一种新型低自由度仿生四足机器人的设计

Dong Zhang, Xiaolin Yan, Rixing Li, Zhongyi Guo
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摘要

目前的四足机器人是根据自然界的四足动物来设计的,使用复杂的控制算法来实现四足机器人的运动和行走,这造成了仿生机器人设计难度大、生产成本高等问题。为了解决上述问题,本文将设计一种四足运动机器人,该机器人可以快速行走,转弯和跨越障碍物,成本低,控制简单。首先,在SOLIDWORKS中建立所设计四足运动机器人的简化三维模型和具体机械结构的三维模型,确保机构设计的合理性。其次,将简化后的模型导入ADAMS进行运动学仿真,完成四足机器人模型参数的设置和定义,验证机械结构方案的可行性。然后,根据复杂的机械结构环境,将部分关键设计部件导入ANASY进行结构有限元分析,验证机构关键部件的刚度和强度是否满足设计要求。最后,结合理论设计搭建了一个真实的四足机器人,并在真实环境中投入运行。通过对仿真结果的对比,验证了整个四足机器人方案的可行性和合理性。
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Design of an Unconventional Bionic Quadruped Robot with Low-degree-freedom of Movement
The current quadruped robots are designed based on the quadruped animals in the natural world, and use complex control algorithms to realize the movement and walking of the quadruped robots, which cause problems such as difficult design of bionic robots and high production costs. In order to solve the above-mentioned problems, this paper will design a four-legged sports robot that can walk quickly, turn and cross obstacles at low cost and simple control. First, establish a simplified threedimensional model of the quadruped motion robot designed and a three-dimensional model of the specific mechanical structure in SOLIDWORKS to ensure the rationality of the mechanism design. Secondly, import the simplified model into ADAMS for kinematics simulation, complete the setting and definition of the parameters of the quadruped robot model, and verify the feasibility of the mechanical structure scheme. Then, according to the complex mechanical structure environment, some key design parts are imported into ANASY for structural finite element analysis to verify whether the stiffness and strength of the key parts of the mechanism meet the design requirements. Finally, a real quadruped robot was built in combination with theoretical design and put into operation in a real environment. The simulation results were compared to verify the feasibility and rationality of the quadruped robot program as a whole.
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Multiagent Motion Planning Based on Deep Reinforcement Learning in Complex Environments Design of an Unconventional Bionic Quadruped Robot with Low-degree-freedom of Movement Action Recognition Method for Multi-joint Industrial Robots Based on End-arm Vibration and BP Neural Network Multi-Mission Planning of Service Robot Based on L-HMM Obstacle Avoidable G2-continuous Trajectory Generated with Clothoid Spline Solution
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