the robot can compensate for misplacements eliminating possible detachment from poles. Although the robot can operate with a single free wheel, however, an extra free wheel is added to increase the stability and safety of the robot. In this paper, the static analysis of the robot is presented and the robot is simulated. Furthermore, the robot is actually implemented and successfully tested in two sizes, a small size and a big/full size. The full-scale prototype has been equipped with washing and inspection tools and tested washing actual street lights. The results show the unique characteristics of this robot that make it more stable if more weight is carried.

This paper presents a wheel–terrain interaction model, which enables efficient modeling of wheeled locomotion in soft soil and numerical simulations of off-road mobile robots. This modular model is derived based on wheel kinematics and terramechanics and the main focus is on describing the stress distributions along the wheel–terrain interface and the reaction forces exerted on the wheel by the soil. When the wheels are steered, the shear stresses underneath the wheel were modeled based on isotropic assumptions. The forces and torques contributed by the bulldozing effect of the side surfaces is also considered in the proposed model. Furthermore, the influence of grousers, commonly used on smaller mobile robots, was modeled by (1) averaging the normal pressures contributed by the grousers and the wheel concave portion, and (2) assuming that the shear phenomenon takes places along the grouser tips. By integrating the model with multibody system code for vehicle dynamics, simulation studies of various off-road conditions in three-dimensional environments can be conducted. The model was verified by using field experiment data, both for a single-wheel vehicle and a whole vehicle.

As for the obstacle avoidance and formation control for the multi-robot systems, this paper presents an obstacle-avoidance method based on the improved artificial potential field (IAPF) and PID adaptive tracking control algorithm. In order to analyze the dynamics and kinematics of the robot, the mathematical model of the robot is built. Then we construct the motion situational awareness map (MSAM), which can map the environment information around the robot on the MSAM. Based on the MSAM, the IAPF functions are established. We employ the rotating potential field to solve the local minima and oscillations. As for collisions between robots, we build the repulsive potential function and priority model among the robots. Afterwards, the PID adaptive tracking algorithm is utilized to multi-robot formation control. To demonstrate the validity of the proposed method, a series of simulation results confirm that the approaches proposed in this paper can successfully address the obstacle- and collision-avoidance problem while reaching formation.

Herein is proposed a concise algorithmic procedure for deriving a minimum l∞-norm solution of the system of consistent linear equations Ax=b, where A is a m×n matrix, b is given as a m×1 vector and x is a n×1 unknown vector. The proposed algorithm is developed based on the geometrical analysis of the characteristics of the minimum infinity-norm solution. The proposed algorithm is well-structured so that it may be implemented easily through simple linear algebraic manipulation. For the case of n>m, the basic idea of the method is extended to finding internally mapped vertices when a n dimensional polytope is transformed into m dimensional polytope through consistent linear mapping A. The proposed method is applied to the task velocity analysis for robot manipulators with joint velocity constraints.

A new algorithm, called rapidly exploring random tree of trees (RRTOT) is proposed, that aims to address the challenge of planning for autonomous structural inspection. Given a representation of a structure, a visibility model of an onboard sensor, an initial robot configuration and constraints, RRTOT computes inspection paths that provide full coverage. Sampling based techniques and a meta-tree structure consisting of multiple RRT* trees are employed to find admissible paths with decreasing cost. Using this approach, RRTOT does not suffer from the limitations of strategies that separate the inspection path planning problem into that of finding the minimum set of observation points and only afterwards compute the best possible path among them. Analysis is provided on the capability of RRTOT to find admissible solutions that, in the limit case, approach the optimal one. The algorithm is evaluated in both simulation and experimental studies. An unmanned rotorcraft equipped with a vision sensor was utilized as the experimental platform and validation of the achieved inspection properties was performed using 3D reconstruction techniques.

Special micromanipulators are needed to manipulate very small objects. Most micromanipulators are specialized to perform a task they are designed for, but are too inflexible to adapt to other problems. Therefore, flexible newly developed mobile microrobots are presented with precision in the sub-micrometer range while offering a macroscopic workspace. The main parts of each mobile microrobot, the mobile platform, the manipulator and end effectors, are explained in detail, with some experimental data given.

The new driving principle of the mobile platform allows high resolution, low energy consumption, which makes an on-board power supply feasible and a maximum velocity of several mm/s.

Useful human interfaces are needed for a successful teleoperation. The most important interface next to the vision feedback is a haptic interface. The paper presents a newly developed haptic interface for a micromanipulation station. The mechanical design and the design of the control system of the haptic interface are discussed in details. The control architecture of the micromanipulation station and the integration of the haptic device into the micromanipulation station are presented.

The paper introduces a novel general feedback control framework, which allows applying the motion controllers originally dedicated for the unicycle model to the motion task realization for the car-like kinematics. The concept is formulated for two practically meaningful motorizations: with a front-wheel driven and with a rear-wheel driven. All the three possible steering angle domains for car-like robots—limited and unlimited ones—are treated. Description of the method is complemented by the formal stability analysis of the closed-loop error dynamics. The effectiveness of the method and its limitations have been illustrated by numerous simulations conducted for the three main control tasks, namely, for trajectory tracking, path following, and set-point regulation.

