This paper reports on the control structure of the pneumatic biped Lucy. The robot is actuated with pleated pneumatic artificial muscles, which have interesting characteristics that can be exploited for legged locomotion. They have a high power to weight ratio, an adaptable compliance and they can absorb impact effects.

The discussion of the control architecture focuses on the joint trajectory generator and the joint trajectory tracking controller. The trajectory generator calculates trajectories represented by polynomials based on objective locomotion parameters, which are average forward speed, step length, step height and intermediate foot lift. The joint trajectory tracking controller is divided in three parts: a computed torque module, a delta-p unit and a bang-bang pressure controller. The control design is formulated for the single support and double support phase, where specifically the trajectory generator and the computed torque differs for these two phases.

The first results of the incorporation of this control architecture in the real biped Lucy are given. Several essential graphs, such as pressure courses, are discussed and the effectiveness of the proposed algorithm is shown by the small deviations between desired and actual attained objective locomotion parameters.

Teleoperated robots are used to perform tasks that human operators cannot carry out because of the nature of the tasks themselves or the hostile nature of the working environment. Though many control architectures have been defined for developing these kinds of systems reusing common components, none has attained all its objectives because of the high variability of system behaviors. This paper presents a new architectural approach that takes into account the latest advances in robotic architectures while adopting a component-oriented approach. This approach provides a common framework for developing robotized systems with very different behaviors and for integrating intelligent components. The architecture is currently being used, tested and improved in the development of a family of teleoperated robots which perform cleaning of ship-hull surfaces.

In this paper, a collision detection and identification method of a manipulator, using wrist and base force/torque sensors, is presented. An impact model is used to simulate the interaction between the manipulator and the human or environment. A neural network approach and a model based method are developed to detect the collision forces and disturbance torques on the joints of the manipulator. The experimental results illustrate the validity of the developed collision detection and identification scheme.

This paper proposes a new visual positioning method for a humanoid robot to approach and grasp a valve based on colour and shape constraints. The robot has two cameras in its head and uses constraints of colour rectangle marks to determine the valve's position and pose. When the hands are near the valve, an image-based visual servoing method is employed to catch the handle of the valve via cameras in end-effectors. Experimental results are presented to verify the effectiveness of the proposed method.

A conventional sonar ring measures the range to objects based on the first echo and is widely used in indoor mobile robots. In contrast, advanced sonar sensing can produce accurate range and bearing (incidence angle) measurements to multiple targets using multiple receivers and multiple echoes per each receiver at the expense of intensive computation. This paper presents an advanced sonar ring that employs a low receiver sample rate to achieve processing of 48 receiver channels at near real time repetition rates of 11.5 Hz. The sonar ring sensing covers 360 degrees around the robot for specular targets for ranges up to six metres, with simultaneously firing of all its 24 transmitters. Digital Signal Processing (DSP) techniques and interference rejection ideas are applied in this sensor to produce a fast and accurate sonar ring. Seven custom designed DSP boards process the receivers sampled at 250 kHz to maximize the speed of processing and to limit memory requirements. This paper presents the new sensor design, the hardware structure, the software architecture, and signal processing of the advanced sonar ring. Repeatability and accuracy of the measurements are tested to characterize the proposed sensor. Due to the low sample rate of 250 kHz, a problem called cycle hopping can occur. The paper presents a solution to cycle hopping and a new transmit coding based on pulse duration to differentiate neighbouring transmitters in the ring. Experimental data show the effectiveness of the designed sensor in indoor environments.

A predictive display method and man-virtual robot interaction based on augmented reality are applied to control a telerobot. We first discuss the process of the augmented reality environment development. Then, we present the advantages of predictive display. Simulation of virtual robot's tasks in the augmented environment improves the safety of the telerobot when it executes the planned tasks. In addition, the immediate feedback from the virtual robot avoids the exacerbation of maneuverability caused by time-delay. For a more natural operation process, we apply multi man-virtual robot interactive methods. Lastly, the experiment of pick & place is conducted to validate the system.

This paper compares two methods to estimate the position of a mobile robot in an indoor environment using only odometric calculus and the WiFi energy received from the wireless communication infrastructure. In both cases we use a well-known probabilistic method based on the Bayes rule to accumulate localization probability as the robot moves on with an experimental WiFi map, and with a theoretically built WiFi map. We will show several experiments made in our university building to compare both methods using a Pioneer robot. The two major contributions of the presented work are that the self-localization error achieved with WiFi energy is bounded, and that no significant degradation is observed when the expected WiFi energy at each point is taken from radio propagation model, instead of an a priori experimental intensity map of the environment.

