Researchers dream of developing autonomous humanoid robots which behave/walk like a human being. Biped robots, although complex, have the greatest potential for use in human-centred environments such as the home or office. Studying biped robots is also important for understanding human locomotion and improving control strategies for prosthetic and orthotic limbs. Control systems of humans walking in cluttered environments are complex, however, and may involve multiple local controllers and commands from the cerebellum. Although biped robots have been of interest over the last four decades, no unified stability/balance criterion adopted for stabilization of miscellaneous walking/running modes of biped robots has so far been available. The literature is scattered and it is difficult to construct a unified background for the balance strategies of biped motion. The zero-moment point (ZMP) criterion, however, is a conservative indicator of stabilized motion for a class of biped robots. Therefore, we offer a systematic presentation of multi-level balance controllers for stabilization and balance recovery of ZMP-based humanoid robots.

This paper describes the autonomous navigation and control of an undersea vehicle using a vehicle control architecture based on the Distributed Architeclure for Mobile Navigation and a terrain-aided navigation technique based on simultaneous localisation and map building. Development of the low-speed platform models for vehicle control and the theoretical and practical details of mapping and position estimation using sonar are provided. Details of an implementation of these techniques on a small submersible vehicle “Oberon” are presented.

The paper introduces the use of radial basis functions (RBFs) to generate smooth point-to-point joint trajectories for robot manipulators. First, Gaussian RBF interpolation is introduced taking into account boundary conditions. Then, the proposed approach is compared with classical planning techniques based on polynomial and trigonometric models. Also, the trajectory planning problem involving via-points is solved using the proposed RBF interpolation technique. The obtained trajectories are then compared with those synthesized using algebraic and trigonometric splines. Finally, the proposed method is tested for the six-joint PUMA 560 robot in two cases (minimum time and minimum time-jerk) and results are compared with those of other planning techniques. Numerical results demonstrate the advantage of the proposed technique, offering an effective solution to generate trajectories with short execution time and smooth profile.

The estimation of dynamic parameters in mechanical systems constitutes an issue of crucial importance both for inverse dynamics based control strategies and dynamic simulation applications where high accuracy is required. The identification procedures can be classified in two main groups: indirect and direct procedures. The first ones act sequentially in several steps in each of them parameters of different nature (basically friction and inertial parameters) are identified by means of specifically designed experiments, while the direct procedures allow the identification of all parameters defining de dynamic model in a single stage. In this paper, the implementation and comparison of an indirect and a direct identification procedures on an industrial robot provided with an open control architecture is addressed.

Navigation and collision avoidance are major areas of research in mobile robotics that involve varying degrees of uncertainty. In general, the problem consists of achieving sensor based motion control of a mobile robot among obstacles in structured and/or unstructured environments with collision-free motion as the priority. A fuzzy logic based intelligent control strategy has been developed here to computationally implement the approximate reasoning necessary for handling the uncertainty inherent in the collision avoidance problem. The fuzzy controller was tested on a mobile robot system in an indoor environment and found to perform satisfactorily despite having crude sensors and minimal sensory feedback.

Exoskeleton robots, which can be worn on human limbs to improve or to rehabilitate their function, are currently of great importance. When these robots are used in rehabilitation, one aspect that must be fulfilled is their capacity to adapt to different patients without significantly varying their performance. This paper describes the application of a relatively new control technique called virtual decomposition control (VDC) to a seven degrees-of-freedom (DOF) exoskeleton robot arm, named ETS-MARSE. The VDC approach mainly involves decomposing complex systems into subsystems, and using the resulting simpler dynamics to conduct control computation, while strictly ensuring global stability and having the subsystem dynamics interactions rigorously managed and maintained by means of virtual power flow. This approach is used to deal with different masses, joint stiffness and biomechanical variations of diverse subjects, allowing the control technique to naturally adapt to the variances involved and to maintain a successful control task. The results obtained in real time on a 7DOF exoskeleton robot arm show the effectiveness of the approach.

A systematic method is developed for the type synthesis of 4-DOF nonoverconstrained parallel mechanisms with three translations and one rotation inspired by the design of H-4. First, the motion requirements of primary platform and secondary platform of the 4-DOF nonoverconstrained parallel mechanisms are analyzed, and the conflict between the number of actuators and the constraint system for nonoverconstrained parallel mechanism is solved. Then, the research topic of type synthesis of 4-DOF nonoverconstrained parallel mechanisms is transformed into the type synthesis of the secondary platform with three translational DOF linked by two chains. On the basis of the screw and reciprocal theory, all possible secondary limbs with 3-DOF, 4-DOF, and 5-DOF are synthesized, respectively. Finally, the configurations and spatial assembly conditions of all possible secondary limbs are provided and some typical mechanisms are sketched as examples.

