A new approach to generating smooth piecewise local trajectories for mobile robots is proposed in this paper. Given the configurations (position and direction) of two points, we search for the trajectory that minimizes the integral of acceleration (tangential and normal). The resulting trajectory should not only be smooth but also safe in order to be applicable in real-life situations. Therefore, we investigate two different obstacle-avoidance constraints that satisfy the minimization problem. Unfortunately, in this case the problem becomes more complex and not suitable for real time implementations. Therefore, we introduce two simple solutions, based on the idea of polynomial fitting, to generate safe trajectories once a collision is detected with the original smooth trajectory. Simulation results of the different algorithms are presented.

This paper will review, firstly, the state and trend of robotics in Japan, and secondly, how to promote a rapid increase of robot population in Japan. Finally, in anticipation of the coming 21st century, human-robot symbiosis is discussed in connection with social implications.

This paper presents a practical approach for the point-to-point control of elastic-jointed robot manipulators. With the proposed approach only position and velocity feedback are referenced, as opposed to most of the existing control schemes of elastic-jointed manipulators which require additional acceleration and/or jerk feedback. To guarantee the robustness of the controller, it is designed on extreme parameter uncertainties due to highly elastic joints of manipulators and energy motivated Lyapunov functions are used to derive the control law. Four pertinent controller gains are chosen in light of the on-line position and velocity feedback of the links and joint sensors. Through a simulated experimental verification, it is demonstrated that the designed simple position and velocity feedback controller, similar to that used for rigid-jointed robots, can globally stabilize the elastic-jointed robot for a bounded reference position. In addition, the tracking performance of the controller reveals that this simple control algorithm is robust in terms of joint flexibility. And the simplicity of the presented control algorithm, as compared to other model-based techniques for flexiblejoint robots, is particularly advantageous. Even though the simulated experiments are conducted on a single-link flexible joint robot, control law derived in this paper has general meaning for multi-link flexible joint robots.

A versatile architecture is presented to implement autonomous vehicles. The focus idea consists of a set of standalone modules, called wireless robotic components wireless robotic components (WRCs). Each component performs a particular function by means of a radio modem interface, a processing unit, and a sensor/actuator. The components interact through a coordinator that redirects asynchronous requests to the appropriate WRCs, configuring a built-in network. The WRC architecture has been tested in marine and terrestrial platforms to perform tasks of waypoint and wall following. Results show that the tested system complies with adaptability and portability that allow conforming a variety of autonomous vehicles.

The present research aims to model, simulate and implement a new hybrid control approach based on a combination of proportional integral derivative (PID) Controller and Model Reference Adaptive Controller (MRAC), in which Lyapunov’s theory is used to ensure asymptotic stability to control a two degrees of freedom (DoF) manipulator driven by McKibben’s artificial pneumatic muscles. The MRAC controller works as a nonlinearity compensator and PID controller works during the transient period, as the MRAC performs poorly in this regime. This new approach is entitled Hybrid Model Reference Adaptive Controller (H-MRAC) and it has an unprecedented topological structure based on three terms. The feedforward term acts in disturbances rejection, the derivative term in oscillations damping and the feedback term acts in error convergence to zero. In this article, a control system dedicated to pneumatic manipulators was developed. As a result, proof of asymptotic convergence was performed for the proposed topological approach, which was validated on a two DoF manipulator. The proposed mechanism satisfactorily met the ISO/TS 15066 standard, and the position tracking obtained a global error of 37.69% and 51.01% smaller than found in the literature examples, entitled MRAC and A-PID, respectively, for simulations and 37.46% and 30.25% for experiments.

In the paper a formal model is presented of the discrete control of a bile robot moving over a plane. The model synthesis has been directed in such a way as to justify the use as a controller of the automaton with internal and external parameters. It has been shown that, while controlled in discrete time the mobile robot performance can be expressed by a one-sidely optimized tree of a two-person extensive game. The tree, after transforming into the form of the state diagram of an automaton, serves as a basis for the synthesis of the automaton with internal and external parameters playing the role of a controller. A method is presented of synthesizing an automaton of this type, being a hardware realization of the mobile robot controller.

