This paper proposed an iterative learning control (ILC) scheme for deformable open-frame cable-driven parallel robots (D-CDPRs). In contrast to the straightforward inverse kinematics of the rigid frame cable-driven parallel robots (CDPRs), accurate modeling of the deformable frame poses challenges due to errors and uncertainties. To address these issues, the authors propose the use of ILC, a control strategy that modifies the control input over iterations based on previous results. ILC has been successfully applied to traditional cable robots, particularly in handling model uncertainty. The paper presents a novel ILC control scheme specifically designed for D-CDPRs, with a focus on reducing tracking errors over repetitive operations. Additionally, hardware experiments are conducted to validate the effectiveness and reliability of the proposed ILC approach. The results demonstrate the efficacy of ILC in mitigating tracking errors, even in scenarios where the dynamic model of the D-CDPRs is unknown.

This article proposes a generalized type of cable-driven parallel robot with deformable frames (D-CDPRs). The class of D-CDPRs allows: first, inevitable deformation of traditional rigid frame CDPRs to be considered; and second, new possibilities to develop CDPRs with lightweight frames that would deform. Comparatively, such lightweight CDPRs are easier to set up and largely reduce the cost of material and construction. However, the analysis and control of D-CDPRs are challenging as existing works usually assume the CDPR frame is rigid, such that the cable exit points on the frame are known and fixed. If the modeling errors induced by the deformable frame are not addressed appropriately, the control performance of D-CDPRs will be inaccurate and even unstable. To tackle this problem, novel modeling, analysis, and control approaches are proposed accordingly for D-CDPRs. Using the Euler–Bernoulli beam equations to develop a D-CDPR model, the workspace analysis is proposed and explored. Furthermore, the model-based feedforward length (MBFL) controller is proposed, where it is shown that cable length can be used to execute the tension control for D-CDPRs. Finally, the proposed work is validated in both simulation and hardware experiments.

This paper presents a robotic in-hand manipulation technique that can be applied to pick an object too large to grasp in a prehensile manner, by taking advantage of its contact interactions with a curved, passive end-effector, and two flat support surfaces. First, the object is tilted up while being held between the end-effector and the supports. Then, the end-effector is tucked into the gap underneath the object, which is formed by tilting, in order to obtain a grasp against gravity. In this paper, we first examine the mechanics of tilting to understand the different ways in which the object can be initially tilted. We then present a strategy to tilt up the object in a secure manner. Finally, we demonstrate successful picking of objects of various size and geometry using our technique through a set of experiments performed with a custom-made robotic device and a conventional robot arm. Our experiment results show that object picking can be performed reliably with our method using simple hardware and control, and when possible, with appropriate fixture design.

The wrench feasibility and twist feasibility are the workspace conditions that indicate whether the mobile-platform (MP) of the cable-driven parallel robots (CDPRs) can provide a sufficient amount of wrench and twist. Traditionally, these two quantities are evaluated independently from the actuator's torque and speed limits, which are assumed to be fixed in the literature, but they are, indeed, coupled. This results in a conservative usage of the actuator capability and, hence, hinders the robot's actual feasibility. In this study, new approaches to analyzing and commanding CDPRs by considering the coupling effect are proposed. First, the required wrench of the MP is mapped into the twist space by the motors' torque–speed relationship and becomes the wrench-dependent available twist set. Then, a new workspace condition and a new metric are introduced based on the available twist set. The metric shows the maximum allowable MP speed map of the workspace. Finally, a varying speed trajectory is designed based on the metric to optimize the total MP traveling time. This study shows the potential of robot wrench–twist capability and enhances the robot hardware effectiveness without any hardware changes.

This article proposes a novel method to determine the optimal cable attachment configuration for reconfigurable cable-driven parallel robots (RCDPRs) considering different workspace conditions. It is shown that wrench-feasible, wrench-closure, and interference-free conditions can be formulated into inequality constraints by considering the cable attachment points as polynomial functions or variables. Furthermore, the proposed method determines the optimal cable attachment location that minimizes the cable force or maximizes the tension factor kinematically at each pose. The proposed formulation can be resolved by different optimization techniques, such as semidefinite programming relaxation and multivariable gradient-based optimization solvers. The proposed approach can be implemented on RCDPRs from low to high degrees-of-freedom and a wide range of obstacles. The proposed formulation can be widely applied for different reconfiguration mechanisms, such as rails, UGV, and UAV.

In this paper, a computationally efficient model predictive control (MPC) is proposed for the trajectory tracking of cable-driven robots subject to state/input constraints. While MPC has been an effective tool in dealing with various constraints, the primary drawback is the high computational load caused by the non-convexity of the corresponding optimization problem. In order to avoid the non-convexity, the prediction model in the proposed reference acceleration MPC (RA-MPC) is simplified into a linear one by assuming the reference accelerations being taken in the future horizon steps. As a result, RA-MPC only optimizes for the instantaneous joint accelerations and the corresponding actuator commands for the current step, resulting in a convex quadratic program that can be efficiently solved. It is further shown that by properly selecting parameters, RA-MPC can be interpreted as ‘soft-CTC’ and ‘soft-LQR’, where the joint acceleration is allowed to deviate from the corresponding desired value, computed from a PD gain or an LQR gain. The effectiveness of the proposed RA-MPC are demonstrated in both simulation and hardware experiment using cable-driven robots.

