Verbal communication is the most natural way of human–robot interaction. Such an interaction is usually achieved by means of a human-robot interface (HRI). In this paper, a HRI is presented to teleoperate a robotic platform via the user's voice. Hence, a speech recognition system is necessary. In this work, a user-dependent acoustic model for Spanish speakers has been developed to teleoperate a robot with a set of commands. Experimental results have been successful, both in terms of a high recognition rate and the navigation of the robot under the control of the user's voice.

To assist physically disabled people with impaired upper limb function, we have developed a new 7-DOF exoskeleton-type robot named Motion Assistive Robotic-Exoskeleton for Superior Extremity (ETS-MARSE) to ease daily upper limb movements and to provide effective rehabilitation therapy to the superior extremity. The ETS-MARSE comprises a shoulder motion support part, an elbow and forearm motion support part, and a wrist motion support part. It is designed to be worn on the lateral side of the upper limb in order to provide naturalistic movements of the shoulder (vertical and horizontal flexion/extension and internal/external rotation), elbow (flexion/extension), forearm (pronation/supination), and wrist joint (radial/ulnar deviation and flexion/extension). This paper focuses on the modeling, design, development, and control of the ETS-MARSE. Experiments were carried out with healthy male human subjects in whom trajectory tracking in the form of passive rehabilitation exercises (i.e., pre-programmed trajectories recommended by a therapist/clinician) were carried out. Experimental results show that the ETS-MARSE can efficiently perform passive rehabilitation therapy.

This paper addresses the trajectory tracking control problem of robotic wheelchairs in the presence of modeling uncertainties. The controller has been designed using position and angular measurements. A global ultra-model, or simplified model achieved from flatness considerations is proposed first. This model highly reduces the design complexity of the state estimation and the output feedback control tasks since it groups, as an unknown time-varying disturbance, both the combined effects of all uncertain state-dependent (i.e., endogenous) nonlinearities and those of external (i.e., exogenous) perturbation inputs which are present in the input-to-flat output model of the system. An extended linear high-gain observer, or Generalized Proportional Integral (GPI) observer, is then developed for the simultaneous, though approximate, state and disturbance estimation. The proposed feedback controller combines the global ultra-model and the GPI observers to conform an active disturbance rejection, or disturbance accommodation, control scheme. The simulation results presented in the paper show that the proposed method has a very good tracking performance and robustness in the presence of system uncertainties, external disturbances and noisy corruptions.

A novel nonlinear teleoperation algorithm for simultaneous inertial parameters and force estimation at the master and slave sides of the teleoperation system is proposed. The scheme, called Extended Active Observer (EAOB), is an extension of the existing active observer. It provides effective force tracking at the master side with accurate position tracking at the slave side in the presence of inertial parameter variation and measurement noise. The proposed method only requires the measurement of robot position, and as a result significantly reduces the difficulty and cost of implementing bilateral teleoperation systems. The approach is described and its stability is analytically verified. The performance of the method is validated through computer simulation and compared with the Nicosia observer-based controller. According to the results, EAOB outperforms the Nicosia observer method and effectively rejects noise.

Many research works on the control of nonholonomic wheeled mobile robots (WMRs) do not consider the actuator saturation problem and the absence of velocity sensors in practice. The actuator saturation deteriorates the tracking performance of the controller, and the use of velocity sensors increases the cost and weight of WMR systems. This paper simultaneously addresses these problems by designing a saturated output feedback controller for uncertain nonholonomic WMRs. First, a second-order input–output model of nonholonomic WMRs is developed by defining a suitable set of output equations. Then a saturated adaptive robust tracking controller is proposed without velocity measurements. For this purpose, a nonlinear saturated observer is used to estimate robot velocities. The risk of actuator saturation is effectively reduced by utilizing saturation functions in the design of the observer–controller scheme. Semi-global uniform ultimate boundedness of error signals is guarantied by the Lyapunov stability analyses. Finally, simulation results are provided to show the effectiveness of the proposed controller. Compared with one recent work of the author, a comparative study is also presented to illustrate that the proposed saturated controller is more effective when WMR actuators are subjected to saturation.

