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Bestsellers

Linear Algebra and Optimization with Applications to Machine Learning
Linear Algebra and Optimization with Applications to Machine Learning

Volume I: Linear Algebra for Computer Vision, Robotics, and Machine Learning
by Jean Gallier and Jocelyn Quaintance
Linear Algebra and Optimization with Applications to Machine Learning
Linear Algebra and Optimization with Applications to Machine Learning

Volume II: Fundamentals of Optimization Theory with Applications to Machine Learning
by Jean Gallier and Jocelyn Quaintance

 

  • articleNo Access

    Graphical Analysis of Local Sliding Failure of Roller Slope

    In this paper, for some typical local slump problems, through the site survey of engineering conditions, we observe the local slumping parts, collect a large number of production data, and adopt the Chiping polar projection method to evaluate the initial stability of the problem area. The unstable structure is combined with the solid scale projection to analyze the sliding direction, the sliding surface, the sliding amount, and the like. The study has a clearer understanding of the local slump problem, and based on the stability judgment results, combined with the site conditions, ultimately serves the engineering examples.

  • articleNo Access

    Dynamic Posture Stabilization Of Humanoid Robot NAO Using 3D-Multilinked Dual Spring-Loaded Inverted Pendulum Model for Uneven and Inclined Floor

    Gait pattern performance, for its crucial significance in humanoid robot stabilization, has attracted the attention of researchers worldwide. Although simplified models highlight major features, bipedal walking has bewildered the researchers. Therefore, for a precise understanding of the bipedal model, a state-of-the-art, simplified model has been proposed in this paper which comprises a 3D-multilinked dual spring-loaded inverted pendulum (3D-MDSLIP) while acknowledging the vertical fluctuations of the center of mass (CoM). In addition, the model considers upper body movement and its effects on the stabilization of the humanoid robot. The mathematical modeling of a humanoid walking over the obstacle and slope is demonstrated to precisely understand the problem. The tuning process of the parameters and postures in a humanoid robot is complex and time-consuming. For proper walking of a robot over uneven terrains and slopes, tuning of the PID controller is achieved using converged teaching-learning based optimization (CTLBO) technique for a central pattern generator (CPG) gait, as introduced in the paper. The optimal gait angles are applied to the experimental and simulated NAO to successfully navigate the provided terrain. Thus, the experimental and simulation results jointly show that the proposed CPG-CTLBO gait learning technique is feasible for finding an optimal gait pattern for the humanoid robot within a deviation of 5%. The energy efficiency of the proposed controller is compared with the default controller of NAO based on the average electronic current in sagittal and lateral movement. Further, it is examined for the energy consumption for several slopes, and the results obtained are acceptable, showing the controller is efficient. Additionally, it has been compared with an existing technique for walking a humanoid robot on uneven terrains. The graph obtained using the proposed technique demonstrates the superiority of the proposed technique.