Large Workspace Research Articles

Motion Planning and Cooperative Manipulation for Mobile Robots With Dual Arms

With large work space and dexterous manipulation capability, mobile robots with dual arms can be used in complex operation scenes such as active detection, disassembly, spraying, cleaning and assembly, is a promising direction for robot development. In this paper, a hybrid control approach is proposed for a mobile robot with dual arms to fulfil an explosive disposal task. Firstly, the motion planning for mobile base and trajectory planning for dual arms are developed, and a hierarchical task planner is designed using the finite state machine to make the robot system to deal with events sensed by active vision. A rapidly-exploring random tree-based motion planning is developed in task space for the mobile base to realize dynamic collision avoidance, while the trajectory planning approach is proposed in the framework of a dual-arm master-slave coordinated mechanism. Next, for mobile robots to complete complex task such as explosive disposal using two dexterous hands, the impedance control approach with slippage detection is developed by considering slippage tendency and slippage intensity to produce a stable in-hand manipulation. Furthermore, the Faster R-CNN is employed to determine the grasping region for robot manipulation through object detection and learning. Finally, the explosive disposal scene is designed to justify the effectiveness and good performance of the proposed methods.

A jerk-limited heuristic feedrate scheduling method based on particle swarm optimization for a 5-DOF hybrid robot

Compared with machine tools, five degrees-of-freedom (DOFs) hybrid robots have been widely concerned in the manufacturing of large complex surface parts due to their characteristics of high flexibility and large workspace. It is of great significance to schedule the time-optimal feedrate that satisfies the high-order constraints (e.g., jerk or jounce) in the toolpath and joint systems to achieve the high-precision and high-efficiency machining of the robot. To overcome the complexity of five-axis feedrate scheduling and improve the optimality of machining time, this paper proposes a jerk-limited heuristic feedrate scheduling (HFS) method with near-optimal time. Firstly, the analytical equations between all constraints and the parametric feedrate are derived, and the mathematical model for control points optimization of the parametric feedrate profile expressed by a B-spline curve is established. Then, combined with the global search particle swarm optimization (GSPSO) algorithm, a proposed moving window planning method optimizes a small number of control points so that the feedrate curve has enough rising space. Subsequently, to obtain the near time-optimal feedrate, the local search PSO (LSPSO) algorithm within the moving window is developed to locally adjust the non-uniformly inserted control points. Compared with the existing methods, the HFS method is beneficial to further optimize the machining time with a faster computation speed, and ensure the stability of the robot machining. Finally, simulations and experiments on the developed TriMule-800 hybrid robot verify the effectiveness of this method.

A nullspace-based force correction method to improve the dynamic performance of cable-driven parallel robots

Cable-driven parallel robots distinguish themselves from other robot types through their large workspace and high dynamic capabilities. Investigations show that with purely kinematic control schemes, the theoretical workspace of such robots cannot be fully realized in practice. Current control methods usually rely on complex models whose parameters are difficult to determine with the required precision or feedback from expensive sensors that can measure the actual platform pose. This work presents a force control method that enables high dynamic capabilities within a large workspace for redundantly-constrained cable-driven parallel robots in practice, without the aforementioned drawbacks. The new method modifies the cable forces within the nullspace of the robot’s structure matrix to keep them within their feasible limits and as close as possible to a desired level without changing the platform’s pose. In simulation, it achieves similar performance as a state-of-the-art model predictive control method, with 79% less computational effort. Experiments show that it can quickly reject disturbances and is significantly better at keeping the cable forces within their limits on highly dynamic trajectories than a purely kinematic control scheme.