While Sit-to-Stand and Stand-to-Sit are routine activities and are crucial pre-requisites to walking and running their underlying dynamics are poorly understood. Furthermore, the potential for using these movements to regenerate energy in energy-sensitive devices such as orthoses, prostheses and humanoid robots has never been examined. Insights in this domain can lead to more energy-efficient prosthesis, orthosis and humanoid robot designs. OBJECTIVES: The objectives are two-fold: first, to determine how much energy can be regenerated during standard movements related to transitions between sitting and standing on a scale humanoid model and second, to determine if the chosen actuator could produce better results if the gear ratio were modified. This manuscript's main contribution to the literature is by showing which joint provides the most regenerative effect during transitions between sitting and standing. MODEL DESIGN AND IMPLEMENTATION: Joint trajectories from existing biomechanics trials of sitting and standing transitions were fed into a 1/10 scale model of a humanoid robot. The robot model, developed in MapleSim, is comprised of standard and off-the-shelf subcomponents, including amplifier, NiMH battery and Robotis Dynamixel RX-28 actuators. RESULTS: Using the RX-28 actuator, the ankle, knee and hip joints all show a degree of regenerative effects, the hip demonstrates the most dramatic levels during the transition from standing to sitting. This contrasts with recent publications which show that the knee has the most important regenerative effects during walking and running. It is also found that for under 3 degree trajectory error the regenerative effect is best for all joints when the gear ratio is increased from the RX-28's 193:1 value to a value of approximately 760:1 for the ankle, 630:1 for the knee and 600:1 for the hip. CONCLUSIONS: During transitions between sitting and standing the greatest potential for regeneration occurs in the hips. Therefore, systems designed to implement regenerative effects between sitting and standing need to include subsystems at the hip for maximum regenerative effects.

This paper investigates the contributions of each joint in perturbed balance by employing multiple balance strategies and exploring gain scheduling. Hybrid controllers are developed for sagittal standing in response to constant pushes, and a hypothesis is then investigated that postural feedback gains in standing balance should change with perturbation size via an optimization approach. Related research indicates the roles of each joint: the ankles apply torque to the ground, the hips and/or arms generate horizontal ground forces, and the knees and hips squat. To investigate it from an optimization point of view, this paper uses a horizontal push of a given size, direction, and location as a perturbation, and optimizes controllers for different push sizes, directions, and locations. It applies to the ankle, hip, squat, and arm swinging strategies in standing balance. By comparing the capability of handling disturbances and investigating the feedback gains of each strategy, this paper quantitatively analyzes the contributions of each joint to perturbed balance. We believe this work is also instructive to study the progressive behavioral changes as the model gets more and more complex.

In this paper, a new method is presented that allows an intelligent manipulator robotic system to track a human hand from far distance in 3D space and estimate its orientation and position in real time with the goal of ultimately using the algorithm with a robotic spherical wrist system. In this proposed algorithm, several image processing and morphology techniques are used in conjunction with various mathematical formulas to calculate the hand position and orientation. The proposed technique was tested on Remote teleguided virtual Robotic system. Experimental results show that proposed method is a robust technique in terms of the required processing time of estimation of orientation and position of hand.

An extension of the well-known Particle Swarm Optimization (PSO) to multi-robot applications has been recently proposed and denoted as Robotic Darwinian PSO (RDPSO), benefited from the dynamical partitioning of the whole population of robots. Although such strategy allows decreasing the amount of required information exchange among robots, a further analysis on the communication complexity of the RDPSO needs to be carried out so as to evaluate the scalability of the algorithm. Moreover, a further study on the most adequate multi-hop routing protocol should be conducted. Therefore, this paper starts by analyzing the architecture and characteristics of the RDPSO communication system, thus describing the dynamics of the communication data packet structure shared between teammates. Such procedure will be the first step to achieving a more scalable implementation of RDPSO by optimizing the communication procedure between robots. Second, an ad hoc on-demand distance vector reactive routing protocol is extended based on the RDPSO concepts, so as to reduce the communication overhead within swarms of robots. Experimental results with teams of 15 real robots and 60 simulated robots show that the proposed methodology significantly reduces the communication overhead, thus improving the scalability and applicability of the RDPSO algorithm.