The problem of path planning for a mobile robot has been studied extensively in recent literature. Much of the work in this area is devoted to the study of path planning for an earth-bound robot in two dimensions. In this paper, we explore the problem for a robot that can fly in three dimensional space or crawl on 3D surfaces or use a combination of both. We assume that the obstacles can be modeled as polyhedral objects.

Vision-based tracking of an object using perspective projection inherently results in non-linear measurement equations in the Cartesian coordinates. The underlying object kinematics can be modelled by a linear system. In this paper we introduce a measurement conversion technique that analytically transforms the non-linear measurement equations obtained from a stereo-vision system into a system of linear measurement equations. We then design a robust linear filter around the converted measurement system. The state estimation error of the proposed filter is bounded and we provide a rigorous theoretical analysis of this result. The performance of the robust filter developed in this paper is demonstrated via computer simulation and via practical experimentation using a robotic manipulator as a target. The proposed filter is shown to outperform the extended Kalman filter (EKF).

This paper presents a real-time algorithm for modifying the trajectory of a manipulator approaching a moving target. The algorithm is based on the superposition scheme; a model developed based on human motion behavior. The algorithm generates a smooth trajectory toward the new target by calculating the vectorial sum between the first trajectory (initial position and first target) and second trajectory (between first and second target location). The algorithm searches for the switch hme that will result in a minimum time trajectory. The idea of the algorithm is to define some domain where the optimal switching time can be found, reduce this domain as much as possible to decrease the number of the points that must be checked and try every remaining candidate in this domain to find numerically the best (optimal) switch time. The algorithm was implemented on an Adept-one robotic system taking into account velocity constraints. The actual velocity profile was found to be less smooth than specified by the mathematical model. When the switch occurs at the middle of the trajectory when the speed is close to its maximum, the change in the movement direction is performed more gently.

In most of our daily motion tasks, the coordination between limbs is very crucial for successful execution of the tasks. In this paper, coordination among oscillators controlling in Cartesian space is studied to control bipedal walking. In our method, phase adjustment among oscillators is considered as one of the key issues to achieve coordination. A new phase adjustment method is proposed. With this method, an oscillator is able to coordinate other oscillators and maintain a desired phase relationship. This property is important for the walking control especially when external perturbations are given. To simplify the relationship between oscillators in a central pattern generator (CPG), a hierarchical CPG structure is adopted, where a main oscillator will be used to adjust other oscillators. In the simulation, the walking motion controlled by the CPG controller converges to a stable pattern even with external perturbations. We have implemented the controller in both the simulation model and real hardware robot.

This paper introduces a simple method for obtaining the pure 3-D translational motion parameter (without rotation) and the translation parameter with a known rotation of a camera. Once the translation vector is available, the 3-D structure of an object can also be obtained. The minimum number of matching points in the two images can be as few as two, and the equations to be solved are linear. Synthetic and real image tests has been performed, and good results have been obtained.

Motion and constraint identification are the fundamental issue throughout the development of parallel mechanisms. Aiming at meaningful result with heuristic and visualizable process, this paper proposes a machine learning-based method for motions and constraints modeling and further develops the automatic software for mobility analysis. As a preliminary, topology of parallel mechanism is characterized by recognizable symbols and mapped to the motion of component limb through programming algorithm. A predictive model for motion and constraint with their nature meanings is constructed based on neural network. An increase in accuracy is obtained by the novel loss function, which combines the errors of network and physical equation. Based on the predictive model, an automatic framework for mobility analysis of parallel mechanisms is constructed. A software is developed with WebGL interface, providing the result of mobility analysis as well as the visualizing process particularly. Finally, five typical parallel mechanisms are taken as examples to verify the approach and its software. The method facilitates to attain motion/constraint and mobility of parallel mechanisms with both numerical and geometric features.

This article designs a robotic Chinese character writing system that can resist random human interference. Firstly, an innovative stroke extraction method of Chinese characters was devised. A basic Chinese character stroke extraction method based on cumulative direction vectors is used to extract the components that make up the strokes of Chinese characters. The components are then stitched together into strokes based on the sequential base stroke joining method. To enable the robot to imitate handwriting Chinese character skills, we utilised stroke information as the demonstration and modelled the skills using dynamic movement primitives (DMPs). To suppress random human interference, this article combines improved DMPs and conductance control to adjust robot trajectories based on real-time visual measurements. The experimental results show that the proposed method can accurately extract the strokes of most Chinese characters. The designed trajectory adjustment method offers better smoothness and robustness than direct rotating and translating curves. The robot is able to adjust its posture and trajectory in real time to eliminate the negative impacts of human interference.

