Abstract. Controlling a biped robot with a high degree of freedom to achieve stable and straight movement patterns is a complex problem. With growing computational power of computer hardware, high resolution real time simulation of such robot models has become more and more applicable. This paper presents a novel approach to generate bipedal gait for humanoid locomotion. This approach is based on modified Truncated Fourier Series (TFS) for generating angular trajectories. It is also the first time that Particle Swarm Optimization (PSO) is used to find the best angular trajectory and optimize TFS. This method has been implemented on Simulated NAO robot in Robocup 3D soccer simulation environment (rcssserver3d). To overcome inherent noise of the simulator we applied a Resampling algorithm which could lead the robustness in nondeterministic environments. Experimental results show that PSO optimizes TFS faster and better than GA to generate straighter and faster humanoid locomotion.
Mobile robot localization is taken into account as one of the most important topics in robotics. In this paper, the localization problem is extended to the cases in which estimating the position of multi robots is considered. To do so, the Joint Probabilistic Data Association Filter (JPDAF) approach is applied for tracking the position of multiple robots. To characterize the motion of each robot, two models are used. First, a simple near constant velocity model is considered and then a variable velocity model is applied for tracking. This improves the performance when the robots change their velocity and conduct maneuvering movements. This issue gives an advantage to explore the movement of the manoeuvring objects which is common in many robotics problems such as soccer or rescue robots. Simulation results show the efficiency of the JPDAF algorithm in tracking multiple mobile robots with maneuvering movements.
Abstract. The slave robot of the macro-micro teleoperation system presented in this paper is a 1-DOF piezo actuator including hysteresis nonlinearity. This nonlinear behavior makes robot control a complex task. In this research the nonlinear and uncertain dynamics of the slave robot has been entered directly into the teleoperation control loop. The LuGre friction model is used as the estimator of the hysteresis loop to cancel out this undesirable term. A 2-DOF master-slave system is decomposed into two 1-DOF systems: a shape system representing the master-slave position coordination, and a locked system representing the dynamics of the coordinated system. For making the closed-loop teleoperation system passive against dynamic parameter uncertainty and force measurement inaccuracy, four virtual flywheels are designed. In this way, the energy generated by troublesome terms inside controllers (i.e. the terms which may endanger passivity of the controller) would be taken from the bounded kinetic energy deposited on these flywheels. Simulations are performed to show effectiveness of the proposed controllers.
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