A Precise Inverse Kinematics Solution Method for Parallel Tripedal Robots

Inverse kinematics contributes significantly to the execution of trajectory planning and control operations in robotics. Traditional inverse kinematics algorithms, predominantly utilized in serial robotic arm control, often lack precision and have limited applicability in parallel-legged robotic systems. To enhance the accuracy of solving inverse kinematics for planar bipedal robots, this paper introduces a design for a parallel tripedal robot and establishes its inverse kinematics model in a two-dimensional plane. Subsequently, a Sequential Quadratic Programming (SQP) algorithm integrated with a Sequential Habitat Genetic Algorithm is devised to address the inverse kinematics equations of the robot, constrained by a linear inverted pendulum model, enabling the tripedal robot to navigate various environments without the need for feedback. Compared to conventional SQP methods, this algorithm expands the solution scope and enhances computational accuracy. Additionally, this paper proposes a hierarchical NSGA-SQP algorithm, which, when compared to the traditional NSGA-SQP algorithm, further augments solution precision. Ultimately, to validate the accuracy and versatility of the proposed algorithm, simulation experiments were conducted, and the algorithm was deployed in real-world scenarios, confirming its feasibility and applicability.