A hyper-redundant manipulator(HRM) can flexibly accomplish tasks in narrow spaces. However, its excessive degrees of freedom pose challenges for path planning. In this letter, an ellipsoid-shape rapidly-exporing random tree (E-RRT*) method is proposed for path planning of HRMs in workspace, particularly those with angle limits. This method replaces line segments with ellipsoids to connect adjacent nodes. Firstly, an analysis of angle constraints of the HRM is conducted, providing restrictions on node selection during path planning. Secondly, a slow-speed informed guiding approach is introduced to optimize the sampling process. Finally, the obtained path is enhanced by adding control points and applying cubic polynomial interpolation to achieve path smoothing. Simulations demonstrate that the proposed E-RRT* method effectively solves the path planning problem for HRMs. Especially in narrow environments, appropriate informed guiding speeds enable E-RRT* to outperform other methods.

This article presents a geometric approach for path planning of serpentine manipulator for real-time control in confined spaces. Firstly, the mechanical design of a serpentine manipulator is introduced, and its kinematics is analyzed. As the serpentine manipulator usually has more than 10 degrees of freedom, the motion control and obstacle avoidance are difficult considering its inverse kinematics. Follow-the-leader is an ideal path planning method for serpentine manipulator, as the manipulator moves forward, all the sections follow the path that the tip of manipulator has passed, which simplifies the obstacle avoidance. The realization of follow-the-leader method is to find the new configurations of the manipulator that can fit the ideal path with small errors. In this article, a novel geometric approach for follow-the-leader motion is proposed to solve new configurations with high precision of location and less computation time. The method is validated through simulation and the deviation from the ideal path is analyzed, simulation results show that calculation time for per step is less than 0.5 ms for a serpentine manipulator with 10 sections. To verify the follow-the-leader method, a 13-degree-of-freedom serpentine manipulator system with 6 sections was built, and 12 magnetic rotary encoders were embedded into the universal joints to collect data of rotation angles of each section. Experimental results show that the manipulator can carry out follow-the-leader motion as expected in real time.

Hyper-redundant manipulator has a slim geometric shape and super high degrees of freedom (DOF), which promises high motion efficiency and flexible obstacle avoidance ability in a confined space. Nevertheless, it also challenges the more complicated motion control strategy. In this article, the concepts of “link eigenvectors” and “manipulator's eigenpoints,” which apply to a widely used geometric kinematics method, are proposed. Hence, the kinematic and dynamic models can be constructed intuitively. And since the indirect joint space and local frames are replaced by the link eigenvectors and unified global frame, the kinematic and dynamic problems, especially the link's position, velocity, and acceleration, can be solved more directly. Further, based on the new models, mechanical analysis and Newton–Euler dynamic equations are effectively simplified, so as to realize the fast and precise dynamic resolution. Experiment results show that the kinematic and dynamic theoretical models are correct. And the driving forces of motors are successfully optimized, while the kinematic precision is improved simultaneously.

While a great number of degree of freedom (DOF) of hyper-redundant manipulators brings superior dexterity, it also challenges the more complicated kinematics algorithms. The kinematics method can not only affect its flexibility and obstacle avoidance ability, but also determine whether it runs efficiently and reliably. Hence, in this article, an effective kinematics method has been proposed based on the morphologic space constraints. It decomposes the resolution of inverse kinematics into two steps: 1) setting the target morphologic space and 2) tracking the morphologic space. In addition, because the proposed kinematics method would calculate the link end positions first but not the joint parameters, this article discards the joint space and obtains the configuration space more directly, by which the method would be more intuitive and efficient. Afterward, a serpentine scanning motion mode, which is efficient, reliable, and of high performance in obstacle avoidance, was studied. Simulation and experiment results show that the kinematics method and serpentine scanning motion mode can meet the requirements of real-time control and obstacle avoidance.

Hyper-redundant manipulator systems (HRMSs) have significant applications in various scenarios. Due to their excessive degrees of freedom (DOF), they can navigate into confined spaces and perform tasks such as exploration, detection, and maintenance. However, its flexibility also renders its motion planning highly challenging. This article proposes an efficient motion planning method for HRMSs, based on path finding and path following. First, the characteristics of a typical HRMS are introduced, and the kinematic model of the HRMS is established. Following that, a path tracking algorithm for the HRMS is introduced. This algorithm integrates a ‘follow the leader’ (FTL) approach with traditional methods to enhance path following efficiency. Thirdly, an improved APF-RRT* algorithm is proposed. This algorithm aims to find suitable paths in the workspace while reducing algorithmic dimensionality. It combines the advantages of both APF and RRT* algorithms. Additionally, an angle correction force field is incorporated for high efficiency. Several sampling-based methods are optimized and compared for analysis. Simulation results show that Improved APF-RRT* can efficiently solve the path planning problem of the HRMS, especially in complex environments. In addition, the smoothing method based on Bezier curves makes the path perform better.

Snake-like robots, which have high degrees of freedom and flexibility, can effectively perform an obstacle avoidance motion in a narrow and unstructured space to complete assignments efficiently. However, accurate closed-loop control is difficult to achieve. On the one hand, this is because adding too many sensors to the robot will significantly increase its mass, size, and cost. On the other hand, the more complex structure of the hyper-redundant robot also challenges the more elaborate closed-loop control strategy. For these reasons, a cable-driven snake-like robot, which is compact and low cost, with force transducers and angle sensors, is designed in this article. The simpler and more direct kinematic model is studied, which applies to a widely used kinematics algorithm. Based on the kinematic model, the inverse dynamics are resolved. Finally, this article analyzes the sources of the motion errors and achieves dual-loop control through force-feedback and pose-feedback. The experiment results show that the robot’s structure and dual-loop control strategy function with high accuracy and reliability, meeting the requirements of engineering applications and high-precision control.