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A method for the synthesis of dynamic control is presented. The method is based on an exact modelling of manipulator dynamics and a relatively simple synthesis of control algorithms. The authors have applied the method to a UMS‐2 industrial robot.

In the paper is presented the practical application of the manipulator automatic two‐level control concept. Anthropomorphic configuration of the system was chosen, consisting of the minimal configuration, which solves the task of attaining the position and the gripper, which has to satisfy correct orientation in approaching the working object, as well as manipulation of the same. The manipulator configuration, chosen in that way, was applied to the concrete task of final treatment of the thermostatic element for the automobile industry. Realization project of this system contains three basic elements:

The purpose of this study is to present an optimization-based gait planning method for biped robots according to the conditions of terrain, which takes fully the relationship between walking stability margin and energy efficiency into account.

First, the authors newly designed a practical gait motion synthesis algorithm by using the optimal allowable zero moment point (ZMP) variation region (OAZR), which can generate different gait motions corresponding to different terrains based on the modifiability of ZMP in lateral (y-axis) direction. Second, an effective gait parameter optimization algorithm is performed to find the optimal set of key gait parameters (step length, duration time of gait cycle, average height of center of mass (CoM), amplitude of the vertical CoM motion and double support ratio), which maximizes either the walking stability margin or the energy efficiency with certain walking stability margin under practical constraints (mechanical constraints of all joint motors, geometric constraints, friction force limit and yawing moment limit) according to the conditions of terrain. Third, the necessary controllers for biped robots have been introduced briefly.

The experiment data and results are described and analyzed, showing that the proposed method was verified through simulations and implemented on a DRC-XT biped robot.

The main contribution is that the OAZR has been defined based on AZR, which could be used to plan and generate the various feasible gait motions to help a biped robot to adapt effectively to various terrains.

This paper presents algorithms for computing the angular velocities of the bodies of a multibody system. A multibody system is any collection of connected bodies. The focus is upon multibody systems consisting of spherically pinned rigid bodies which do not form closed loops. Simple formulae are presented for computing the angular velocities. It is shown that once the angular velocities are known the entire kinematical description and hence, the dynamics of the system, may be developed routinely and in automated fashion. Extension to more general multibody systems follows without conceptual change in the procedures.

Spatial ability is essential for engineers’ professional performance. Several studies describe it as a skill that can be enhanced using new technologies. Virtual reality (VR) is an emerging technology that is proving very useful for training different skills and improving spatial perception. In this chapter, the authors firstly present some previous works that use VR to train students, mainly in the area of engineering studies, and which demonstrate that VR can improve some aspects of the spatial perception. This study took a group of engineering students who used VR technologies to carry out learning activities designed to improve their spatial perception, which was measured with a widely used spatial ability test. The results obtained confirm that the use of VR technologies can improve students’ spatial perception. This proposal is easily transferable to other educational contexts. On the one hand, it could be implemented to improve spatial ability in other engineering studies, and on the other hand, with simple adaptation, it could be used to enhance other skills.

Generally, humanoid robots usually suffer significant impact force when walking or running in a non-predefined environment that could easily damage the actuators due to high stiffness. In recent years, the utilization of passive compliant series elastic actuators (SEA) for driving humanoid's joints has proved the capability in many aspects so far. However, despite being widely applied in the biped robot research field, the stable control problem for a humanoid powered by the SEAs, especially in the walking process, is still a challenge. This paper proposes a model reference adaptive control (MRAC) combined with the back-stepping algorithm to deal with the parameter uncertainties in a humanoid's lower limb driven by the SEA system. This is an extension of our previous research (Lanh et al., 2021).

Firstly, a dynamic model of SEA is obtained. Secondly, since there are unknown and uncertain parameters in the SEA model, a Model Reference Adaptive Controller (MRAC) is employed to guarantee the robust performance of the humanoid's lower limb. Finally, an experiment is carried out to evaluate the effectiveness of the proposed controller and the SEA mechanism.

This paper proposes an effective control algorithm that can be widely applied for the humanoid-SEA system. Besides, the effect of the coefficients in the control law is analyzed to further improve the response's quality.

Even though the simulation shows good results with stable system response, the practical experiment has not been implemented to fully evaluate the quality of the controller.

The MRAC is applied to control the humanoid's lower limb and the back-stepping process is utilized to combine with an external SEA system but still maintain stabilization. The simplified model of the lower-limb system proposed in the paper is proven to be appropriate and can be taken for further research in the future.

The purpose of this paper is to present an improved concept of software‐based laboratory exercises, namely a Virtual Laboratory for Engineering Sciences (VLES).

