Cable-Driven Parallel Robots (CDPRs) have shown significant potential in industrial applications due to their large workspace, high payload capacity, and flexibility. Nonetheless, ensuring safe and efficient human-robot collaboration, particularly during carrying tasks, remains an open problem. This paper primarily contributes a cable tension–based metric for detecting contact events, combined with a frequency-domain analysis of estimated external wrenches to distinguish different contact scenarios. Building upon this framework, three common contact scenarios are then addressed: (i) payload placement and removal without rigid attachment to the moving-platform (SC1), (ii) unintentional human-cable collisions (SC2), and (iii) human-platform collisions (SC3). Specific management strategies are then proposed, including real-time mass estimation for payload handling, cable tension release for human-cable collisions, and a compliant trajectory controller for human-platform collisions. Experimental validations on a CDPR prototype demonstrate accurate scenario classification and safe contact handling without compromising overall productivity. By facilitating safer interactions, improved adaptability, and reliable handling of diverse contact events, this work expands the applicability of collaborative CDPRs in real-world industrial and logistic settings.

This work introduces PERCEPT-PIETON, a project aiming to understand through the use of virtual reality and inertial motion capture, perceptual-motor and cognitive mechanisms involved during driver-pedestrian interactions from the driver’s point of view. We are be particularly interested in how drivers regulate their behaviour and predict pedestrian’s intentions based on individual (age, gender,...) and behavioural (walking speed, trajectory,...) characteristics of the latter. The objective is threefold : (i) a theoretical scientific contribution to obstacle avoidance literature; (ii) applied scientific knowledge for public decision-makers; and (iii) the creation of a free access library of biological pedestrians movements.

Cable elasticity can significantly impact the accuracy of Cable-Driven Parallel Robots (CDPRs). However, it’s frequently disregarded as negligible in CDPR simulations and designs. In this paper, we propose a numerical approach, referred to as SEECR, which is designed to estimate the behavior of a CDPR featuring elastic cables while ensuring the Static Equilibrium (SE) of the Moving-Platform (MP). By modeling the cables as elastic springs, the proposed approach correctly predicts which cables become slack, estimates the tension distribution among cables and computes unwanted MP motions, allowing to predict the impact of design choices. The results have been validated experimentally on two cable types and configurations.

Some cable-driven parallel robots (CDPRs) can be rapidly deployed on-site. To achieve such deployability, the fixed frame is usually substituted by four masts. However, not having any rigid fixture between the masts reduces the overall stiffness of the CDPR. This paper introduces a CDPR called Rocaspect, that has four compliant masts. The robot behavior and accuracy is evaluated experimentally and three different mast models are proposed.

Cable-Driven Parallel Robots (CDPRs) are well-adapted to large workspaces since they replace rigid links by cables. However, they lack in positioning accuracy and new control methods are necessary to achieve profile-following tasks. This paper presents a control scheme designed for these tasks, relying on a combination of accurate boarded distance sensors and of a less accurate remote camera. The profile-following task is divided into two subtasks that are partially conflicting: maintaining a parallel orientation and a constant distance with the surface to follow, and following a trajectory between two points on the surface. The data fusion to solve the redundancy is based on the Gradient Projection Method. This control scheme is validated experimentally on a CDPR prototype and shown to provide the expected behaviour.

Motion planning for Cable-Driven Parallel Robots (CDPRs) is a challenging task due to various restrictions on cable tensions, collisions and obstacle avoidance. The presented work aims at proposing an optimal path planning strategy in order to both maximize the wrench capability and the dexterity of the robot in a cluttered environment. First, an asymptoticallyoptimal path finding method based on a variant of rapidly exploring random trees (RRT) is implemented along with the GilbertJohnsonKeerthi (GJK) algorithm to account for the collision detections. Then, a goal biased Artificial Field Guide (AFG) is employed to reduce convergence time and ensure directional exploration. Finally, a post-processing algorithm is added to get a short and smooth resultant path by fitting appropriate splines. The proposed path planning strategy is analyzed and demonstrated on a simulated and experimental setup of a six-DOF spatial CDPR.

Cable-driven parallel robots (CDPRs) are a type of parallel robots, where cables are used instead of rigid links. This leads to many advantages, such as large workspace, low mass in motion and simple reconfiguration. The drawbacks are accuracy issues and complex cable management. Indeed, it is usual that cables become slack. That can be caused by, for example, cable mass, uncertainties in the system, and a higher number of cables than the number of degrees of freedom of the moving-platform. This reduces CDPR stiffness and degree of actuation. While visual servoing provides good accuracy and is robust to different perturbations in the system and to modeling errors, it does not deal with cable slackness. Thus, a CDPR with visual servoing can become underactuated due to cable slack. We propose in this paper to enrich visual servoing with a tension correction algorithm. Experimental results show reduction of slackness and thus avoiding slackness-related trajectory perturbations and loss of stability.

