This paper demonstrates how numerical optimization techniques can efficiently be used to create self-stable running motions for a human-like robot model. Exploitation of self-stability is considered to be a crucial factor for biological running and might be the key for success to make bipedal and humanoid robots run in the future. We investigate a two-dimensional simulation model of running with nine bodies (trunk, thighs, shanks, feet, and arms) powered by external moments at all internal joints. Using efficient optimal control techniques and stability optimization, we were able to determine model parameters and actuator inputs that lead to fully open-loop stable running motions.

The Stewart platform manipulator is a fully kinematic linkage system that has major mechanical differences from typical serial link robots. It is a six-axis parallel robot manipulator with a high force-to-weight ratio and good positioning accuracy that exceeds that of a conventional serial link robot arm. This study examines the dynamic equations and control methodology for a Stewart platform. Because manual symbolic expansion of Stewart platform robot dynamic equations is tedious, time-consuming, and prone to errors, an automated derivation process is highly desired. The main goal of this work is to present an efficient procedure for computer generation of dynamic equations for a Stewart platform manipulator. As MATLAB has a powerful signal processing toolbox along with symbolic processing capabilities and is widely used as a common technical computing environment in many universities and research laboratories, the objective of this study was to develop a MATLAB-based approach for symbolic computation for a parallel linked robot. Additionally, a computed-torque control methodology is utilized for such a structure. Simulation results demonstrate the effectiveness of the proposed control methodology.

A path planning algorithm for a spherical mobile robot rolling on a plane is presented in this paper. The robot is actuated by two internal rotors that are fixed to the shafts of two motors. These are in turn mounted on the spherical shell in mutually orthogonal directions. The system is nonholonomic due to the nonintegrable nature of the rolling constraints. Further, the system cannot be converted into a chained form, and neither is it nilpotent nor differentially flat. So existing techniques of nonholonomic path planning cannot be applied directly to the system. The approach presented here uses simple geometrical notions and provides numerically efficient and intuitive solutions. We also present the dynamic model and derive motor torques for execution of the algorithm. Along the proposed paths, we achieve dynamic decoupling of the variables making the algorithm more suitable for practical applications.

The inverse kinematics of a 12 degrees-of-freedom (DOFs) biped robot is formulated in terms of certain parameters. The biped walking gaits are developed using the parameters. The walking gaits are optimized using genetic algorithm (GA). The optimization is carried out considering relative importance of stability margin and walking speed. The stability margin depends on the position of zero-moment-point (ZMP) while walking speed varies with step-size. The ZMP is computed by an approximation-based method which does not require system dynamics. The optimal walking gaits are experimentally realized on a biped robot.

This paper deals with the computation of the orientation error and the kinematic model of a 3-DOF translational parallel manipulator called the RAF robot. We derived a simple analytical model allowing the computation of the orientation, generated by the deformation of the PKLs, when an external load is applied to the platform. These models allowed us to map the orientation error on the workspace of the robot. We showed in particular that the minimum orientation error can be obtained when the platform is in a certain region of its workspace. Due to its analytical nature, the developed model can also be used for a sensitivity analysis in order to maximize the manipulator precision.

In our previous work, a novel force control actuator, called series damper actuator (SDA), has been proposed. This paper proposes a general design procedure for the SDA system. From design requirements, several key parameters of the SDA plant can be determined. Based on these parameters, the selection or design of the series damper and the motor can be carried out. A case study is included to illustrate the effectiveness of the procedure. As there could be more than one feasible solutions from the procedure, the mechatronic design quotient (MDQ) method can be adopted to select the best solution from a feasible solution space.

This paper presents a quadratic programming (QP) form algorithm to realize on-line planning of mobile manipulators with consideration for improving the stability level. With Lie group and screw tools, the general tree topology structure mobile robot dynamics and dynamic stability attributes were analysed. The stable support condition for a mobile robot is constructed not only in a polygonal support region, but also in a polyhedral support region. For a planar supporting region, the tip-over avoiding requirement is formulated as the tip-over prevent constraints with the reciprocal products of the resultant support wrench and the imaginary tip-over twists, which are constructed with the boundaries of the convex support polygon. At velocity level, the optimized resolution algorithm with standard QP form is designed to resolve the inverse redundant kinematics of the Omni-directional Mobile ManipulatorS (OMMS) with stability considerations. Numerical simulation results show that the presented methods successfully improve the stability level of the robot within an on-line planning process.

