A Hybrid Obstacle-Avoidance Method of Spatial Hyper-Redundant Manipulators for Servicing in Confined Space

Abstract

SummaryDue to a large number of redundant degrees of freedom (DOFs), the hyper-redundant manipulator shows outstanding dexterity and adaptability in avoiding the obstacles in confined space. In this paper, a hybrid obstacle-avoidance method of spatial hyper-redundant manipulators is proposed, with both efficiency and accuracy considered. The space around an obstacle is classified into safe, warning, and dangerous zones. A two-level protection strategy is then addressed to handle the obstacle-avoidance problem from qualitative (i.e., pseudo-distance based on super-quadric function) and quantitative (i.e., Euclidean distance based on practical geometry function) perspectives, respectively. The only condition for switching between the two-level protections is the value of pseudo-distance. Then, a modified modal method, which is a trajectory planning method, is presented to plan the collision-free trajectory of the manipulator by maximizing the minimum pseudo-distance or Euclidean distance in different zones. Some parameters, including the arm-angle parameters and the equivalent link length parameters, are defined to represent the manipulator configuration. They are adjusted to avoid the obstacle, singularity, and joint limit. The simulations of 12-DOF manipulator and an experiment of 18-DOF manipulator verify the proposed methods.

Collision-free kinematics for hyper-redundant manipulators in dynamic scenes using optimal velocity obstacles

“…Fahimi et al 14 present a mode shape technique-based approach to resolve the OA problem for hyper-redundant manipulators. Mu et al 15 propose a new strategy named hybrid OA method, which can be used in OA motion planning for hyper-redundant manipulators.…”

“…It can be observed that the algorithms in the literature 17,39 do not consider the obstacles in the workspaces. In the literature, 7,15,18,33,37 although the proposed approaches can avoid collisions, they cannot be applied to the dynamic working environments. Moreover, the algorithms in Rolf et al 17 and Safeea et al 37 only apply to 2D workspaces.…”

“…9,10 This limit leads to the development of shape trajectory control approaches, which use differential geometry to formulate the closed-form modal inverse kinematic solutions and adjust the manipulator configurations to avoid the obstacles. [11][12][13][14][15] Those approaches to solve the inverse kinematic problem are only for limited kinematic models, which constrain the performance (dexterity in cluttered environments) of the hyper-redundant manipulators and restrict their potential applicability.…”

An obstacle avoidance algorithm for space hyper-redundant manipulators using combination of RRT and shape control method

“…Another interesting backbone-curve-based method is presented in ref. [42], with a novel modified modal approach [49]. In this work, the macro shape of the manipulator is constrained by the modified backbone curve.…”

Novel Method of Obstacle Avoidance Planning for Redundant Sliding Manipulators

“…The application of artificial intelligence methods based on neural networks provides a new idea for manipulator control. These methods are considered to be very promising since its excellent learning ability [22]- [24]. Xu et al [8], [25] propose a novel kinematic controller based on a recurrent neural network (RNN) which is competent in model adaption.…”