Mobility is a fundamental parameter of mechanisms expressing in a qualitative manner their kinematic and dynamic properties. The mobility formulae presented in literature take into consideration some of the structural entities, such as bodies, joints, constraints, closed loops, and space characteristics; however, the specific mechanical model that has traditionally been at the origin of the mobility criteria themselves is incompletely specified and, even then, only implicitly. In this paper, we propose a classification of the mobility criteria based on the known dynamic models. While all known mobility criteria have been associated with a specific dynamic model, some particular, less used dynamic models (like natural coordinates and multi-particle models) suggested new mobility criteria models. The associated mechanical model for each category of mobility criteria allows a qualitative assessment of the kinematic and dynamic sets of equations to be formulated in later stages of analysis. A simple multi-loop mechanism is taken as an example just to illustrate the mobility calculation and qualitative assessment of the kinematic and dynamic models in each case. Based on the proposed classification of the mobility formulae, an assessment is made with particular regard to their applicability to overconstrained mechanisms.

Employing passive dynamics of the simplest point-foot walker, we have shown that the walking surface could have a great role in promoting the gait stability. In this regard, the stabilization of the simplest walking model,3 between the range of slopes greater than 0.0151 rad. and less than 0.26 rad., has been achieved. The walker like other passive dynamic walking models has no open or closed-loop control system; so, is only actuated by the gravity field. Moreover, no damper or spring is used. Obviously, according to the model's unstable behavior, it is unable to walk on an even flat ramp between the mentioned intervals.3 Here, instead of restraining the model, we let it explore other smooth surfaces, walking on which, will end in an equally inclined surface. To reach the objective, we employ a parallel series of fixed straight lines (local slopes) passing through contact points of an unstable cycling gait, which is generated by an ordinary ramp. To categorize, we have nicknamed those local slopes that guide the biped to a stable cyclic walking, “Ground Attractors,” and the other, leading it to a fall, “Repulsive Directions.” Our results reveal that for the slope <0.26 rad., a closed interval of ground attractors could be found. Stabilization of those unstable limit cycles by this technique makes obvious the key role of walking surface on bipedal gait. Furthermore, following our previous work,13 the results confirm that the two thoroughly similar walking trajectories can have different stability. All of these results strongly demonstrate that without considering the effects of a walking surface, we cannot establish any explicit relationship between the walker's speed and its stability.

Controlling a walking biped robot is a challenging problem due to the robot's complex and uncertain dynamics. In order to tackle this problem, we propose a sliding mode controller based on a dynamic model that we obtained using the conformal geometric algebra (CGA) approach. An important contribution of this paper is the development of algorithms using the CGA framework. The CGA framework permits us to use lines, points, and other geometric entities to obtain the Lagrange equations of the system. The references for the joints of the robot were obtained in a bio-inspired way following the kinematics of a walking human body. The first and second derivatives of the reference signal were obtained via an exact robust differentiator based on a high-order sliding mode. We analyzed the performance of the proposed control schemes by using bio-inspired walking patterns and simulations.

Segway is a self-balancing motorized two-wheeled vehicle which is able to carry the human body. The main issue in design of such a vehicle is to choose a stable control system capable of keeping the rider close to the upright position over smooth and non-smooth surfaces. This work extends the research previously performed by the authors for design of a controller, using the feedback linearization technique, to increase the stability of a two-wheeled vehicle carrying human. This paper investigates the design and validation of a controller for an inertial mobile vehicle using the Lyapunov's feedback control design technique. The system equations of motion are derived followed by finding the Lyapunov function required to design the controller. Owing to the discontinuity, originating from a sign function in the control law, the proposed control system is discontinuous. Therefore, the existence, continuity, and uniqueness of the solution are proven utilizing the Filippov's solution. Afterwards, the asymptotic stability of the control system is proven using the extensions of Lyapunov's stability theory to nonsmooth systems, and LaSalle's invariant set theorem. Finally, the effectiveness of the proposed control system is validated using simulation studies. Results confirm that the controller keeps the system stable while provides good position tracking responses.