Novel kinematic architectures can be alternatives for designing energy efficient robotic systems. In this work, the impact of kinematic redundancies in the energy consumption of a planar PKM, the 3PRRR manipulator, is experimentally verified. Because of the presence of the kinematic redundancies, the inverse kinematic problem presents infinity solutions. In this way, a redundancy resolution scheme based on the Model Predictive Control technique is proposed and exploited. It can be concluded that the energy consumption of the non-redundant parallel manipulator 3RRR for executing predefined tasks can be considerably reduced by the inclusion of kinematic redundancies.

Inverse kinematics (IK) is a nonlinear problem that may have multiple solutions. A modified genetic algorithm (GA) for solving the IK of a serial robotic manipulator is presented. The algorithm is capable of finding multiple solutions of the IK through niching methods. Despite the fact that the number and position of solutions in the search space depends on the position and orientation of the end-effector as well as the kinematic configuration (KC) of the robot, the number of GA parameters that must be set by a user are limited to a minimum through the use of an adaptive niching method. The only requirement of the algorithm is the forward kinematics (FK) equations which can be easily obtained from the Denavit–Hartenberg link parameters and joint variables of the robot. For identifying and processing the outputs of the proposed GA, a modified filtering and clustering phase is also added to the algorithm. For the postprocessing stage, a numerical IK solver is used to achieve convergence to the desired accuracy. The algorithm is validated on three KCs of a modular and reconfigurable robot (MRR).

An assistive device for upper limb support was developed and evaluated in terms of usability, user satisfaction and motor performance on six end-users affected by neuro-motor disorders (three spinal cord injury; one multiple sclerosis; two Friedreich's ataxia). The system consisted of a lightweight 3-degrees-of-freedom robotic exoskeleton arm for weight relief, equipped with electromagnetic brakes. Users could autonomously control the brakes using a USB-button or residual electromyogram activations. The system functionally supported all of the potential users in performing reaching and drinking tasks. For three of them, time, smoothness, straightness and repeatability were also comparable to healthy subjects. An overall high level of usability (system usability score, median value of 90/100) and user satisfaction (Tele-healthcare Satisfaction Questionnaire - Wearable Technology, median value of 104/120) were obtained for all subjects.

Recursive matrix relations in kinematics and dynamics of a Delta parallel robot having three revolute actuators are established in this paper. The prototype of the manipulator is a three degrees-of-freedom space mechanism, which consists of a system of parallel closed kinematical chains connecting to the moving platform. Knowing the translation motion of the platform, we develop first the inverse kinematics problem and determine the position, velocity and acceleration of each robot's element. Further, the inverse dynamic problem is solved using an approach based on the fundamental principle of virtual work. Finally, a comparative study on time-history evolution of the torques of the three actuators is analysed.

The paper considers the problem of motion planning and posture control of multiple n-link doubly nonholonomic mobile manipulators in an obstacle-cluttered and bounded workspace. The workspace is constrained with the existence of an arbitrary number of fixed obstacles (disks, rods and curves), artificial obstacles and moving obstacles. The coordination of multiple n-link doubly nonholonomic mobile manipulators subjected to such constraints becomes therefore a challenging navigational and steering problem that few papers have considered in the past. Our approach to developing the controllers, which are novel decentralized nonlinear acceleration controllers, is based on a Lyapunov control scheme that is not only intuitively understandable but also allows simple but rigorous development of the controllers. Via the scheme, we showed that the avoidance of all types of obstacles was possible, that the manipulators could reach a neighborhood of their goal and that their final orientation approximated the desired orientation. Computer simulations illustrate these results.

A new method for real-time obstacle avoidance and trajectory planning of underactuated unmanned surface vessels is presented. In this method, ordinary differential equations (ODEs) are used to define transitional trajectories that can avoid obstacles and reach a final desired target trajectory using a robust tracking control law. The obstacles are approximated and enclosed by elliptical shapes. A transitional trajectory is then defined by a set of ordinary differential equations whose solution is a stable elliptical limit cycle defining the nearest obstacle on the vessel's path to the target. When no obstacle blocks the vessel's path to its target, the transitional trajectory is defined by exponentially stable ODE whose solution is the target trajectory. The planned trajectories are tracked by the vessel through a sliding mode control law that is robust to environmental disturbances and modeling uncertainties and can be computed in real time. The method is illustrated using a complex simulation example with a moving target and multiple moving and rotating obstacles and a simpler experimental example with stationary obstacles.