The control of cable-driven robots is challenging due to the system’s nonlinearity, actuation redundancy, and the unilaterally bounded actuation constraints. To solve this problem, a workspace-based model predictive control (W-MPC) scheme is proposed, which combines the online model predictive control with offline workspace analysis. Using the workspace, a set of convex constraints can be generated for a given reference trajectory. This can then be used to formulate a convex optimization problem for the online W-MPC. Meanwhile, strict recursive feasibility and stability are obtained by taking advantage of the predictive feature of MPC. To demonstrate the effectiveness of the proposed W-MPC, simulation was performed on a 2-link planar cable-driven robot and a spatial cable-driven parallel robot for both nominal and non-nominal scenarios. Hardware experiment was also carried out using a 3 degree-of-freedom planar cable robot. The results show that the controller is efficient and effective to perform motion tracking with the cable force constraints satisfied despite the existence of various model uncertainties.

This paper presents a new generalized ray-based approach to the generation and representation of the wrench-closure workspace (WCW) for cable-driven robots (CDRs). Existing WCW studies have yet to address two significant problems, first is the lack of a generalized approach to generate the WCW with continuity information for all degrees-of-freedom (DoFs) and arbitrary CDRs, and second is a workspace representation for higher DoF robots. The proposed work addresses these issues using a generalized ray-based lattice WCW generation approach that can be applied in all DoFs. Furthermore, a new graph workspace representation is introduced with a range of advantages in the way CDR workspace can be visualized and studied. Such a representation is powerful since it: can be used for any other type of workspace beyond the WCW; can be visualized in two-dimensions regardless of the number of DoFs of the system; allows metric information to be included; and opens up the use of well-established graph theory techniques to study the workspace. Through three different CDR examples, a 3-DoF planar cable-driven parallel robot (CDPR), a 4-DoF multilink robot, and a 6-DoF CDPR, the characteristics and advantages of the proposed method are highlighted.

The study of cable-driven parallel robots (CDPRs) has attracted much attention in recent years. However, to the best of the authors' knowledge, no single software platform exists for researchers to perform different types of analyses for CDPRs of arbitrary structure. In this paper, the Cable-robot Analysis and Simulation Platform for Research (CASPR) of CDPRs is introduced. Using this platform, arbitrary types and structures of CDPRs, such as single and multi-link CDPRs, can be studied for a wide range of analyses, including kinematics, dynamics, control and workspace analysis. CASPR achieves this using a general CDPR model representation and an abstracted software architecture. Moveover, CDPRs can be defined using Extensible Markup Language (XML) with out-of-the-box availability of an extensive range of robots and analysis tools. The open-source platform aims to provide both a communal environment for the researchers to use and add models and algorithms to. The example case studies demonstrate the potential to perform analysis on CDPRs, directly compare algorithms and conveniently add new models and analyses.

Fluid motion planners are a type of artificial potential field (APF) motion planners that use the differential equations of fluid flow to determine the desired trajectory. The fluid flow approach in motion planning can efficiently produce natural-looking trajectories. However, the differential equations used in previous studies are restricted to motion planning in 2-D environments. In this paper, the fluid flow approach is extended to a motion planning framework for 3-D mobile robots that avoids spheroidal obstacles. Compared with existing APF approaches, kinematic constraints in both speed and curvature are also considered. Possessing the efficiency of 2-D fluid motion planners, the proposed approach is able to plan natural-looking reference trajectories for nonholonomic 3-D mobile robots. The approach is demonstrated through various 3-D example scenarios. The work can be considered as a fundamental framework for 3-D fluid motion planning, where additional kinematic constraints and more complex scenarios can be incorporated.

Joint interaction forces and moments play a significant role within multilink cable-driven manipulators (MCDMs). In this paper, the consideration of joint interaction forces and moments in the objective function and constraints specific to the inverse dynamics of MCDMs are considered for the first time. By formulating the relationship between the joint interactions and cable forces, it is shown that the minimization of the joint interactions results in a convex quadratic program. Furthermore, the inclusion of constraints to maintain the stability of unilateral spherical joints results in a quadratically constrained quadratic program. Simulation results of the proposed formulations on two-link eight-cable and eight-link 76-cable manipulators are compared with the traditional two-norm cable force minimization. Results show that the formulations are able to take advantage of the actuation redundancy in considering the joint interactions within the inverse dynamics of MCDMs.

Multilink cable-driven manipulators offer the compactness of serial mechanisms while benefitting from the advantages of cable-actuated systems. One major challenge in modeling multilink cable-driven manipulators is that the number of combinations in the possible cable-routing increases exponentially with the number of rigid bodies. In this paper, a generalized model for multilink cable-driven serial manipulators with an arbitrary number of links that allow for arbitrary cable routing is presented. Introducing the cable-routing matrix (CRM), it is shown that all possible cable routing can be encapsulated into a single representation. The kinematics and dynamics for the generalized model are derived with respect to the CRM. The advantages of the proposed representation include the simplicity and convenience in modeling and analysis, where all cable routing is inherently considered in a single model. To illustrate this, the inverse dynamics analysis is performed for two example systems: a 2-link 4-DoF manipulator that is actuated by 6 cables and an 8-link 24-DoF mechanism actuated by 76 cables. The results show the validity and scalability of the generalized formulation, allowing for complex systems with arbitrary cable routing to be modeled and analyzed.