A Suspended Cable-Driven Parallel Robot With Articulated Reconfigurable Moving Platform for Schönflies Motions

Cable-driven parallel robots (CDPRs) can provide large translational workspace with high payload, but their rotational capability is generally limited due to the inherent design. Additionally, among the existing topology structures of CDPRs, few lower mobility CDPRs with subspatial motions are reported till now. Aiming to narrow the abovementioned research gaps, this article presents a novel suspended CDPR with an articulated reconfigurable moving platform to generate Schönflies motions and enhance the rotational capability. The proposed robot uses four pairs of parallel cables to constrain the redundant motions. The moving platform consists of one end-effector gripper and two subplatforms, which are articulated through revolute joints. A gearbox is embedded in the moving platform to amplify the rotational motion about the vertical axis. For the proposed robot, the kinematic and static modeling is given in detail. The multiobjective optimal design is conducted to determine the dimensional parameters. The reconfiguration of the moving platform is formulated as an optimization problem and demonstrated through a case study. The interference-free static workspace is determined through a numerical approach. A prototype of the proposed robot is fabricated, and experimental tests are performed to evaluate the feasibility of the proposed robot.

Development of an Untethered Adaptive Thumb Exoskeleton for Delicate Rehabilitation Assistance

Robot-assisted thumb rehabilitation can improve the hand function of stroke patients because the thumb accounts for 40% of hand function. However, existing thumb rehabilitation robots are limited in terms of portability, comfort, adaptability, and independent joint actuation. This article proposes an untethered adaptive thumb exoskeleton that actively assists the 3-degree-of-freedom movements of the thumb. The exoskeleton is composed of an adaptive thumb mechanism and a spherical mechanism. The kinematics, statics, and performances of the adaptive thumb mechanism and the spherical mechanism are analyzed. Experimental validation is performed to test the workspace, self-alignment, interaction forces, admittance controller, and grasping assistance performance of the exoskeleton. The workspace and self-aligning experiments prove that the proposed exoskeleton can achieve a large workspace of the thumb joints and realize self-alignment. The interaction force experimental results show that the exoskeleton can reduce the tangential interaction forces by 76.8% and improve comfort. Finally, the control and delicate grasping assistance experiments validate the exoskeleton’s ability to realize the delicate grasping of the thumb. These characteristics show that the thumb exoskeleton has the potential to assist delicate thumb rehabilitation.

Automated Manipulation of Microswarms Without Real-Time Image Feedback Using Magnetic Tweezers

Microswarms assembled by microparticles have shown promising prospects in targeted delivery. However, the automated manipulation of microswarms remains a considerable challenge due to the limitations of existing <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in vivo</i> imaging technology. In this article, we design a magnetic tweezer system with a large workspace of 100 mm × 100 mm × 30 mm, which can assemble, transport, and disassemble microswarms efficiently. The magnetic tweezers generate rotating magnetic fields in the workspace, enabling magnetized microparticles to roll toward a specific point along spiral trajectories. The assembly process and mechanism of microswarms are analyzed. The developed system can assemble low-density magnetic microparticles to form a stable and compact microswarm at a predetermined position. Actuation of the magnetic tweezers allows precise navigation of the swarm without relying on real-time image feedback. The experimental results show that the flexible microswarm can achieve satisfactory motion performance and transmission efficiency. The microswarm can successfully move on a slope with an inclination angle of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$40^\circ $</tex-math></inline-formula> and navigate analog channels. The overall delivery efficiency can reach 92%.

A Novel Cable-Driven Parallel Robot With Movable Anchor Points Capable for Obstacle Environments

Cable-driven parallel robots (CDPRs) have the characteristics of large workspace and fast response speed, which attracted lots of interests in the past decade. Most of the CDPRs use flexible cables to manipulate the moving platform while the length of cables is changed by the winches fixed on the base. Consequently, interferences among the driving cables, the moving platform, and the environment become inevitable problems, which significantly limit the effective workspace of CDPRs and its performance in complex multiobstacle environment. This article proposes a novel CDPR with movable anchor points (M-CDPR). The movable anchor point of each driving cable can move along the track on the fixed frames. Besides, we establish the kinematics and dynamics of the M-CDPR, and propose the collision detection method and the obstacle avoidance algorithm. Simulation analyzes indicate that the wrench-feasible workspace of the M-CDPR increases 456.06% compared with traditional CDPRs in the same dimension. Moreover, the M-CDPR can realize obstacle avoidance without changing the desired trajectory under different conditions when there exist multiple static obstacles, or both moving and static obstacles. In addition, a prototype is fabricated, consisting of eight driving cables and eight movable anchor points. Experimental results show that the proposed M-CDPR performed well in an environment containing a number of static and/or moving obstacles without any interference.

