Dynamic Modeling and Simulation of a Yaw-Angle Quadruped Maneuvering With a Planar Robotic Tail

2016 ◽  
Vol 138 (8) ◽  
Author(s):  
William Rone ◽  
Pinhas Ben-Tzvi
Keyword(s):  
Dynamic Modeling ◽  
Trajectory Planning ◽  
Frequency Modulation ◽  
Quadruped Robot ◽  
Contact Friction ◽  
Ground Contact ◽  
Cycle Frequency ◽  
Tail Structure ◽  
Yaw Angle ◽  
The Impact

This paper analyzes the impact a planar robotic tail can have on the yaw-angle maneuvering of a quadruped robot. Tail structures ranging from a one degree-of-freedom (1DOF) pendulum to a 6DOF serpentine robot are simulated, along with a quadruped model that accounts for ground contact friction. Tail trajectory generation using split-cycle frequency modulation is used to improve net quadruped rotation due to the tail's motion. Numerical results from the tail and quadruped models analyze the impact of trajectory factors and tail structure on the net quadruped rotation. Results emphasize the importance of both tangential and centripetal tail loading for tail trajectory planning and show the benefit of a multi-DOF tail.

scholarly journals Time-jerk optimal trajectory planning of hydraulic robotic excavator

2021 ◽  
Vol 13 (7) ◽  
pp. 168781402110346
Author(s):  
Yunyue Zhang ◽  
Zhiyi Sun ◽  
Qianlai Sun ◽  
Yin Wang ◽  
Xiaosong Li ◽  
...  
Keyword(s):  
Angular Velocity ◽  
Trajectory Planning ◽  
Optimal Trajectory ◽  
High Efficiency ◽  
Optimal Solution ◽  
Optimal Time ◽  
Target Point ◽  
Robotic Excavator ◽  
The Impact ◽  
Optimal Trajectory Planning

Due to the fact that intelligent algorithms such as Particle Swarm Optimization (PSO) and Differential Evolution (DE) are susceptible to local optima and the efficiency of solving an optimal solution is low when solving the optimal trajectory, this paper uses the Sequential Quadratic Programming (SQP) algorithm for the optimal trajectory planning of a hydraulic robotic excavator. To achieve high efficiency and stationarity during the operation of the hydraulic robotic excavator, the trade-off between the time and jerk is considered. Cubic splines were used to interpolate in joint space, and the optimal time-jerk trajectory was obtained using the SQP with joint angular velocity, angular acceleration, and jerk as constraints. The optimal angle curves of each joint were obtained, and the optimal time-jerk trajectory planning of the excavator was realized. Experimental results show that the SQP method under the same weight is more efficient in solving the optimal solution and the optimal excavating trajectory is smoother, and each joint can reach the target point with smaller angular velocity, and acceleration change, which avoids the impact of each joint during operation and conserves working time. Finally, the excavator autonomous operation becomes more stable and efficient.

Combined Trajectory Planning and Tracking for Autonomous Vehicles on Deformable Terrains

2020 ◽  
Author(s):  
James Dallas ◽  
Yifan Weng ◽  
Tulga Ersal
Keyword(s):  
Neural Network ◽  
Trajectory Planning ◽  
Autonomous Vehicles ◽  
Performance Metrics ◽  
Soft Soil ◽  
Computation Time ◽  
Operating Conditions ◽  
The Neural Network ◽  
Vehicle Response ◽  
The Impact

Abstract In this work, a novel combined trajectory planner and tracking controller is developed for autonomous vehicles operating on off-road deformable terrains. Common approaches to trajectory planning and tracking often rely on model-dependent schemes, which utilize a simplified model to predict the impact of control inputs to future vehicle response. However, in an off-road context and especially on deformable terrains, accurately modeling the vehicle response for predictive purposes can be challenging due to the complexity of the tire-terrain interaction and limitations of state-of-the-art terramechanics models in terms of operating conditions, computation time, and continuous differentiability. To address this challenge and improve vehicle safety and performance through more accurate prediction of the plant response, in this paper, a nonlinear model predictive control framework is presented that accounts for terrain deformability explicitly using a neural network terramechanics model for deformable terrains. The utility of the proposed scheme is demonstrated on high fidelity simulations for a notional lightweight military vehicle on soft soil. It is shown that the neural network based controller can outperform a baseline Pacejka model based scheme by improving on performance metrics associated with the cost function. In more severe maneuvers, the neural network based controller can achieve sufficient fidelity as compared to the plant to complete maneuvers that lead to failure for the Pacejka based controller. Finally, it is demonstrated that the proposed framework is conducive to real-time implementability.

A Simple Dynamic Modeling of Head Slap in Hard Disk Drive

2001 ◽  
Author(s):  
Seong-Hun Lee ◽  
Jeong-Hak Lee ◽  
Kwang-Joon Kim
Keyword(s):  
Hard Disk Drive ◽  
Dynamic Modeling ◽  
Structural Design ◽  
Continuous System ◽  
Disk Drive ◽  
Lumped Parameter Model ◽  
Test Results ◽  
Lumped Parameter ◽  
Shock Resistance ◽  
The Impact

Abstract In order to understand mechanism of the impact between head and disk of a HDD subject to a shock and to improve the shock resistance effectively, it is essential to develop a dynamic model which can represent well the head slap. Although motion of the head and disk subject to a shock requires modeling by a continuous system to be rigorous, in this study, a simplified lumped parameter model is developed to understand basic dynamics of the head slap and to determine crucial parameters for the improvement of the structural design. In addition, drop test results of the HDD are presented to back to up the derived model.

THE MOTION ANALYSIS AND TRAJECTORY PLANNING OF STATIC GAIT FOR THE QUADRUPED ROBOT

2017 ◽  
Author(s):  
RUINA DANG ◽  
PENG XU ◽  
QICHANG YAO ◽  
BO SU ◽  
LEI JIANG ◽  
...  
Keyword(s):  
Motion Analysis ◽  
Trajectory Planning ◽  
Quadruped Robot
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