International Journal of Humanoid Robotics

This article proposes a novel strategy to generate both a human-like walking pattern and a human-like zero moment point (ZMP) trajectory for a biped android robot. In general, the motion-capture technique has been widely utilized to obtain a walking pattern that is kinematically similar to the walking of a human. However, in addition to kinematic considerations, a suitable ZMP shaping technique is necessary to apply the human gait derived by motion capturing to biped robots more effectively. In previous research by the authors, a walking pattern generation strategy was developed considering the kinematics using motion capturing and Fourier fitting. However, it was found that there were differences between the calculated ZMP trajectory of the earlier research and the measured ZMP trajectory directly derived from the sensor in this research. Therefore, the differences and their factors are analyzed and a new strategy is proposed that effectively reduces the differences between them. Finally, the proposed strategy is shown to be effective for generating human-like walking pattern and ZMP trajectory for biped android robots through stick figure simulations.

Stability analysis is one of the main issues in the research area of biped robots with point feet. This article develops stability analysis and robust control of a planar biped robot with point feet with one degree of underactuation. A stability analysis is presented for the bipedal motion comprising single support and impact phases by using Poincaré map for nonlinear systems. Then, the stability conditions of periodic orbits are derived and stable gait pattern is determined using an optimization process. Thereafter, a robust sliding mode control with a time-invariant feedback is proposed to track stable gait in the presence of parameter uncertainties of the biped. Proposed approach is carried out for two types of bipeds, namely, a normal model and a balanced model in which the biped center of mass located at the hip using a novel model. Energy efficiency of biped is investigated for both models. Moreover, the stability of biped motion is studied in the presence of an unexpected stair. Simulation results show the biped motion quickly converges to cyclic motion during the first gait in both models.

Fan out (FO) is adopted as a general index among human robot interaction researchers in predicting the maximum number of robots a single operator can handle simultaneously while maintaining performance at acceptable levels. Neglect tolerance model forms the basis for FO metric that assumes ideal conditions wherein the operator switches control between robots sequentially based on acceptable performance ignoring any false alarms due to erroneous interactions. In this article, we redefine the FO metric to account for any additional demands due to the occurrence of false alarms, as these additional demands could lead to task failure. Experiments with our virtual and real humanoid soccer robots across tele-operation and semi-autonomous modes of autonomy showed significant drop in FO predictions with inclusion of demands due to false alarms for all experimental cases.

This article describes a joint trajectory optimized controller developed in a humanoid robot simulator following the real robot characteristics. As simulation is a powerful tool for speeding up the control software development, the proposed accurate simulator allows to fulfill this goal. The simulator, based on the Open Dynamics Engine and GLScene graphics library, provides instant visual feedback. The proposed simulator, with realistic dynamics, allows to design and test behaviors and control strategies without access to the real hardware in order to carry out research on robot control without damaging the real robot. The low-level joints controller techniques, such as acceleration, speed, and energy consumption minimization, are discussed and experimental results are presented in order to validate the proposed simulator.

The forward and inverse dynamic models of the underactuated 2-DOF finger have been established in this article based on virtual spring approach. This approach not only avoids the solution of differential-algebraic equations but also leads to a completely decoupled dynamic model that is ideal for directly inverse dynamic analysis, real-time dynamic simulation and control. To verify this approach, an underactuated 3-joint finger has been brought forward. Simulation results from Matlab/Simulink are consistent with those obtained from ADAMS grasp simulations. For the hand real-time dynamic control, the velocity observer has been established based on the dynamic model, the adaptive curve fitting with the observer has obtained precise velocity signals, made up the uncertain parameters such as torsion spring, inertial, damps, etc. and achieved ideal results. By applying dynamics model and observer, the force-based impedance control can realize more accurate and stable force control during grasp.

Traditional planning of biped robot walking patterns solves optimal trajectory for minimizing energy consumption. However, a diversity of biped robot walking functions lead to a variety of walking types. The walking patterns to implement a variety of biped robot objectives should have enough parameters to cope with their functions. In this article, walking patterns based on two 4-3-4 polynomials for the trajectories of biped robot waist and lower limb are proposed. The main advantage of the walking pattern is that 4-3-4 polynomials containing the parameters of acceleration and deceleration for biped walking make the implementation of a variety of walking types possible. In the study, the prototype mechanism of a biped robot is designed. After that, the direct and inverse kinematic equations of the biped robot are derived. For studying motion energy of biped robots, kinetic and potential energies are also defined. Based on these definitions, the parameters of the biped robot trajectories for minimum motion energy are solved. The solution is summarized by a development procedure. In addition, the study of zero moment point (ZMP) during the biped robot in walking is included.

The visual detection of robots is a difficult but relevant problem in several robotic applications. In this article, a framework for the robust and fast visual detection of legged robots is proposed. This framework uses cascades of nested classifiers, the Adaboost boosting algorithm, and domain-partitioning-based weak classifiers. Using the proposed framework, frontal, profile, and back detectors for AIBO robots (model ERS7), as well as detectors for humanoid robots, are built. The detection rate (DR) of the obtained systems is quite high: 90% with an average of 0.1 false positives (FPs) per image, when the final detections are filtered out using context information (horizon line). In addition, a robot referee that uses these detectors to track players during a soccer game is described. Experiment results showed that the referee achieves very high robot DRs (98.7% DR with ~ 1 false detection every 16 images) and fast processing speed.

The present article designed a genetic quadratic particle swarm optimization (GQPSO). Aiming at the low particle diversity at the early searching stage of quadratic particle swarm optimization (QPSO), the method adopts mutation and exchanging and regenerating mechanisms from genetic algorithm so as to avoid premature convergence and improves optimization. Meanwhile, the present article gave a comprehensive consideration to decision elements such as cost, resources, and service in the process of automotive parts' logistics, transportation, and loading; a model of automotive parts' logistics, transportation, and loading optimization was set up. GQPSO was introduced for solutions. Simulation examples show that GQPSO improves the computational efficiency, significantly, and there is a higher probability of searching the global optimum. It provides optimization method for the automobile parts' logistics and transportation plans.