Workspace Mapping Method Based on Edge Drifting for the Teleoperation System

The workspace mapping method for master-slave isomeric robots is a key research direction. In order to enhance the safety and stability of the operation of such robots, a position-joint hybrid mapping method based on edge drifting is proposed in this paper. First, teleoperation is divided into two phases, that is, task approach and task operation. During the task approach, the edge drifting algorithm is adopted to largely cover the workspace of a robot. Rate mapping is used to quickly control the movement of the slave robot to the target position. During task operation, a hybrid mapping algorithm integrating the Cartesian space and the joint space highly precisely maps both the position and pose of the slave robot to accurately follow the control command of the master end and achieve precise control. Lastly, the proposed method is validated on the experimental platform for master-slave isomeric teleoperation. The experimental results indicate that this mapping method allows the master-slave isomeric teleoperation system to cover a large workspace precisely with desirable precision in position and pose following.

Design and Gesture Optimization of a Soft-Rigid Robotic Hand for Adaptive Grasping.

Soft robotic hands are inherently safer and more compliant in robot-environment interaction than rigid manipulators, but their flexibility and versatility still need improving. In this article, a gesture adaptive soft-rigid robotic hand is proposed. The robotic hand has three pneumatic two-segment fingers. Each finger segment is driven independently for flexible gesture adjustment to match up with different object shapes. The palm is constructed by a rigid skeleton driven by a soft pneumatic spring. It provides a firm support, large workspace, and independent force control for the fingers. Geometry model of the robotic hand is established, based on which a grasping gesture optimization algorithm is adopted. The fingers achieve optimal contact with objects by performing maximal curving similarity with the object outlines. Experiment shows that the soft-rigid robotic hand provides adaptive and reliable grasping for objects of different sizes, shapes, and materials with optimized gestures.

Lightweight Multipurpose Three-Arm Aerial Manipulator Systems for UAV Adaptive Leveling after Landing and Overhead Docking

In aerial manipulation, the position and size of a manipulator attached to an aerial robot defines its workspace relative to the robot. However, the working region of a multipurpose robot is determined by its task and is not always predictable prior to deployment. In this paper, the development of a multipurpose manipulator design for a three-armed UAV with a large workspace around its airframe is proposed. The manipulator is designed to be lightweight and slim in order to not disrupt the UAV during in-flight manipulator movements. In the experiments, we demonstrate various advanced and critical tasks required of an aerial robot when deployed in a remote environment, focusing on the landing and docking tasks, which is accomplished using a single manipulator system.

Orientation Workspace Analysis and Parameter Optimization of 3-RRPS Parallel Robot for Pelvic Fracture Reduction

Abstract For parallel robots with general configuration, it is difficult to achieve the large rotation range requirement for pelvic fracture reduction. Application-based workspace optimization is important. In this paper, a 3-revolute-revolute-prismatic-spherical (3-RRPS) parallel robot with optimized parameters is studied, which can offer a large orientation workspace and relatively compact configuration. The inverse kinematics of the robot is analyzed by the closed-loop vector method. The cylindrical coordinate searching algorithm and boundary extraction method are adopted to calculate the orientation workspace. Defining the comprehensive branch length (CBL) to express robot’s compactness under the premise of satisfying the required orientation workspace. The genetic algorithm (GA) is adopted to optimize structural parameters of the robot with CBL as the objective function. The optimization results show that when the orientation angles of the moving platform are limited to not less than 28 deg, the CBL of the robot is 291 mm. Finally, the virtual prototype simulation verification shows that the orientation angles of the moving platform around x-axis and y-axis can reach ±28 deg, the orientation angle around z-axis can reach ±40 deg, which meets the requirements of the rotational range for pelvic fracture reduction surgery.

