Research on Kinematics and Dynamics of Intelligent Robots

1、 Introduction

With the rapid progress of technology, intelligent robots have gradually penetrated into various fields of our lives, from industrial production to medical services, and then to home services, the presence of intelligent robots can be seen everywhere. In order to enable robots to perform tasks more efficiently, precise control of robots has become crucial. This cannot be achieved without in-depth research on robot kinematics and dynamics. This article will provide a detailed exploration of the kinematics and dynamics of intelligent robots.



2、 Intelligent robot kinematics

Kinematics Fundamentals 

The kinematics of intelligent robots mainly studies the temporal variation of motion parameters such as the position, velocity, and acceleration of each joint of the robot. It focuses on the position and posture of the robot's end effector in space, which is the foundation of robot navigation, positioning, and motion planning.

kinematic model 

The kinematic modeling of intelligent robots is crucial for understanding their motion characteristics. By establishing coordinate systems for each link of the robot and determining the relative position and attitude between the links, the position and attitude of the robot's end effector can be derived. Common kinematic modeling methods include D-H parameter method, improved D-H parameter method, space vector method, etc.

Forward kinematics and inverse kinematics

Forward kinematics calculates the position and posture of the end effector in space based on the angle values of each joint of the robot. Reverse kinematics, on the other hand, calculates the required angle values for each joint based on the target position and posture of the robot's end effector. Reverse kinematics is one of the core issues in robot control, as it directly determines whether the robot can accurately perform tasks.


Kinematic optimization and trajectory planning

In the application of intelligent robots, in order to meet the needs of different tasks, it is necessary to plan reasonable robot motion trajectories. This involves kinematic optimization problems, which involve finding the optimal robot motion trajectory under certain constraint conditions (such as obstacle avoidance, shortest time, etc.). Kinematic optimization and trajectory planning are important means to improve the efficiency and stability of robot motion.

The challenges of intelligent robot kinematics in practical applications

Although kinematic theory provides a theoretical basis for the motion control of intelligent robots, it still faces many challenges in practical applications. For example, how to accurately obtain the angle values of each joint of a robot? How to update the motion status of robots in real-time? How to quickly solve inverse kinematics problems, etc. These problems need to be solved through advanced sensor technology, computer vision technology, and optimization algorithms.


3、 Dynamics of intelligent robots

Fundamentals of Dynamics

The dynamics of intelligent robots mainly study the relationship between robot motion and force. It focuses on the forces and torques generated by the joints of the robot, as well as how these forces and torques affect the robot's motion state. Dynamic analysis is the key to evaluating the load capacity, stability, and dynamic response performance of robots.

Dynamic modeling

The dynamic modeling of intelligent robots is the foundation for understanding the dynamic characteristics of robots. By establishing the dynamic equations of the robot, the relationship between the forces, torques, and motion states of each joint of the robot can be described. Common dynamic modeling methods include Newton Euler method, Lagrange method, Kane method, etc.

Dynamic analysis and control

Dynamic analysis can help us understand the dynamic performance of robots, such as acceleration, inertial force, joint driving torque, etc. Through dynamic analysis, we can evaluate the load capacity, stability, and dynamic response performance of robots. Meanwhile, dynamic control is an important means to achieve precise motion control of robots. Common dynamic control methods include powerful/hybrid control, impedance control, adaptive control, etc.

Dynamics optimization and simulation

Dynamic optimization is the optimization design of the structural and control parameters of a robot through optimization algorithms to improve its dynamic performance and stability. Dynamic simulation, on the other hand, simulates the motion process of a robot through a computer, predicting its motion performance and dynamic response. Dynamics optimization and simulation provide important theoretical support and practical guidance for the design and control of robots.
The challenges of intelligent robot dynamics in practical applications
In the practical application of intelligent robots, dynamic problems also face many challenges. For example, how to accurately measure the force and torque of a robot? How to adjust control strategies in real-time to adapt to changes in the dynamic environment of robots? How to reduce the complexity of dynamic calculations to improve control accuracy and real-time performance. These problems need to be solved through advanced sensor technology, control algorithms, and computing techniques.
4、 Conclusion
The kinematics and dynamics of intelligent robots are important branches in robotics, which respectively study the motion laws of robots and the relationship between motion and force. By conducting in-depth research on the kinematics and dynamics of intelligent robots, we can better understand and control their motion behavior, improve their performance and application scope. In the future, with the continuous development of intelligent technology, research on robot kinematics and dynamics will continue to deepen, providing strong support for the innovation and progress of intelligent robots.