Earth-contact mechanism (ECM), a type of mechanism to keep the system in contact with the earth and to move with the terrain changes. This paper uses the virtual equivalent parallel mechanism (VEPM) to convert the terrain data into the kinematical variables of the moving platform in the VEPM, and further analyzes the performance of the VEPM at each terrain point. Then, the comprehensive performance of the VEPM is chosen as the optimization goal, and a task-oriented dimensional optimization approach combined with the particle swarm algorithm and the neural network algorithm is proposed. This paper conducted a comparative experiment to verify the superiority of the new approach in optimizing the ECM’s comprehensive performance, whose performance analysis also can be applied into the layout design of the ECM. This paper proposed an analysis method to construct the ECM’s performance map based on the digital terrain map, which helps the control system and operator to make the optimal control decision.

This paper presents a compliant variable admittance adaptive fixed-time sliding mode control (SMC) algorithm for trajectory tracking of robotic manipulators. Specifically, a compliant variable admittance algorithm and an adaptive fixed-time SMC algorithm are combined to construct a double-loop control structure. In the outer loop, the variable admittance algorithm is developed to adjust admittance parameters during a collision to minimize the collision time, which gives the robot compliance property and reduce the rigid collision influence. Then, by employing the Lyapunov theory and the fixed-time stability theory, a new nonsingular sliding mode manifold is proposed and an adaptive fixed-time SMC algorithm is presented in the inner loop. More precisely, this approach enables rapid convergence, enhanced steady-state tracking precision, and a settling time that is independent of system initial states. As a result, the effectiveness and improved performance of the proposed algorithm are demonstrated through extensive simulations and experimental results.

Accurate prediction for mechanisms’ dynamic responses has always been a challenging task for designers. For modeling easiness purposes, mechanisms’ synthesis and optimization have been mostly limited to rigid systems, making consequently the designer unable to vow that the manufactured mechanism satisfies the target responses. To address this limitation, flexible mechanism synthesis is aimed in this work. Two benchmark mechanisms being the core of myriad mechanical devices are of scope, mainly, the flexible slider-crank and the four-bar. In addition to the mechanism dimensions, materials properties have been embedded in the synthesis problem. Two responses are of interest for the slider-crank mechanism, the slider velocity, and the midpoint axial displacement for the flexible connecting rod. Whereas five responses have been compiled for the four-bar mechanism synthesis. A comparative analysis of seven optimization techniques to solve the synthesis problem for both mechanisms has been performed. Subsequently, an executable computer-aided design tool for mechanisms synthesis has been developed under MATLAB®. Numerical outcomes emphasize the limits of a single-response-based synthesis for a flexible mechanism. It has been proven that combining different responses alleviates possible error and fulfill high-accuracy requirement.

It is standard now in undergraduate and graduate courses in robotics to teach the basic concepts of position control design strategies. Due to the geared motors inherent in most educational and industrial manipulators, sophisticated control design strategies such as the inverse dynamics technique cannot be easily demonstrated in a laboratory setting. A direct drive 5-bar-linkage manipulator with reduced motor torque requirements is proposed in this paper for such a purpose. The manipulator dynamics are easily understood by undergraduates and an inverse dynamics control strategy is suggested which can be easily designed by students at the undergraduate level.

This paper describes a hierarchical architecture for rhythmic movement generation, which suits a juggling-like task involving sensory-motor coordination. Our approach, which is interpreted as a “bidirectional weak coupling” to the environment, does not require a continuous monitoring of the environment, but can adapt a robot to a change in the environment, owing to the interaction between the robot and the environment at the ball contact. The proposed architecture contains two passive-control mechanisms, the “entrainment mechanism” and the “open-loop stable mechanism,” that lead to the emergence of a self-organized temporal order in the whole system. This dynamic temporal pattern enables a robot to perform a stable rhythmic movement. We demonstrate a robot which juggles two balls rebounding off the wall and confirm the effectiveness of our approach.