Piezoelectric hybrid actuation mode to improve speeds in cross-scale micromanipulations

Piezoelectric precision actuators are powerful tools used to explore and reform the microworld. A large number of achievements have emerged to promote their progress. However, most of them only focus on high accuracies and large workspaces, but ignore the roles of fast speeds for high working efficiencies and wide application fields. Inspired by the wobbling and jumping gaits of the cricket, a hybrid actuation mode for piezoelectric actuators is proposed to improve speeds in cross-scale micromanipulations. After solving three key problems of physical design, operation method and control strategy, this idea is verified with FEM simulations and theoretical models. The experiments indicate that the hybrid mode increases the speed by about 300% over the conventional walking mode, and the maximum speed reaches about 3.9 mm/s (0.16 rad/s). Furthermore, the resolution is as high as 3.8 nm (0.14 μrad), and the RMS positioning error is smaller than 34.2 nm in a stroke of 1 mm. With unlimited stroke, fast speed and high precision, the hybrid mode is very suitable for the accurate quick positioning in a large range. The experiment also demonstrates great potential applications in micro-nano assemblies. To sum up, the hybrid mode significantly improves the speeds of piezoelectric actuators under the premises of high accuracies and large workspaces. Besides, this mode is a universal approach, which can be easily applied on other actuators to improve speeds, so it is helpful to expand applications of piezoelectric precision actuators.

Simulation-Based Comparison of Novel Automated Construction Systems

As automated construction processes require large workspaces and high payloads, the use of cables is a reasonable approach to span wide distances and share loads. Therefore, a cable-driven parallel robot is a suitable choice for automated masonry construction. Another possible robotic system for this task consists of a set of cooperative drones, each connected to the end effector and the payload by a cable. Because of the similarities between the two robotic systems, the same object-oriented programmed software can be used for trajectory planning and subsequent investigations, making minor adjustments. The implemented optimizing path planning algorithm takes into account the physical boundaries, motion time, collision avoidance and energy requirements. Thus, a simulation-based comparison of the characteristics of both systems can be made. In this paper, the necessary physical models for both the drone system and the cable robot are derived in detail. Based on the common framework, this paper presents a comparison between the two robotic systems, defining two different scenarios. The first scenario demonstrates the functioning of the optimizer approach. The second scenario is used to compare the two systems. For this purpose, the trajectories for all 1720 masonry units of the first floor of a house are optimized. The analysis of the results shows that both systems can transport heavy loads, with the cable robot having advantages on smaller sites, while the drone system covers larger distances for the price of slower performance and higher energy consumption.

Redundant Posture Optimization for 6R Robotic Milling Based on Piecewise-Global-Optimization-Strategy Considering Stiffness, Singularity and Joint-Limit

Robotic machining has obtained growing attention recently because of the low cost, high flexibility and large workspace of industrial robots (IRs). Multiple degrees of freedom of IRs improve the dexterity of machining while causing the problem of redundancy. Meanwhile, the performance of IRs, such as their stiffness and dexterity, is affected by their position and posture obviously. Therefore, a redundant posture optimization method for robotic milling is proposed to improve the machining performance of the robot. The multiple characteristics of the robot are considered, including the joint-limit, singularity and stiffness, which have symmetry in its workspace. Firstly, the joint-limit is regarded as the constraint. And a symmetrical and effective constraint method is proposed to simply guarantee that all the interpolation points can avoid joint interference. Then, the performance indices of singularity and stiffness are designed as the optimization target. On this basis, the piecewise-global-optimization-strategy (PGOS) is proposed for redundant optimization. Owning to the PGOS, all the given planned tool points in their corresponding segment are considered simultaneously to avoid the gradual deterioration in traditional methods, which is especially suitable for the machining process with a continuous path. Moreover, the computational load of the optimization solution is considered and limited by the designed segmentation strategy. Finally, a series of comparative simulations are conducted to validate the good performance of the proposed method.

