Design and Kinematics on Biased Channel Retractable Continuum Robot

Fast inverse kinematics (IK) algorithm is significant for real-time precise motion control for continuum and soft manipulators. In this paper, we studied an explicit expression of a two-segment continuum manipulator based on constant curvature assumptions and discussed the existence of the IK solutions. Utilizing the pseudo-rigid-body method, we contrast this model with the traditional six-axis rigid industrial robot arm, revealing that two-segment extensible continuum manipulators exhibit limited rotation angles around the directional vector of their tips, thereby showcasing reduced dexterity. By pre-constraining five degrees-of-freedom (DOF) and addressing the definition of the remaining DOF, we streamline the IK-solving process, resulting in minimal computational overhead suitable for a wide range of applications. This model promises a robust and real-time approach for controlling two-segment extensible continuum manipulators, enhancing their operational efficiency and effectiveness.

Continuum manipulators can exhibit behaviors similar to snakes, elephant's trunks, and octopus tentacles, which possess incredible dexterity and intrinsic compliance for safe interaction with unstructured environments. However, the lack of enough stiffness limits their scope and application. In this paper, we introduce four different structures of continuum manipulators, including a simple structure with three elastic actuated rods, a structure with a passive rigid kinematic chain, a structure with a hyperelastic notochord and a segmental structure inspired from the spine without articular structure. This paper presents an experimental comparison of four continuum manipulators and aims to explore approaches to enhance the stiffness of a continuum manipulator and maintain the simple constant curvature kinematics as far as possible simultaneously. Results of this paper contribute to guiding the design of a continuum manipulator for achieving desired stiffness properties.

Purpose Slim and dexterous manipulators with long reaches can perform various exploration and inspection tasks in confined spaces. This paper aims to present the development of such a dexterous continuum manipulator for potential applications in the aviation industry. Design/methodology/approach Benefiting from a newly conceived dual continuum mechanism and the improved actuation scheme, this paper proposes a design of a slim and dexterous continuum manipulator. Kinematics modeling, simulation-based dimension synthesis, structural constructions and system descriptions are elaborated. Findings Experimental validations show that the constructed prototype possesses the desired dexterity to navigate through confined spaces with its kinematics calibrated and actuation compensation implemented. The continuum manipulator with different deployed tools (e.g. graspers and welding guns) would be able to perform inspections and other tasks at remote locations in constrained environments. Research limitations/implications The current construction of the continuum manipulator possesses quite some friction inside its structure. The bending discrepancy caused by friction could accumulate to an obvious level. It is desired to further reduce the friction, even though the actuation compensation had been implemented. Practical implications The constructed continuum manipulator could perform inspection and other tasks in confined spaces, acting as an active multi-functional endoscopic platform. Such a device could greatly facilitate routine tasks in the aviation industry, such as guided assembling, inspection and maintenance. Originality/value The originality and values of this paper mainly lay on the design, modeling, construction and experimental validations of the slim and dexterous continuum manipulator for the desired mobility and functionality in confined spaces.

Continuum manipulators can operate in complex environments where traditional rigid manipulators fail. However, the modeling of inverse kinematics remains challenging because of its inherent nonlinearities and various external conditions. This work proposes an online learning control framework with a data cache pool utilizing a constant‐curvature model inspired neural network (CCMINN) model to obtain the inverse kinematics model of tendon‐actuated continuum manipulators. The CCMINN model is a kind of geometric relationships‐inspired neural network, which is inspired by the geometric relationships within the constant‐curvature model. This model improves the ability of traditional fully connected neural network models on high convergence speed and precision through its constant‐curvature inspiration layers. These layers embed geometry insights into the neural network structure rather than loss functions like physics‐informed neural networks. The online learning framework enables CCMINN to maintain high control accuracy in a variety of external load scenarios. Experiments show average tracking errors of 1.4 mm, 1.38 mm, and 1.48 mm (0.7%, 0.64%, and 0.74% of the continuum manipulator length) in the free space, under constant and variable loading conditions, respectively. The results show that combining the fast‐converging CCMINN with an online learning control framework enables high‐precision and robust positioning control of continuum manipulators under various external payloads.

PurposeThe purpose of this paper is to present a novel hybrid pre-tension mechanism for continuum manipulators to prevent wire slack and improve continuum robot payload capacity, as well as to present a new method to control continuum manipulators’ shape.Design/methodology/approachThis research explains the hardware design of a hybrid pre-tension mechanism device and proposes a mathematic formulation wire-tension based on robot design. Also, the wire-tension control method and payload estimation model would be discussed.FindingsWire-tension is directly related to the continuum manipulators’ rigidity and accuracy. However, in the case of robot motion, wires lose their tension and such an issue leads to the inaccuracy and twist deformation. Therefore, the proposed design assists in preventing any wire slack and derailing the problem of the wires.Originality/valueThe novelty of this research is proposed pre-tension mechanism device design and control schematics. Proposed pre-tension mechanism designed to maintain up to eight wires simultaneously.

