This paper presents a numerical algorithm to model the impact between articulated structures, or between an articulated structure and an object. The proposed algorithm, called impulse articulated-body algorithm (IABA), is based on the ABA but uses impulses and velocities rather than forces and accelerations. The algorithm also inherits the advantages of the ABA: versatility and low computational cost. The IABA provides a method to determine the impact impulse, without increasing the order of the algorithm.

This paper investigates the stable-running problem of a planar underactuated biped robot, which has two springy telescopic legs and one actuated joint in the hip. After modeling the robot as a hybrid system with multiple continuous state spaces, a natural passive limit cycle, which preserves the system energy at touchdown, is found using the method of Poincaré shooting. It is then checked that the passive limit cycle is not stable. To stabilize the passive limit cycle, an event-based feedback control law is proposed, and also to enlarge the basin of attraction, an additive passivity-based control term is introduced only in the stance phase. The validity of our control strategies is illustrated by a series of numerical simulations.

A new type of 28-DOF (degree of freedom) full-size humanoid robot, driven by a closed-chain type of joint actuation system, is developed in this paper. Each leg of the robot is composed of six joints, where three are at the hip, one is at the knee, and two are at the ankle. The robot has six joints for each arm, one balancing joint, and three joints for the head, with two cameras. The weight of the robot is 75 kg, and its height is 168 cm.

The actuation systems of the pitching joint for the arms and legs of the robot are designed based on a closed-chain mechanism composed of four bar links driven by a ball screw, and each leg of the robot is designed to support 95 kg weight to include a 20 kg payload that can be carried by the robot arms having very light designs (with weight 8.5 kg), but each capable of carrying a 10 kg payload.

An analysis of the closed-chain joint actuation systems of a light arm capable of handling heavy objects is performed, and the light arm is designed via finite-element method analysis performed using ANSYS. In addition, the kinematic analysis and the detailed structure of the arm and leg of the robot are performed.

The main controller uses the ARM processor and a distributed controller for the leg joints is developed using the TMS320c2407 processor with the communications between the main and joint controllers being performed via the CAN system.

Good performances of the proposed robot is demonstrated by presenting several experimental results; these include (1) experimentally handling a 13 kg payload, (2) through walking experiments of the robot supporting a 85 kg load, and (3) measurements of the arm and leg joint motors while performing walking experiments.

The main goal of this paper is the design of 4PUS+1PS parallel manipulator, using an optimization problem that takes into accounts the characteristics of the workspace and dexterity. The optimization problem is formulated considering constraints on actuated and passive joint limits. A comparison between quantum particle swarm Optimization (QPSO) and PSO is developed. Two numerical examples are presented, which reveal the advantages of QPSO to PSO. Moreover, it is shown that by introducing the dexterity index as a quality measure throughout the workspace, the parallel manipulator is improved at the cost of a minor reduction in its workspace.

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.

The postural stability of bipedal robots is investigated in perspective of foot-rotation during locomotion. With foot already rotated, the biped is modeled as an underactuated kinematic structure. The stability of such biped robots is analyzed by introducing the concept of rotational stability. The rotational stability investigates whether a biped would lead to a flat-foot posture or the biped would topple over. The rotational stability is quantified as a ground reference point named “rotational stability index (RSI)” point. Conditions are established to achieve rotational stability during biped locomotion using the concept of the RSI point. The applicability of the RSI point is illustrated through experimentation for the landing stability analysis of the bipedal jumping gaits.

The traditional stability criteria such as zero-moment point (ZMP) [M. Vukobratovic and B. Borovac, “Zero-moment point – thirty five years of its life,” Int. J. Humanoid Robot. 1(1), 157–173 (2004)] and foot-rotation indicator (FRI) [A. Goswami, “Postural stability of biped robots and the foot-rotation indicator (FRI) point,” Int. J. Robot. Res. 18(6), 523–533 (1999)] are not applicable to analyze biped's postural stability when foot is already rotated. The RSI point is established as a stability criteria for planar bipedal locomotion in presence of foot rotation.

The real-time balance PD control of an eight-link biped robot using a zero-moment point (ZMP) dynamic model is implemented using two alternative intelligent computing control techniques that were compared: one based on support vector regression (SVR) and another based on a first order Takagi–Sugeno–Kang (TSK) -type neural-fuzzy (NF). Both methods use the ZMP error, and its variation as inputs and the output is the correction of the robot's torso necessary for its sagittal balance. The SVR and the NF were trained based on simulation data, and their performance was verified with a real biped robot. Two performance indexes are proposed to evaluate and compare the online performance of the two control methods.