Adaptive Simultaneous Magnetic Actuation and Localization for WCE in a Tubular Environment

Simultaneous magnetic actuation and localization is a promising technology to realize active wireless capsule endoscopy. In this article, an adaptive approach is proposed to efficiently propel and precisely locate a magnetically actuated capsule in unknown complex tubular environments. In order to track the capsule in real time in a large workspace, we improve upon our previous external sensor-based magnetic localization strategies by proposing an adaptive method to automatically activate an optimal subset of sensors during the capsule movement and developing a simplified multiple objects tracking algorithm to estimate the six-dimensional pose of the capsule in real time. Moreover, based on a study of capsule locomotion in tubular environments with different shapes, we propose to dynamically adjust the pose of the actuator to achieve efficient and robust propulsion of the capsule in an unknown tubular environment. The effectiveness of our proposed system is validated in extensive experiments on phantoms and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ex vivo</i> animal organs. Compared with the state-of-the-art, our method can realize the closed-loop control of a magnetic capsule without requiring sensing modules to be placed inside the capsule, which can reduce the space constraints and energy consumption of the capsule. Moreover, the system and algorithms for adaptive actuation and localization can provide an improved propulsion speed, workspace range, and localization update frequency as well as a comparable localization accuracy.

Design and Experimental Characterization of a Push-Pull Flexible Rod-Driven Soft-Bodied Robot

Soft robots with a well-balanced performance in terms of dexterity, accuracy, and payload have a great potential for application. Balancing safe human-robot interaction with operation performance enables the use of soft robot in biomedical fields, among others, such as surgery, rehabilitation and elder care. In this letter, we present a rod-driven soft robot (RDSR) where the flexible rods embedded in the silicone-based body provide a double push-pull actuation, to satisfy the needs of balanced performance. The RDSR can realize multi DOFs movement with elongation, contraction and bending. For trajectory tracking, Gaussian process model enables RDSR to achieve more accurate motion control with an RMSE within 2.8 mm compared to the constant curvature model with that within 10.8 mm. Comparative experiments demonstrate that the workspace, vertical and lateral stiffness of the RDSR are up to 5, 2.6 and 5.2 times that of an analogous tendon-driven soft robot (TDSR), respectively. Additionally, the RDSR possesses the ability, that the TDSR does not have, to actively apply pushing perpendicular to an inclined plane. Based on numerical Jacobian matrix, the maximum force along target direction is greater than 4 N for a 30 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^\circ$</tex-math></inline-formula> plane. Furthermore, pick-and-place tests validate that our soft robot, with large workspace, precise and steady motion, is capable of conducting object manipulation tasks.

Ultrasound-Guided Catheterization Using a Driller-Tipped Guidewire With Combined Magnetic Navigation and Drilling Motion

The endovascular intervention has been widely used to treat occlusive peripheral vascular disease (PVD). However, the current procedure has concerns such as low successful rate, undesired trauma, and radiation exposure. This article proposes a robotic solution to mitigate these limitations. A miniature magnetic driller-tipped guidewire (MDG) is designed, which performs 1) controllable bending under directional magnetic fields to navigate in complex vasculature and 2) mechanical drilling under rotating magnetic fields to pass through clogged regions. An integrated actuation system is adopted for magnetic control and ultrasound (US) imaging in a large workspace. A control framework composed of the preoperative and intraoperative stages is developed, which internally coordinates all system modules, addresses noisy US imaging, and provides convenient operation. Demonstrations under an optical camera verify the flexible steering ability and effective unclogging motion of the MDG. Furthermore, US image-monitored <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in vitro</i> experiments validate the overall hardware platform and control strategy. The designed MDG realizes dual objectives, including controllability at bifurcations and penetrability at clots. The introduced US imaging modality largely reduces radiation hazards in conventional catheterization. This article studies the intervention of the MDG under electromagnetic field navigation and US imaging guidance. The proposed workflow has the potential to improve operational safety and clinical outcomes of the occlusive PVD treatment.