In this paper, a model-based exponential stabilization of a quadruped robot is studied in bounding motion. The dynamics of the five-link planar underactuated mechanical model of the quadruped robot with four actuated joints system is derived. It is shown that the dynamical equation of the proposed simplified model belongs to a class of second-order nonholonomic mechanical systems which cannot be stabilized by any smooth time-invariant state feedback. Utilizing a coordinate transformation based on the so-called normalized momentum, a robust backstepping control method is presented for the quadruped robot. Both theoretical analysis and numerical simulations show that the robust backstepping controller can stabilize the underactuated quadruped robot so that it could balance on its rear legs and track a desired trajectory. Despite the model parameter uncertainties, the robustness of the controller is maintained. The simulation results show the effectiveness of the proposed method.

An approach for collision–free trajectory planning along designated paths of two robots in a common workspace is presented. Specifically, in order to describe potential collision between the links of two robots along the designated paths, explicit forms of virtual obstacle are adopted, according to which links of one robot are made to grow while the other robot is forced to shrink as a point on the path. Then, a notion of virtual coordination space is introduced to visualize all the collision–free coordinations of two trajectories. Assuming that a collision–free coordination curve between the two robots is given via a virtual coordination space, the minimum time collision–free trajectory pair for the two robots is sought considering dynamic constraints of torque and velocity bounds of actuators of the two robots.

A light-weight, high-torque actuator with accurate torque control capability is described. The actuator uses a small hydrostatic transmission to achieve the advantage of large gear reduction from a high speed DC motor, and retains accurate joint torque sensing and control capabilities with no backlash. A disadvantage of the actuator is that is introduces extra dynamics which must be accounted for in robot control systems. It is shown that state feedback enables closed loop control of joint torque, with full back drivability, through an effective gear ratio of 485:1 for the experimental system. The actuator can therefore be used for both position control and output force control, which is essential for modern robot control algorithms. A mathematical model of the system is presented in this paper along with experimental results.

Robotics Agent Coacher for Cerebral Palsy motor Function (RAC CP Fun) is an attempt to implement socially assistive robotics, and a motor learning approach in rehabilitating movement disorders with a central origin. The concept and architecture of RAC CP Fun implements the motor learning theory and behavioral approach, i.e. principles of repetition, stages of learning, appropriate feedback, random practice, and enriched environments. Eleven children with cerebral palsy (CP) and fourteen typically developed (TD) children participated in two procedures while interacting with a robot and performing motor exercises. The interaction level and motor performance of children were measured and compared. Children with CP exhibited a higher interaction level; however, their motor performance was lower than that of TD children. RAC CP Fun was found to be feasible to interact with children of pre-school age, to augment the motivation of the children with CP, and to involve the children in motor exercises.

We have designed a robotic arm based on a double parallel four bar linkage to act as an assistant in minimally invasive surgical procedures. The remote center of motion (RCM) geometry of the robot arm kinematically constraints the robot motion such that minimal translation of an instrument held by the robot takes place at the entry portal into the patientApos;s body. In addition to the two rotational degrees of freedom comprising the RCM arm, distal translation and rotation are provided to manoeuver the instrument within the patient's body about an axis coincident with the RCM. An XYZ translation stage located proximal to the RCM arm provides positioning capability to establish the RCM location relative to the patients anatomy. An electronics set capable of controlling the system, as well as performing a series of safety checks to verify correct system operation, has also been designed and constructed. The robot is capable of precise positional motion. Repeatability in the ±10 micron range is demonstrated. The complete robotic system consists of the robot hardware and an IBM PC-AT based servo controller connected via a custom shared memory link to a host IBM PS/2. For laparoscopic applications, the PS/2 includes an image capture board to capture and process video camera images. A camera rotation stage has also been designed for this application. We have successfully demonstrated this system as an assistant in a laparoscopic cholecystectomy. Further applications for this system involving active tissue manipulation are under development.

This paper deals with the position workspace, orientation workspace, and singularity of a 3-degree-of-freedom (DOF) planar parallel manipulator with actuation redundancy, which is created by introducing a redundant link with active actuator to a 3-DOF nonredundant parallel manipulator. Based on the kinematic analysis, the position workspace and orientation workspace of the redundantly actuated parallel manipulator and its corresponding nonredundant parallel manipulator are analyzed, respectively. In the singularity analysis phase, the relationship between the generalized input velocity and the generalized output velocity is researched on the basis of the theory of singular value decomposition. Then a method to investigate the singularity of parallel manipulators is presented, which is used to determine the singularity of the redundantly actuated parallel manipulator. In contrast to the corresponding nonredundant parallel manipulator, the redundant one has larger orientation workspace and less singular configurations. The redundantly actuated parallel manipulator is incorporated into a 4-DOF hybrid machine tool which also includes a feed worktable to demonstrate its applicability.

This paper addresses the dynamic dexterity of a planar 2-degree of freedom (DOF) parallel manipulator with virtual constraint. Without simplification, the dynamic formulation is derived by using the virtual work principle. The condition number of the inertia matrix of the dynamic equation is presented as a criterion to evaluate the dynamic dexterity of a manipulator. In order to obtain the best isotropic configuration of the dynamic dexterity in the whole workspace, two global performance indices, which consider the mean value and standard deviation of the condition number of the inertia matrix, respectively, are proposed as the objective function. For a given set of geometrical and inertial parameters, the dynamic dexterity of the parallel manipulator is more isotropic in the center than at the boundaries of the workspace.