IKDP: Inverse Kinematics through Diffusion Process
Hao-Tang Tsui, Yu-Rou Tuan, Hong-Han Shuai
- 发表年份
- 2024
- 访问权限
- 开放获取
摘要
It is a common problem in robotics to specify the position of each joint of the robot so that the endpoint reaches a certain target in space. This can be solved in two ways, forward kinematics method and inverse kinematics method. However, inverse kinematics cannot be solved by an algorithm. The common method is the Jacobian inverse technique, and some people have tried to find the answer by machine learning. In this project, we will show how to use the Conditional Denoising Diffusion Probabilistic Model to integrate the solution of calculating IK. Index Terms: Inverse kinematics, Denoising Diffusion Probabilistic Model, self Attention, Transformer
关键词
相关论文
一种面向线弧增材制造的电动汽车结构可制造性拓扑优化的双环框架
Qiang Cui, Chuan Yu, Daoqian Yang 等 5 位作者
Robotics and Computer-Integrated Manufacturing · 2026
几何数字孪生:一种用于航空发动机装配精度预测的数字智能模型
Ke Shang, Xin Jin, Teli Xu 等 7 位作者
Robotics and Computer-Integrated Manufacturing · 2026
通过人工智能驱动的机器人技术革新产业
Aryan Chaudhary
Recent Advances in Computer Science and Communications · 2026
新型大口径偏置馈电可展开天线设计与动态性能预测
Chuang Shi, Tianming Liu, Ning Xue 等 9 位作者
Aerospace Science and Technology · 2026