A novel obstacle avoidance heuristic algorithm of continuum robot based on FABRIK

Obstacle avoidance and path planning of continuum robots are challenging tasks due to the hyper-redundant degree of freedoms (DOFs) and restricted working environments. Meanwhile, most current heuristic algorithm-based obstacle avoidance algorithms exist with low computational efficiency, complex solution process, and inability to add global constraints. This paper proposes a novel obstacle avoidance heuristic algorithm based on the forward and backward reaching inverse kinematics (FABRIK) algorithm The update of key nodes in this algorithm is modeled as the movement of charges in an electric field, avoiding complex nonlinear operations The algorithm achieves the robustness of inverse kinematics and path tracking in complex environments by imposing constraints on key nodes and determining the location of obstacles in advance This algorithm is characterized by a high convergence rate, low computational cost, and can be used for real-time applications. The proposed approach also has wide applicability and can be applied to both mobile and fixed-base continuum robots And it can be further extended to the field of hyper-redundant robots. The algorithm’s effectiveness is further validated by simulating the path tracking and obstacle avoidance of a five-segment continuum robot in various environments and comparisons with classical methods.