The ZMP is calculated by reading four force sensors placed under each robot's foot. The gait implemented in this biped is based on ankle and hip human trajectories that were acquired and adapted to the robot's size. Some experiments are presented and the results show that the implemented gait combined either with the SVR controller or with the TSK NF network controller can be used to control this biped robot. The SVR and the NF controllers exhibit similar stability, but the SVR controller runs at 0.2 ms, about 50 times faster than the NF controller and much faster than a controller based on full ZMP dynamic model equations.

A mechanical design and dynamics walking simulation of a novel tripod walking robot are presented in this paper. The tripod walking robot consists of three 1-degree-of-freedom (DOF) Chebyshev–Pantograph leg mechanisms with linkage architecture. A balancing mechanism is mounted on the body of the tripod walking robot to adjust its center of gravity (COG) during walking for balancing purpose. A statically stable tripod walking gait is performed by synchronizing the motions of the three leg mechanisms and the balancing mechanism. A three-dimensional model has been elaborated in SolidWorks® engineering software environment for a characterization of a feasible mechanical design. Dynamics simulation has been carried out in the MSC.ADAMS® environment with the aim to characterize and to evaluate the dynamic walking performances of the proposed design with low-cost easy-operation features. Simulation results show that the proposed tripod walking robot with proper input torques, gives limited reaction forces at the linkage joints, and a practical feasible walking ability on a flatten ground.

In this paper, we have reported a trajectory planning for a 1-degree-of-freedom clutched robotic arm. This novel robotic arm has only one actuator, but it can work in a spatial space by using a proper clutch system and a suitable trajectory planning. An algorithm has been proposed for generating a prescribed trajectory by means of seven operation modes, which are generated by different states of clutches.

A new localization algorithm is proposed for a fast moving mobile robot, which utilizes only one beacon and the global features of the differential-driving mobile robot. It takes a relatively long time to localize a mobile robot with active beacon sensors, since the distance to the beacon is measured based on the traveling time of the ultrasonic signal. When the mobile robot is moving slowly, the measurement time does not yield a high error. At a higher speed, however, the localization error becomes too large for the mobile robot to be located accurately. Therefore, in high-speed mobile robot operations, instead of using two or more active beacons, only one active beacon and the global features of the mobile robot are used to localize the mobile robot. The two global features are the radius and center of the rotational motion for the differential-driving mobile robot, which generally describe the motion of, and are used for the trace prediction of, a mobile robot. In high-speed operations, the localizer finds the intersection point of this predicted trace and the circle, which is centered at the beacon whose radius is the distance between the mobile robot and the beacon. This new approach overcomes the large localization error caused by the high speed of the mobile robot. The performance of the new localization algorithm is verified through experiments with a high-speed mobile robot.

Independent mobility is one of the major challenges for elderly. Assistive robots must guarantee user's safety. Existing methods to quantitatively express user's safety are not applicable to mobility assistance robots due to physical attachment. This paper proposes a danger index to estimate user's safety during mobility assistance. The formulation and validation of the index is achieved through extensive subjective and objective experimentation. A motion control method is also introduced that uses the proposed danger index for monitoring user's safety and initiating proper safety actions in case of danger. As an example, experimental results with SpiderBot-II are reported in this paper.

This paper presents a new planar passive dynamic model with contact between the feet and the ground. The Hertz contact law and the approximate Coulomb friction law were introduced into this human-like model. In contrast to McGeer's passive dynamic models, contact stiffness, contact damping, and coefficients of friction were added to characterize the walking model. Through numerical simulation, stable period-one gait and period-two gait cycles were found, and the contact forces were derived from the results. After investigating the effects of the contact parameters on walking gaits, we found that changes in contact stiffness led to changes in the global characteristics of the walking gait, but not in contact damping. The coefficients of friction related to whether the model could walk or not. For the simulation of the routes to chaos, we found that a small contact stiffness value will lead to a delayed point of bifurcation, meaning that a less rigid surface is easier for a passive model to walk on. The effects of contact damping and friction coefficients on routes to chaos were quite small.

This paper presents a novel trajectory planning method for a flexible Cartesian robot manipulator in a point-to-point motion. In order to obtain an exact mathematical model, the parameters of the equation of motion are determined from an identification experiment. An artificial neural network is employed to generate the desired base position, and then, a particle swarm optimization technique is used as the learning algorithm, in which the sum of the displacements of the manipulator is chosen as the objective function. We show that the residual vibrations of the manipulator can be suppressed by minimizing the displacement of the manipulator. The effectiveness and validity of the proposed method are demonstrated by comparing the simulation and experimental results.