Cable-Driven Parallel Robots (CDPRs) are parallel robots with rigid links replaced by cables. As for most parallel robots the determination of the analytical solutions to the direct geometrico-static model (DGSM) is a difficult task that is often not feasible online. However, the knowledge of the moving-platform (MP) pose is necessary in order to control the CDPR, e.g. with visual servoing. When the MP pose measurement is not available, an estimation can be sufficient. This paper compares three estimation methods: (a) control-based; (b) image-based; and (c) model-based. The three methods are implemented experimentally with an open-loop velocity controller and a closed-loop visual servoing controller. Overall, very good results are shown with model-based and control-based methods for both controllers. Finally, it is shown that the visual servoing controller leads to a better accuracy of the robot than the velocity controller.

This paper investigates the effect of the robot configuration on the performance of an aerial cable towed system (ACTS) composed of three quadrotors manipulating a point mass payload. The kinematic and dynamic models of the ACTS are derived in a minimal set of geometric coordinates, and a centralized feedback linearization controller is developed. Independent to the payload trajectory, the configuration of the ACTS is controlled and is evaluated using a robustness index named the capacity margin. Experiments are performed with optimal, suboptimal, and wrench infeasible configurations. It is shown that configurations near the point of zero capacity margin allow the ACTS to hover but not to follow dynamic trajectories, and that the ACTS cannot fly with a negative capacity margin. Dynamic tests of the ACTS show the effects of the configuration on the achievable accelerations.

A Mobile Cable-Driven Parallel Robot (MCDPR) is composed of a classical Cable-Driven Parallel Robot (CDPR) carried by multiple mobile bases. The additional mobilities due the motion of the mobile bases allow such systems to autonomously modify their geometric architecture, and thus make them suitable for multiple manipulation tasks in constrained environments. Moreover, these additional mobilities mean MCDPRs are kinematically redundant and may use this redundancy to optimize secondary task criteria. However, the high dimensional state space and closed chain constraints add complexity to the motion planning problem. To overcome this, we propose a method for trajectory planning for MCDPRs performing pick and place operations in cluttered environments by using direct transcription optimization. Two different scenarios have been considered and their results are validated using a dynamic simulation software (V-REP) and experimentally.

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Cable-Driven Parallel Robots (CDPRs) have several advantages over conventional parallel manipulators most notably a large workspace. CDPRs whose workspace can be further increased by modification of the geometric architecture are known as Reconfigurable Cable Driven Parallel Robots(RCDPRs). A novel concept of RCDPRs, known as Mobile CDPR (MCDPR) that consists of a CDPR carried by multiple mobile bases, is studied in this paper. The system is capable of autonomously navigating to a desired location then deploying to a standard CDPR. In this paper, we analyze the Static equilibrium (SE) of the mobile bases when the system is fully deployed. In contrast to classical CDPRs we show that the workspace of the MCDPR depends, not only on the tension limits, but on the SE constraints as well. We demonstrate how to construct the Available Wrench Set (AWS) for a planar MCDPR wih a point-mass end-effector using both the convex hull and Hyperplane shifting methods. The obtained results are validated in simulation and on an experimental platform consisting of two mobile bases and a CDPR with four cables.

The subject of this paper is about the use of a suspended Cable-Driven Parallel Robot (CDPR) for pick-and-place operations of heavy and heterogeneous objects. The knowledge of the payload mass and its center of mass in realtime is an asset for robust control of the device, which is required to ensure a good stability, especially when the objects have different shapes, sizes and masses. Accordingly, this paper aims at experimentally evaluating the effects of (i) the pulleys modeling and (ii) the use of force sensors for the payload estimation. It turns out that the consideration of the pulleys into the geometric model of the robot improves the mass and center of mass estimations of the payload. A comparison is made between the estimation of cable tensions from force sensors and from motor currents. Finally, a torque controller with a feedforward term for real-time mass compensation is proposed and implemented on a CDPR prototype.

There have been several research works on reconfigurable parallel manipulators in the last few years. Some robots are reconfigurable in the sense that the position of the anchor points on the moving platform or the actuated joints can be changed. Some problems may arise when one intends to make a prototype and develop its control scheme. A reconfigurable planar parallel robot, named NaVARo, is a 3-DOF planar parallel manipulator with eight actuation modes. The subject of this paper is about a control scheme of NaVARo while taking advantage of multiple sensors such as motor encoders, additional absolute encoders and magnetic sensors used to determine the current assembly mode of the manipulator. Finally, a methodology is presented to determine the home configuration of NaVARo.

This paper deals with Reconfigurable Cable-Driven Parallel Robots (RCDPRs). A RCDPR is able to change the locations of its cable exit points, the latter being defined as the connection points between the cables and the robot base frame. Given a RCDPR, a set of possible reconfigurations, a desired platform path and a description of the robot environment, the reconfiguration strategy proposed in this paper selects the optimal configurations to be associated to each point of the desired path. The selection of the optimal configurations can be performed with respect to several criteria such as the number of configuration changes, the number of cable reconfigurations and the robot stiffness. In this paper, the optimization is performed using a Dijkstra's based algorithm.

The paper addresses a problem of robotic manipulator calibration. The main contributions are in the area of the elastostatic parameters identification. In contrast to other works, the considered approach takes into account elastic properties of both links and joint. Particular attention is paid to generation of the complete and irreducible stiffness model that is suitable for the identification. To solve the problem, physical and algebraic model reduction methods are proposed. They are based on taking into account the physical properties of the manipulator elements and structure of the corresponding observation matrix. The advantages of the developed approach are illustrated by an application example that deals with elastostatic calibration of an industrial robot.

