Synergistic integration of vibration absorption and damping into 3D-printed fixtures for thin-wall machining

To reduce vibration during machining and to avoid re-manufacture or scrap parts, two main methods have been proposed, vibration damping and absorption. In this paper, a novel synergistic integration between both techniques using pillar elements known as flexures (acting as absorbers) and a flexible pneumatic expandable diaphragm (acting as a damper) is presented. Four setups have been compared: the proposed Hybrid Fixture, a traditional solid vice, a flexures fixture, and an expandable diaphragm-only clamp. The Hybrid Fixture was able to reduce the workpiece vibration by 58% and the surface waviness by 74.1% when compared with the traditional solid fixture

A Robust Human–Robot Collaborative Control Approach Based on Model Predictive Control

Human skill-based robotic control to perform critical manufacturing operations (e.g., repair and inspection for high-value assets) can reduce scrap rates and increase overall profitability in the industrial community. In this study, a human–robotic collaborative control system is developed for accurate path tracking subject to unknown external disturbances and multiple physical constraints. This is achieved by designing a model predictive control with a sliding-mode disturbance rejection term. To rule out the possibility of the constraints violation caused by external disturbances, tightened constraints are formulated to generate the control input signal. The proposed controller drives the robotic system remotely with enhanced smoothness and real-time human modification on the outputted performance so that the human experience can be fully transferred to robotic systems. The efficacy of the proposed collaborative control system is verified by both Monte–Carlo simulation with 200 cases and experimental results including tungsten inert gas welding based on a universal robot 5e with 6 degree-of-freedom

Modelling of modular soft robots: From a single to multiple building blocks

Despite the advances in soft robots, their modelling is still one of the research challenges due to the complexity and non-linearity of their soft nature. A novel design of reconfigurable soft robots was recently introduced to bring more maturity to the field of soft robots. Here, a modelling study of the building blocks and the assembled soft robot is developed for a deeper understanding of the system and for predicting their behaviours. The model is validated using several sets of individual and multiple building blocks and the results show good tracking between the model and the experiments with reasonable errors. Towards adopting the model in robotic applications, a grasping setup of 2 assembled soft fingers is demonstrated where the model is used to predict the grasping force and compared to feedback sensing. The force prediction reveals the adaptability of the model and its robustness

An efficient follow-the-leader strategy for continuum robot navigation and coiling

Efficient path planning for hyper-redundant continuum and snake-like robots is a challenging task due to limited sensing capabilities, high computational loads, multiple possible solutions, and non-linear models. This paper presents a new approach to snake robot navigation and coiling, with an algorithm that enables online step-by-step position adjustment with a follow-the-leader strategy, significantly improving the performance of the robot when compared to previous methods. The proposed algorithm is demonstrated on a 16-degree-of-freedom snake-like robot for inspection and maintenance tasks in nuclear facilities

Tasering Twin Soft Robot: A Multimodal Soft Robot Capable of Passive Flight and Wall Climbing

The application of Soft Crawling Robots (SCRs) to real-world scenarios remains a grand challenge due to their limited deployment time to reach the target and accessibility to difficult-to-reach environments by any obstacles. To overcome these limitations, a novel multimodal Tasering Twin Soft Robot (TTSR), carrying two SCRs, capable of 1) passive flight and 2) wall climbing to a desired location by deploying SCRs once reached the target is proposed. For satisfying both tasks, reconfigurable design of SCRs using a novel bistable mechanism and detaching mechanism based on a shape-memory alloy for deploying SCRs is proposed. Each SCR is driven by two dielectric elastomer actuators (DEA) and three electroadhesive (EA) feet. To demonstrate multimodality, the TTSR with two SCRs is launched by pneumatic pressure and flown over an obstacle. While flying, the SCRs are folded compactly to reduce the air drag and perch on a wall 3 m away (50 times of body length) within 0.64 s. After perching, the SCRs reconfigure themselves for crawling and separated from each other. After that, the SCRs crawl, performing planar motion, and reach predefined locations on the wall. Moreover, the SCR can move across 15°-slope dihedral surfaces and inverted surface