Modelling and Analysis of the Spital Branched Flexure-Hinge Adjustable-Stiffness Continuum Robot

Continuum robots are increasingly being used in industrial and medical applications due to their high number of degrees of freedom (DoF), large workspace and their ability to operate dexterously. However, the positional accuracy of conventional continuum robots with a backbone structure is usually low due to the low stiffness of the often-lengthy driving cables/tendons. Here, this problem has been solved by integrating additional mechanisms with adjustable stiffness within the continuum robot to improve its stiffness and mechanical performance, thus enabling it to be operated with high accuracy and large payloads. To support the prediction of the improved performance of the adjustable stiffness continuum robot, a kinetostatic model was developed by considering the generalized internal loads that are caused by the deformation of the flexure-hinge mechanism and the structural stiffening caused by the external loads on the end-effector. Finally, experiments were conducted on physical prototypes of 2-DoF and 6-DoF continuum robots to validate the model. It was found that the proposed kinetostatic model validates experimental observations within an average deviation of 9.1% and 6.2% for the 2-DoF and 6-DoF continuum robots, respectively. It was also found that the kinematic accuracy of the continuum robots can be improved by a factor of 32.8 by adding the adjustable stiffness mechanisms.

A Review of Cable-Driven Parallel Robots: Typical Configurations, Analysis Techniques, and Control Methods

Cable-driven parallel robots (CDPRs) have applications in large workspaces and at high operating speeds, which necessitates considering the mass and elasticity of cables for accurate analyses of kinematics, dynamics, workspace, trajectory planning, and control. In this article, first, the typical CDPR configurations along with their application areas are summarized. Then, various approaches, such as optimizing cable and motor configurations or integrating additional elements to the structure of CDPRs that can be used for workspace geometry optimization, are discussed. Afterward, different models for the cables with mass and elasticity, such as Irvine’s sagging or spring dampers studied in the literature for integrating into the kinematics and dynamics equations, are reported. Later, along with reviewing different approaches for trajectory planning of planar and spatial CDPRs, advances in configuration optimization for collision-free trajectory planning are addressed. Finally, kinematic and dynamic control algorithms to handle the effect of mass and elasticity of the cables and robust and adaptive control algorithms to tackle structured and unstructured uncertainties, such as in the mass and moment of the moving platform (MP) and external disturbances, are reported.

Review of Industrial Robot Stiffness Identification and Modelling

Due to their high flexibility, large workspace, and high repeatability, industrial robots are widely used in roughing and semifinishing fields. However, their low machining accuracy and low stability limit further development of industrial robots in the machining field, with low stiffness being the most significant factor. The stiffness of industrial robots is affected by the joint deformation, transmission mechanism, friction, environment, and coupling of these factors. Moreover, the stiffness of a robot has a nonlinear distribution throughout the workspace, and external forces during processing cause irregular deviations of the robot, thereby affecting the machining accuracy and surface quality of the workpiece. Many scholars have researched identifying the stiffness of industrial robots and have proposed methods for improving the performance of industrial robots, mainly by optimizing the body structure of the robot and compensating for deformation errors with stiffness models. This paper reviews recent research on the stiffness modelling of industrial robots, which can be broadly classified as finite element analysis (FEA), matrix structure analysis (MSA), and virtual joint modelling (VJM) methods. Each method is studied from three aspects: algorithms, implementation, and limitations. In addition, common measurement techniques have been introduced for measuring deformation. Further research directions are also discussed.