The implementation of distance learning and e‐learning in engineering sciences (such as Mechanical and Electrical Engineering) is still far behind current practice in narrative disciplines (Economics, Management, etc.). This is because education in technical disciplines requires laboratory exercises, providing skill‐acquisition and hands‐on experience. In order to overcome this problem for distance‐learning developers and practitioners, a new modular and hierarchically organized approach is needed.

The concept involves simulation models to emulate system dynamics, full virtual reality to provide visualization, advanced social‐clubbing to ensure proper communication, and an AI tutor to supervise the lab work. Its modularity and hierarchical organization offer the possibility of applying the concept to practically any engineering field: a higher level provides the general framework – it considers lab workplaces as objects regardless of the technical field they come from, and provides communication and supervision – while the lower level deals with particular workplaces. An improved student's motivation is expected.

The proposed concept aims rather high, thus making the work truly challenging. With the current level of information and communication technologies, some of the required features can only be achieved with difficulty; however, the rapid growth of the relevant technologies supports the eventual practicality of the concept. This paper is not intended to present any final results, solutions, or experience. The idea is to promote the concept, identify problems, propose guidelines, and possibly open a discussion.

The purpose of this paper is to design a novel optimized biped robot gait generator which plays an important role in helping the robot to move forward stably. Based on a mathematical point of view, the gait design problem is investigated as a constrained optimum problem. Then the task to be solved is closely related to the evolutionary calculation technique.

Based on this fact, this paper proposes a new way to optimize the biped gait design for humanoid robots that allows stable stepping with preset foot-lifting magnitude. The newly proposed central force optimization (CFO) algorithm is used to optimize the biped gait parameters to help a nonlinear uncertain humanoid robot walk robustly and steadily. The efficiency of the proposed method is compared with the genetic algorithm, particle swarm optimization and improved differential evolution algorithm (modified differential evolution).

The simulated and experimental results carried out on the small-sized nonlinear uncertain humanoid robot clearly demonstrate that the novel algorithm offers an efficient and stable gait for humanoid robots with respect to accurate preset foot-lifting magnitude.

This paper proposes a new algorithm based on four key gait parameters that enable dynamic equilibrium in stable walking for nonlinear uncertain humanoid robots of which gait parameters are initiatively optimized with CFO algorithm.

The purpose of this paper is to test the measurement performances of a planar‐type meander sensor installed in robot foot in order to examine its potential application as ground reaction force sensor.

A planar‐type meander sensor is composed of two pairs of meander coils. Variation of input inductance between coils serves as a measure of small displacements in a plane. Pairs of meander coils are installed in an actuated robot foot to measure displacements proportional to normal or tangential components of ground reaction force which acts upon the foot. The sensor was modeled by the concept of partial inductance and a new simulation tool was developed based on this concept.

Pairs of meander coils were tested against angular displacements, and results showed that the sensor gives correct information about displacement regardless how the foot touches the ground with its whole area. Deviations between position of computed and real acting point of ground reaction force are relatively small. Owing to good results obtained, a miniaturized sensor was developed having the same performances as previously developed prototype.

This paper presents initial work in implementing a planar‐type meander sensor in robot foot as to measure ground reaction force. Developed simulation tool gives accurate analysis of inductance variation of meander structures. In addition, the measurement error and sensor's nonlinearity are analyzed. Calculated results show a good agreement with experimental results. Hence, miniaturized sensor, easier for implementation, is proposed.

Humanoid robots have complicated dynamics, and they lack dynamic stability. Despite having similarities in kinematic structure, developing a humanoid robot with robust walking is quite difficult. In this paper, an attempt to produce a robust and expected walking gait is made by using an ALO (ant lion optimization) tuned linear inverted pendulum model plus flywheel (LIPM plus flywheel).

The LIPM plus flywheel provides the stabilized dynamic walking, which is further optimized by ALO during interaction with obstacles. It gives an ultimate turning angle, which makes the robot come closer to the obstacle and provide a turning angle that optimizes the travel length. This enhancement releases the constraint on the height of the COM (center of mass) and provides a larger stride. The framework of a sequential locomotion planer has been discussed to get the expected gait. The proposed method has been successfully tested on a simulated model and validated on the real NAO humanoid robot.

The convergence curve defends the selection of the proposed controller, and the deviation under 5% between simulation and experimental results in regards to travel length and travel time proves its robustness and efficacy. The trajectory of various joints obtained using the proposed controller is compared with the joint trajectory obtained using the default controller. The comparison shows the stable walking behavior generated by the proposed controller.

Humanoid robots are preferred over mobile robots because they can easily imitate the behaviors of humans and can result in higher output with higher efficiency for repetitive tasks. A controller has been developed using tuning the parameters of LIPM plus flywheel by the ALO approach and implementing it in a humanoid robot. Simulations and experiments have been performed, and joint angles for various joints are calculated and compared with the default controller. The tuned controller can be implemented in various other humanoid robots