Due to the space constraints and obstacles, the traditional industrial manipulator is too difficult to achieve some tasks, such as the gluing for the wing bulkhead of the aircraft and the maintenance for cooling pipes of the nuclear power plant, etc. Continuum manipulator, inspired by the trunk and the tentacle, proves to be very effective for above-mentioned tasks. A novel octopus-like biomimetic robots, is proposed in this paper, which is consisting of continuum joints and discrete joints, and provide a host of benefits, such as the large space of movement, the high flexibility and the heavy load. A novel analytical approach for solving kinematics of the octopus-like arm manipulator with mixed joints is presented in this paper. Based on the bionic mechanism of the continuum manipulator constructed from mixed joints, the robot configuration is established. In this paper, we present a detailed formulation and explanation of a novel kinematic model for the continuum robots with mixed joints. The modeling method based on the Denavit–Hartenberg parameters(also called DH parameters) is used to depict the motion of robot. The robot is comprised of the continuum joint and the rotated joint, so the kinematic model of continuum joint is crucial for constructing that of the whole robot. The continuum joint is equivalent to a section of elastic body, whose D-H parametors can be obtain from the constant-curvature method. Then the forward kinematics of the whole robot can be builded in a D-H frame. Research results will create a new modeling method for the octopus-like continuum manipulators with mixed joints, which can give a new approach for the design on the biomimetic manipulators operating in the unstructured envirement.

Continuum manipulators are continuously bending robots with unlimited number of kinematic degrees of freedom. Most existing continuum manipulators have a central strut made of a single elastic material, and multiple cables placed around the strut are employed to actuate the manipulator. The kinematics for such robots has been extensively studied by assuming the manipulator has a circular shape. In this paper, we aim to investigate the kinematic and static modeling for novel soft continuum manipulators fabricated by multi-material 3D printing with heterogeneous soft materials. We model cylindrical shape manipulators consisting of three sections with three different materials, and they are actuated by three independent cables placed symmetrically. By pulling the cables with different displacements, the manipulators can be bent in three-dimensional space. As our initial study, we employ a single cable for all prototypes. Experimental results are compared with the simulation results to validate the proposed modeling method.

This study proposes an innovative algorithm integrating kinematic modeling and intelligent optimization to address the motion planning of multi-segment cable-driven continuum manipulator. Under the piecewise constant curvature (PCC) hypothesis, a forward kinematic framework is formulated to define a structured mapping between joint-space parameters and task-space coordinates. Leveraging the established model, a refined APF strategy is implemented to synthesize collisionavoidance paths for the manipulator, while the Jacobian pseudo-inverse method is applied to obtain corresponding general joint angle solutions. Moreover, to enhance optimization efficiency, the initial population is generated by leveraging the least-squares solution as a baseline, with search boundaries dynamically defined through the null-space properties of the Jacobian pseudoinverse. Then the trajectory optimization is executed under dual constraints of end-effector pose and arm shape via the cheetah optimizer (CO). Numerical simulations validate the algorithm's capability to maintain trajectory tracking accuracy while accounting for end-effector pose, providing an effective solution for motion planning of multi-segment continuum manipulators.

In this work, we consider the problem of controlling the end effector position of a continuum manipulator through local stiffness changes. Continuum manipulators offer the advantage of continuous deformation along their lengths, and recent advances in smart material actuators further enable local compliance changes, which can affect the manipulator's bulk motion. However, leveraging local stiffness change to control motion remains lightly explored. We build a kinematic model of a continuum manipulator as a sequence of segments consisting of symmetrically arranged springs around the perimeter of every segment, and we show that this system has a closed form solution to its forward kinematics. The model includes common constraints such as restriction of torsional or shearing movement. Based on this model, we propose a controller on the spring stiffnesses for a single segment and provide provable guarantees on convergence to a desired goal position. The results are verified in simulation and compared to physical hardware.

Tendon-sheath actuation mechanism is widely used in surgical robot, especially in endoscopic surgery, due to its capable of providing remote force and action transmission through long and flexible channel. However, hysteresis, backlash, nonlinear friction are the drawbacks of this mechanism. Our surgical robot use continuum manipulator which is useful in endoscopic surgery, due to its flexible and simple structure. Unlike other literatures that focus on tendon-sheath compensation only, the continuum manipulator is also taken into application level analysis. A model based feedforward motion compensation for tendon-sheath driven continuum manipulator is presented. The model is validated by using optical tracking system to trace the distal end position. Experiment result shows that the proposed model reduces the position error less than 5%.