Significant research has been aimed at the development and control of teleoperator systems due to both the practical importance and the challenging theoretical nature of the problem. Two controllers are developed in this paper for a nonlinear teleoperator system that target coordination of the master and slave manipulators and passivity of the overall system. The first controller is proven to yield a semi-global asymptotic result in the presence of parametric uncertainty in the master and slave manipulator dynamic models. The second controller yields a global asymptotic result despite unmeasurable user and environmental input forces. To develop each controller, a transformation encodes the coordination and passivity objectives in the closed loop system. The coordinated system is forced to track a dynamic system to assist in meeting all control objectives. Finally, continuous nonlinear integral feedback terms are used to accommodate for incomplete system knowledge for both controllers. Lyapunov-based techniques are used to prove that all control objectives are met and that all signals are bounded.

A stochastic ellipsoid modelling of repeatability is proposed for industrial manipulator robots. The covariance matrix of angular position is determined introducing the jump process, which reveals to be a first and second order stationary Gaussian process.

From this accurate covariance matrix, the stochastic ellipsoid theory gives the density of position in the workspace around the mean position. Hence the pose repeatability index can be computed in different locations. Computed and experimental repeatability are compared. Experimental repeatability variability is studied. A new “intrinsic repeatability index” is proposed. In conclusion, the modelling reflects well the location and load influence on the repeatability.

Increasing the energy autonomy of a hopping one-legged robot is studied in this paper. For a particular passive gait, of all those possible, the energy dissipated per unit length of travel is shown to be less than for any other gait. This optimal gait is identified analytically, by exploiting the commonly used SLIP model to simplify real robot dynamics. Both mechanical and electrical losses are considered. The accuracy of the optimal gait analytical prediction is evaluated by a numerical analysis of a realistic robot model. Finally, restrictions imposed on executing the optimal gait due to motor limitations are studied.

This paper presents investigations into the applications and performance of positive and negative input shapers in command shaping techniques for the vibration control of a flexible robot manipulator. A constrained planar single-link flexible manipulator is considered and the dynamic model of the system is derived using the finite element method. An unshaped bang-bang torque input is used to determine the characteristic parameters of the system for design and evaluation of the input shaping control techniques. The positive and specified amplitude negative input shapers are designed based on the properties of the system. Simulation results of the response of the manipulator to the shaped inputs are presented in the time and frequency domains. Performances of the shapers are examined in terms of level of vibration reduction, time response specifications and robustness to parameters uncertainty. The effects of derivative order of the input shaper on the performance of the system are investigated. Finally, a comparative assessment of the impact amplitude polarities of the input shapers on the system performance is presented and discussed.

A brand-new paradigm of robots–quantum robots–is proposed through the fusion of quantum theory with robot technology. A quantum robot is essentially a complex quantum system which generally consists of three fundamental components: multi-quantum computing units (MQCU), quantum controller/actuator, and information acquisition units. Corresponding to the system structure, several learning control algorithms, including quantum searching algorithms and quantum reinforcement learning algorithms, are presented for quantum robots. The theoretical results show that quantum robots using quantum searching algorithms can reduce the complexity of the search problem from O($N^2)$ in classical robots to O($N\sqrt N)$. Simulation results demonstrate that quantum robots are also superior to classical robots in efficient learning under novel quantum reinforcement learning algorithms. Considering the advantages of quantum robots, some important potential applications are also analyzed and prospected.

In the paper, a new adaptive control law for controlling robot manipulators is derived based on the Lyapunov theory; trigonometric functions are used for the derivation of the parameter estimation law. In this note, we have derived a logarithmic parameter estimation law based on a previous paper, and the boundedness of tracking error has been shown.

A novel 3-DOF prismatic-revolute-cylindrical (PRC) translational compliant parallel micromanipulator (CPM) has been designed for 3-D nanomanipulation in this paper. The system is configured by a proper selection of hardware and analyzed via the established pseudo-rigid-body (PRB) model. The CPM workspace is determined taking into account the physical constraints imposed by piezoelectric actuators and flexure hinges.