Cooperative continuum robots: Enhancing individual continuum arms by reconfiguring into a parallel manipulator

Continuum robots are able of in-situ inspection tasks in cluttered environments and narrow passages, where conventional robots and human operators cannot intervene. However, such intervention often requires the robot to interact with the environment, and the low stiffness and payload of continuum robots limits their intervention capabilities. In this paper, we propose a paradigm shift from individual to multiple continuum robots, which can reach the target environment from different paths and then physically connect, reconfiguring into a parallel architecture to enhance precision, stiffness, and payload. The main challenges in modelling and controlling cooperative continuum robots are outlined, and an experimental comparison between individual and cooperating continuum robots that connect through a novel shape-memory-alloy-based clutch highlights the advantages of the proposed technology

Reconfigurable Soft Robots by Building Blocks

Soft robots are of increasing interest as they can cope with challenges that are poorly addressed by conventional rigid-body robots (e.g., limited flexibility). However, due to their flexible nature, the soft robots can be particularly prone to exploit modular designs for enhancing their reconfigurability, that is, a concept which, to date, has not been explored. Therefore, this paper presents a design of soft building blocks that can be disassembled and reconfigured to build different modular configurations of soft robots such as robotic fingers and continuum robots. First, a numerical model is developed for the constitutive building block allowing to understand their behavior versus design parameters, then a shape optimization algorithm is developed to permit the construction of different types of soft robots based on these soft building blocks. To validate the approach, 2D and 3D case studies of bio-inspired designs are demonstrated: first, soft fingers are introduced as a case study for grasping complex and delicate objects. Second, an elephant trunk is used for grasping a flower. Third, a walking legged robot. These case studies prove that the proposed modular building approach makes it easier to build and reconfigure different types of soft robots with multiple complex shapes

Contouring controller design based on iterative contour error estimation for three-dimensional machining

Recently, there has been a growth of interest in high precision machining in multi-axis feed drive systems, subjected to problems such as friction, cutting force and incompatibility of individual driving axis dynamics. To guarantee high precision machining in modern computer numerical controlled (CNC) machines, CNC's controllers do its control efforts to reduce contour error. One of the common approaches is to design a controller based on the estimation of contour error in real time. However, for complex contours with severe curvatures, there is a lack of effective algorithms to calculate contour errors accurately. To address this problem, this paper proposes an accurate contour error estimation procedure for three-dimensional machining tasks. The proposed method is based on an iterative estimation of the instantaneous curvature of the reference trajectory and coordinates transformation approach, and hence, it is effective for complex reference trajectories with high curvatures. In addition, contour error controller is presented to reduce the estimated contour error. The feasibility and superiority of the proposed model as well as contour error controller are demonstrated through experimental system using a desk-top three-axis CNC machine. © 2011 Elsevier Ltd

Energy Saving in Feed Drive Systems Using Sliding-Mode-Based Contouring Control With a Nonlinear Sliding Surface

Reduction of contour error, which is defined as the shortest distance between the actual position of the cutting tool and the reference trajectory, is an essential requirement in machining by multiaxis feed drive systems. In addition, because these machines operate all the time in industrial applications all over the world, reduction of the consumed energy in these machines contributes to environmental, natural resources, and energy problems. This paper presents a novel sliding mode contouring controller with a nonlinear sliding surface to improve the machining accuracy of the biaxial feed drive systems. Because the contour error is more important than the tracking error with respect to each feed drive axis, the contour error component is included in the proposed sliding surface. The advantage of including the contour error in the proposed sliding surface is that the damping ratio of the system changes from its initial low value to final high value as the contour error changes from high value to small value and vice versa. Hence, the proposed algorithm allows a closed-loop system to simultaneously achieve low energy consumption and small settling time, resulting in a smaller error. By using the proposed method, experimental results for a biaxial feed drive system show a significant performance improvement in terms of the contour error. In addition, the proposed approach reduces the control input variance by about 41.2 % and 14.9 % for x - and y-axis, respectively, and consumed energy by about 23.7 % and 5.5 % for the respective axis from the conventional method with a linear sliding surface