In this study, the kinematics and dynamics of a six-degree-of-freedom parallel manipulator, known as Hexarot, are evaluated. Hexarot is classified under axis-symmetric robotic mechanisms. The manipulator comprises a cylindrical base column and six actuated upper arms, which are connected to a platform through passive joints and six lower arms. The actuators of the mechanism are located inside a cylindrical-shaped base, which allows the mechanism to rotate infinitely about the axes of the latter column. In the context of kinematics, the inverse-kinematic problem is solved using positions, velocities, and accelerations of the actuated joints with respect to the position, orientation, and motion of the platform. Accordingly, the main objective of this study is to dynamically model the manipulator using the Newton–Euler approach. For validation, the obtained dynamic model of the Hexarot manipulator is simulated in MATLAB based on the formulations presented in this paper. The kinematic and dynamic models of the manipulator are simulated for a given motion scenario using MATLAB and ADAMS. The results of the mathematical model obtained using MATLAB are in good agreement with that using the ADAMS model, confirming the effectiveness of the proposed mathematical model.

Robotic-assisted surgery is a continuously developing field because robots have demonstrated clear benefits in operating rooms. Until now, vast majority of robots used in surgery had serial structures. This paper presents the kinematic modelling of a 5-degree of freedom hybrid parallel architecture in two slightly different variants. The kinematics of this structure is determined, and following the analysis of singularities, the best variant is chosen. The robot workspace is computed and finally the experimental model and some simulation results are presented.

A cable manipulator controls its end-effector by a number of cables. If the cables can balance any external and inertia wrenches at a certain pose of the end-effector, the cable manipulator is said to have a force-closure at this pose. Since a cable can work only in tension, the force-closure at a specific pose may not exist. Thus, how to check the existence of force-closure at a given pose is an important issue for design and control of cable manipulators. This paper describes a systematic method of verifying the existence of force-closure at a specific pose of a general 6-DOF cable manipulator with seven or more cables. By examining the Jacobian matrix of the manipulator, the method can determine whether a force-closure exists at the pose corresponding to the Jacobian matrix. The necessity and sufficiency of the proposed method are mathematically proven. Moreover, a convex-analysis-based simplification of the method for manipulators with more than seven cables is also discussed.

This paper concerns the modeling and control of a mobile manipulator which consists of a robotic arm mounted upon a mobile platform. The equations of motion are derived using the Lagrange-d'Alembert formulation for the nonholonomic model of the mobile manipulator. The dynamic model which considers slip of the platform's tires is developed using the Newton-Euler method and incorporates Dugoff's tire friction model. Then, the tracking problem is investigated by using a well known nonlinear control method for the nonholonomic model. The adverse effect of the wheel slip on the tracking of commanded motion is discussed in the simulation. For the dynamic model, a variable structure control approach is employed to minimize the harmful effect of the wheel slip on the tracking performance. The simulation results demonstrate the effectiveness of the proposed control algorithm.

The aim of this work has been the implementation and testing in real conditions of a new algorithm based on the cell-mapping techniques and reinforcement learning methods to obtain the optimal motion planning of a vehicle considering kinematics, dynamics and obstacle constraints. The algorithm is an extension of the control adjoining cell mapping technique for learning the dynamics of the vehicle instead of using its analytical state equations. It uses a transformation of cell-to-cell mapping in order to reduce the time spent during the learning stage. Real experimental results are reported to show the satisfactory performance of the algorithm.

A robot has to be safe and reliable. An unreliable robot may become the cause of unsafe conditions, high maintenance costs, inconvenience, etc.

Over the years, in general safety and reliability areas various assessment methods have been developed, e.g. failure mode and effects analysis, fault tree analysis, and Markovian analysis. In view of these, this paper presents an overview of the most suitable robot safety and reliability assessment techniques.

This paper addresses the formation tracking control of a group of tractor–trailer systems in the presence of model uncertainties. A virtual leader–follower formation technique is used to design a controller in order to force a team of tractor–trailer systems to construct a desired formation configuration. Since tractor–trailer systems have a nonlinear multi-input multi-output model with strong couplings, multi-layer neural networks are employed to overcome unknown nonlinearities and uncertain parameters by using on-line weight tuning algorithms. Neural network approximation errors and external disturbances are also compensated with adaptive robust signals. The dynamic surface control approach has been used to reduce the complexity of the proposed controller effectively. Lyapunov’s direct method proves that all signals in the closed-loop formation control system are bounded and tracking errors converge to a neighborhood of the origin whose size is adjustable. Finally, simulation results will be provided to illustrate the efficiency of the proposed controller.