This paper describes the development of a desktop robotic system that enables the plug-and-play function through the USB (universal serial bus) port of a personal computer (PC). Thus a new kind of desktop PC peripheral is invented that has programmable manipulability. The robotic system is realized on an internally distributed control structure that facilitates higher system reliability. A PID control algorithm is implemented on a prototype of the proposed system, to demonstrate the system's ability to implement feedback control. Experimental results show the performance and properties of the proposed system.

The present paper proposes a successful application of differential evolution (DE) optimized fuzzy logic supervisors (FLS) to improve the quality of solutions that extended Kalman filters (EKFs) can offer to solve simultaneous localization and mapping (SLAM) problems for mobile robots and autonomous vehicles. The utility of the proposed system can be readily appreciated in those situations where an incorrect knowledge of Q and R matrices of EKF can significantly degrade the SLAM performance. A fuzzy supervisor has been implemented to adapt the R matrix of the EKF online, in order to improve its performance. The free parameters of the fuzzy supervisor are suitably optimized by employing the DE algorithm, a comparatively recent method, popularly employed now-a-days for high-dimensional parallel direct search problems. The utility of the proposed system is aptly demonstrated by solving the SLAM problem for a mobile robot with several landmarks and with wrong knowledge of sensor statistics. The system could successfully demonstrate enhanced performance in comparison with usual EKF-based solutions for identical environment situations.

Space robotic systems are expected to play an increasingly important role in the future. Unlike on the earth, space operations require the ability to work in the unstructured environment. Some autonomous behaviors are necessary to perform complex and difficult tasks in space. This level of autonomy relies not only on vision, force, torque, and tactile sensors, but also the advanced planning and decision capabilities. In this paper, the authors study the autonomous target capturing from the issues of theory and experiments. Firstly, we deduce the kinematic and dynamic equations of space robotic system. Secondly, the visual measurement model of hand–eye camera is created, and the image processing algorithms to extract the target features are introduced. Thirdly, we propose an autonomous trajectory planning method, directly using the 2D image features. The method predicts the target motion, plans the end-effector's velocities and solves the inverse kinematic equations using practical approach to avoid the dynamic singularities. At last, numeric simulation and experiment results are given. The ground experiment system is set up based on the concept of dynamic simulation and kinematic equivalence. With the system, the experiments of autonomous capturing a target by a free-floating space robot, composed of a 6-DOF manipulator and a satellite as its base, are conducted, and the results validate the proposed algorithm.

This paper presents a polar-space kinematics control method to achieve simultaneous tracking and stabilization for an omnidirectional wheeled mobile robot with three independent driving omnidirectional wheels equally spaced at 120° from one another. The kinematic model of the robot in polar coordinates is presented. With the kinematic model, a kinematic control method based on feedback linearization is proposed in order to achieve simultaneous tracking and stabilization. The proposed method is easily extended to address the path following problem. Computer simulations and experimental results are presented to show the effectiveness and usefulness of the proposed control method at slow speeds.

This paper presents a distributed multiple mobile robots framework which allows programming and control of virtual and real mobile robots. The system provides the map building, path planning, robot task planning, simulation, and actual robot control functions in an indoor environment. Users can program the virtual robots in a customized simulation environment and check the performance of execution, i.e., if the simulation result is satisfying, users can download the code to a real robot. The paper focuses on the distributed architecture and key technologies of virtual robots simulation and control of real robots. A method for construction and transfer of a key index value (which stores the robot configuration) is proposed. Using this method, only the robot key configuration index is needed to build the robot in the virtual environment. This results in reduced network load and improved real time performance of the distributed system. Experiments were conducted to compare the performance of the proposed system with the performance of a centralized system. The results show that the distributed system uses less system resources and has better real time performance. What is more, this framework has been applied to Yaskawa's robot “SmartPal.” The simulation and experiment results show that our robotic framework can simulate and control the robot to perform complex tasks.

This paper describes a complete laser-based approach for tracking the pose of a robot in a dynamic environment. The main novelty of this approach is that the matching between consecutively acquired scans is achieved using their associated curvature-based representations. The proposed scan matching algorithm consists of three stages. Firstly, the whole raw laser data is segmented into groups of consecutive range readings using a distance-based criterion and the curvature function for each group is computed. Then, this set of curvature functions is matched to the set of curvature functions associated to the previously acquired laser scan. Finally, characteristic points of pairwise curvature functions are matched and used to correctly obtain the best local alignment between consecutive scans. A closed form solution is employed for computing the optimal transformation and minimizing the robot pose shift error without iterations. Thus, the system is outstanding in terms of accuracy and computation time. The implemented algorithm is evaluated and compared to three state of the art scan matching approaches.