Perception is an essential component of an intelligent autonomous system. However, the traditional sensors used in robotics and industrial are limited when considering high mobility, wide distribution, and possible wireless operation of the sensors in sensor networks. The self-powered sensing solves the most shackling issue in the current sensing field, thus enabling many previously unattainable application scenarios. In this paper, a novel variable-length continuum manipulator with self-powered sensors is designed, and an adaptive capture control scheme based on deep learning prediction is proposed for the envelope grasp of a fixed cylinder target and the hook grasp of a ring target moving in a small range. First, adaptive capture parameters of the manipulator are generated according to a target’s size and position. Then, deep neural networks are utilized to accurately predict the bending angle of the manipulator with a large displacement motion at the tip of the continuum manipulator. Finally, based on the feedback data from the driving motor’s built-in angular velocity sensor on the continuum manipulator, a set of capture criteria are presented to identify the envelope and capture states of the target. The capture experimental results on a prototype reveal that the generated parameters highly match the targets. The prediction method’s accuracy is higher than that of conventional feedforward neural networks. The capture criteria based on the feedback data from driving motor’s built-in angular velocity sensor can correctly identify the target capture states. In additional, the future research of the adaptive capture control based on self-powered sensors is discussed.

Continuum manipulators have attracted lots of interests in the past few years, due to their super flexibility and dexterity. In this paper, a cable-driven flexible finger is designed and analyzed based on continuum mechanism. Compared with traditional rigid-link fingers, the proposed flexible finger shows excellent compliance and adaptivity. Mathematic models are necessary before real applications. However, accurate modeling of this kind of continuum mechanism is always a challenge. A large number of existing researches applied Piecewise Constant Curvature assumption to establish the kinematic model, but they totally neglected effect of statics, leading to unacceptable errors. This paper proposes the Unit Constant Curvature assumption to establish the static model based on Newton-Euler method, which considers effect of actuating tensions, gravity, external loads and internal contact forces. Based on the proposed static model, simulations are made to investigate the deformation of the flexible finger under various loading conditions. Results show that the finger profile greatly depends on forces and moments applied by both its own actuators and external environments.

It is important to enable a robot to manipulate a target object that has no 3-D model information and is situated in an environment with other unknown objects nearby. This poses an open problem of how to combine perception and manipulation to enable the robot to build an appearance-based model of the target object on the spot to facilitate further manipulation of the object while avoiding the other unknown obstacles in the way. In this paper, we introduce an approach to enable a continuum manipulator, which is apt to maneuver through a crowded environment, to gradually build a 3-D surface model of the target object by moving an RGB-D sensor around the object while also detecting and avoiding surrounding unknown obstacles. Our approach interleaves perception and manipulation such that perception guides the manipulator movement, which in turn allows more perception of the target object for object model building and further manipulator motion. Our approach is characterized by a progressive strategy to register RGB-D images of the target object to build and extend a partial model of the object and the corresponding motion planning strategy for the continuum robot to carry out model building and avoid obstacles at the same time. To demonstrate the effectiveness of our approach, experiments on progressive model building of real objects from real RGB-D images are conducted, where a simulated continuum robot plans and executes its motion to carry the RGB-D camera around a target object for taking those images in an augmented reality setting.

Additive manufacturing is an automated process for producing layer-by-layer material deposition. Recently this technology has been introduced in the industrial construction in order to print houses or smaller piece structures for on-site assembly, with complex geometry. In Additive manufacturing processes, the material deposition step is generally followed by a printing quality inspection step. However, the geometry of printed structures with minimal surfaces is sometimes complex, where rigid structure robots cannot reach certain zones to scan their surfaces. In this paper, a continuum-hyper-redundant manipulator equipped with a camera is attached to the end-effector of a mobile-manipulator robot for the quality inspection process. Indeed, Continuum manipulators can bend along structures with complex geometry; and this inherent flexibility makes them suitable for navigation and operation in congested environments. The number of controlled actuators being greater than the dimension of task space, this work is summarized in a trajectory tracking of hyper-redundant robots. This issue lies in the resolution of strongly nonlinear equations with a realtime computation. Thus, a hybrid methodology which combines the advantages of quantitative and qualitative approaches is used for modeling and resolution of the hyper-redundant robot kinematics. A kinematic controller was designed and a set of experiments was carried out to evaluate the level of efficiency of the proposed approach.

By combining the investigation of the biomechanics and behavior of elephant trunk in the performance of a wide range of dexterous manipulations, a novel approach in the design and kinematics modeling of a fruit harvesting continuum manipulator was proposed. By comparing the structure of two different species of elephant trunk, a new continuum structure which matched the key features of elephant trunk was designed. Based on analysis of the underlying elephant trunk’s grasping mode, a novel kinematics model was proposed. Contrast to traditional robot kinematics which focused on end effector’s position and posture, the proposed continuum manipulator kinematics focus on the center of manipulator’s position and posture, which is more effective when trunk robot realizing grasp and establishes the foundation for its application. Finally, three typical grasping experiments were implemented. The experiment results showed that the manipulator could conduct wrap/pinch manipulations effectively for both small objects and bigger ones. DOI: 10.3965/j.ijabe.20150801.008 Citation: Shao T, Zhang L B, Du M Y, Bao G J, Yang Q H. Fruit harvesting continuum manipulator inspired by elephant trunk. Int J Agric & Biol Eng, 2015; 8(1): 57－63.