This paper presents a methodology to analyze the assembly conditions of parallel manipulators and compute the maximum pose errors of their moving platform, while considering geometric errors, joint clearances, link flexibility and joint elasticity. First, the proposed methodology consists in determining the zone(s) of the manipulator workspace in which the manipulator can be assembled assuming that its links and joints are rigid, while taking into account geometric errors and joint clearances. Then, the minimum energy required to assemble the manipulator in the non-assembly zone(s) is computed, while considering link flexibility and joint elasticity. The maximum pose errors of the moving-platform are also computed throughout the manipulator workspace. Finally, a two-dof spatial parallel manipulator, named IRSbot-2, is used as an illustrative example.

This paper presents the preliminary studies dedicated to the design of cable-driven parallel robots (CDPRs) for industrial purposes. The goal is to transport the proper tools around a jacket, an offshore structure supporting a wind turbine, in order to perform painting and sandblasting tasks. In this paper, a simplified case study consisting of a structure composed of four tubes is investigated. A fully constrained CDPR and a suspended CDPR are studied. The design problems of the CDPRs at hand are formulated as optimization problems. They aim at determining the locations of the base anchor points of the cables that minimize the size of the CDPR, while satisfying a set of constraints. Those constraints guarantee that the moving platform can support the external wrenches and that there is no interference between the cables and between the cables and the environment, all along the path to be followed by the moving platform.

Roboticists are faced with new challenges in robotic-based manufacturing. Up to now manufacturing operations that require both high stiffness and accuracy have been mainly realized with computer numerical control machine tools. This paper aims to show that manufacturing finishing tasks can be performed with robotic cells knowing the process cutting conditions and the robot stiffness throughout its Cartesian workspace. It makes sense that the finishing task of large parts should be cheaper with robots. However, machining robots have not been adapted for such operations yet. As a consequence, this paper introduces a methodology that aims to determine the best placement of the workpiece to be machined knowing the elastostatic model of the robot and the cutting forces exerted on the tool. Therefore, a machining quality criterion is proposed and an optimization problem is formulated and solved. The KUKA KR270-2 robot is used as an illustrative example throughout the paper.

The paper focuses on the stiffness modeling of heavy industrial robots with gravity compensators. The main attention is paid to the identification of geometrical and elastostatic parameters and calibration accuracy. To reduce impact of the measurement errors, the set of manipulator configurations for calibration experiments is optimized with respect to the proposed performance measure related to the end-effector position accuracy. Experimental results are presented that illustrate the advantages of the developed technique.

This paper focuses on stiffness matrix computation for manipulators with passive joints, compliant actuators, and flexible links. It proposes both explicit analytical expressions and an efficient recursive procedure that are applicable in the general case and allow us to obtain the desired matrix either in analytical or numerical form. Advantages of the developed technique and its ability to produce both singular and nonsingular stiffness matrices are illustrated by application examples that deal with stiffness modeling of two Stewart-Gough platforms.

The paper focuses on stiffness matrix computation for manipulators with passive joints. It proposes both explicit analytical expressions and an efficient recursive procedure that are applicable in general case and allow obtaining the desired matrix either in analytical or numerical form. Advantages of the developed technique and its ability to produce both singular and non-singular stiffness matrices are illustrated by application examples that deal with stiffness modeling of two Stewart-Gough platforms.

In this paper, 3-PPR planar parallel manipulators with D- or U-shape base are compared with respect to their workspace size and kinematic sensitivity to joint clearances. First, the singularities and workspace of a general 3-PPR planar parallel manipulator are analyzed. Then, an error prediction model applicable to both serial and parallel manipulators is developed. As a result, two nonconvex quadratically constrained quadratic programs are formulated in order to find the maximum reference-point position error and the maximum orientation error of the moving-platform for given joint clearances. Finally, the contributions of the paper are highlighted by means of a comparative study of two manipulators.

This paper presents a new methodology for joint stiffness identification of serial robots. This methodology aims at evaluating all joint stiffness values responsible for both translational and rotational displacements of the robot end-effector subject to an external wrench (force and torque). The links of the robot are supposed to be quite stiffer than the joints and not known as it is usually the case with industrial serial robots. The robustness of the identification method and the sensitivity of the results to measurement errors and number of experimental tests are also analyzed. The Kuka KR240-2 robot is used as an illustrative example through the paper.

This paper introduces a methodology to analyze geometrically the singularities of manipulators, of which legs apply both actuation forces and constraint moments to their moving platform. Lower mobility parallel manipulators and parallel manipulators, of which some legs have no spherical joint, are such manipulators. The geometric conditions associated with the dependency of six PlUumlcker vectors of finite lines or lines at infinity constituting the rows of the inverse Jacobian matrix are formulated using Grassmann-Cayley algebra (GCA). Accordingly, the singularity conditions are obtained in vector form. This study is illustrated with the singularity analysis of four manipulators.