IKBT: solving closed-form Inverse Kinematics with Behavior Tree
This addresses the limitations of numerical methods for robot arm planning and control, though it appears incremental as it builds on existing symbolic approaches with a new organizational framework.
The authors tackled the inverse kinematics problem for serial robot arms by developing a symbolic solver that integrates Behavior Trees to organize the equation-solving process, successfully solving 18 out of 19 example robots of 4-6 DOF and generating LaTeX reports and Python code templates.
Serial robot arms have complicated kinematic equations which must be solved to write effective arm planning and control software (the Inverse Kinematics Problem). Existing software packages for inverse kinematics often rely on numerical methods which have significant shortcomings. Here we report a new symbolic inverse kinematics solver which overcomes the limitations of numerical methods, and the shortcomings of previous symbolic software packages. We integrate Behavior Trees, an execution planning framework previously used for controlling intelligent robot behavior, to organize the equation solving process, and a modular architecture for each solution technique. The system successfully solved, generated a LaTex report, and generated a Python code template for 18 out of 19 example robots of 4-6 DOF. The system is readily extensible, maintainable, and multi-platform with few dependencies. The complete package is available with a Modified BSD license on Github.