Search Results (31)

Modular self-reconfigurable robots hold the promise of being capable of performing a wide variety of tasks. However, many systems fall short of either delivering this promised functionality due to constraints in system architecture or validating it on functional hardware prototypes. This paper demonstrates the functional capabilities of the Planar Adaptive Robot with Triangular Structure (PARTS) and documents the versatility of this robot system using a holistic approach that combines simulations and hardware demonstrations on a prototype with nine fabricated modules. PARTS is a two-dimensional modular robot consisting of modules with a shape-shifting triangular geometry capable of forming adaptable space-covering structures. Meta-modules and mesh restructuring techniques are presented as methods for achieving topological self-reconfiguration. The feasibility of these methods is demonstrated by applying them on a simulated reconfiguration example of 62 modules. The paper showcases the versatility of PARTS on the hardware prototype using task-specific configurations, including locomotion using a meta-module and a walker configuration, module-module interaction by establishing a bridge between two separated module clusters, and interaction with the environment using a gripper and supporting structure configuration. The results validate the versatility and emphasize the potential of the system’s design concept, motivating the transfer of the hardware architecture to the third dimension. Full article

The ability of shape memory polymers to change shape upon external stimulation makes them exceedingly useful in various areas, from biomedical engineering to soft robotics. Especially, shape memory hydrogels (SMHs) are well-suited for biomedical applications due to their inherent biocompatibility, excellent shape morphing performance, tunable physiochemical properties, and responsiveness to a wide range of stimuli (e.g., thermal, chemical, electrical, light). This review provides an overview of the unique features of smart SMHs from their fundamental working mechanisms to types of SMHs classified on the basis of applied stimuli and highlights notable clinical applications. Moreover, the potential of SMHs for surgical, biomedical, and tissue engineering applications is discussed. Finally, this review summarizes the current challenges in synthesizing and fabricating reconfigurable hydrogel-based interfaces and outlines future directions for their potential in personalized medicine and clinical applications. Full article

Liquid crystal elastomers (LCEs) are a monolithic material with programmable three-dimensional (3D) morphing modes stemming from their designable non-uniform molecular orientations (or director). However, the shape morphing mode is generally fixed when director patterns of LCEs are determined. Multi-mode shape morphing is difficult to achieve since director patterns cannot be reconfigured. Herein, we demonstrate the ability to reconfigure LCE director patterns and initial shapes—and thus shape morphing modes—by the manual assembly and de-assembly of LCE pixels. We measured the mechanical properties of LCEs with and without UV glue and found their Young’s moduli were 9.6 MPa and 11.6 MPa. We firstly fabricate LCE pixels with designed director fields and then assemble 24 pixels with required director fields into an LCE film with a designed director pattern, which corresponds to a programmed shape morphing mode. We further exhibit that we can de-assemble the LCE film back into original pixels or new pixels with different shapes and then re-assemble them into a new film with a different initial shape and director pattern, which corresponds to a second programmed shape morphing mode. Principally, we can have a large amount of shape morphing modes if we have enough pixels. The demonstrated capability of multi-mode shape morphing enhances functions of LCEs, which broadens their applications in soft robotics, programmable origami/kirigami, responsive surfaces, and so on. Full article

Reconfigurable robots have the potential to perform complex tasks by adapting their morphology to different environments. However, designing optimal morphologies for these robots is challenging due to the large design space and the complex interactions between the robot and the environment. An in-house robot named $Smorphi$, having four holonomic mobile units connected with three hinge joints, is designed to maximize area coverage with its shape-changing features using transformation design principles (TDP). The reinforcement learning (RL) approach is used to identify the optimal morphologies out of a vast combination of hinge angles for a given task by maximizing a reward signal that reflects the robot’s performance. The proposed approach involves three steps: (i) Modeling the Smorphi design space with a Markov decision process (MDP) for sequential decision-making; (ii) a footprint-based complete coverage path planner to compute coverage and path length metrics for various Smorphi morphologies; and (iii) pptimizing policies through proximal policy optimization (PPO) and asynchronous advantage actor–critic (A3C) reinforcement learning techniques, resulting in the generation of energy-efficient, optimal Smorphi robot configurations by maximizing rewards. The proposed approach is applied and validated using two different environment maps, and the results are also compared with the suboptimal random shapes along with the Pareto front solutions using NSGA-II. The study contributes to the field of reconfigurable robots by providing a systematic approach for generating optimal morphologies that can improve the performance of reconfigurable robots in a variety of tasks. Full article

Miniaturized four-dimensional (4D) micro/nanorobots denote a forerunning technique associated with interdisciplinary applications, such as in embeddable labs-on-chip, metamaterials, tissue engineering, cell manipulation, and tiny robotics. With emerging smart interactive materials, static micro/nanoscale architectures have upgraded to the fourth dimension, evincing time-dependent shape/property mutation. Molecular-level 4D robotics promises complex sensing, self-adaption, transformation, and responsiveness to stimuli for highly valued functionalities. To precisely control 4D behaviors, current-laser-induced photochemical additive manufacturing, such as digital light projection, stereolithography, and two-photon polymerization, is pursuing high-freeform shape-reconfigurable capacities and high-resolution spatiotemporal programming strategies, which challenge multi-field sciences while offering new opportunities. Herein, this review summarizes the recent development of micro/nano 4D laser photochemical manufacturing, incorporating active materials and shape-programming strategies to provide an envisioning of these miniaturized 4D micro/nanorobots. A comparison with other chemical/physical fabricated micro/nanorobots further explains the advantages and potential usage of laser-synthesized micro/nanorobots. Full article

Detrimental environmental impacts due to the increasing demands of the aviation industry have gained tremendous global attention. With a potential fuel saving, along with high aerodynamic performance and maneuverability during different phases of a flight, adaptable wing design has become a viable alternative to its fixed-shape counterpart. A morphing wing design embraces, and can respond accordingly to, most of the flight condition variations effectively and efficiently. Despite these prospects, morphing wing design comes with some challenges due to its inherent complexity caused by an increased number of degrees of freedom. With the availability of various morphing parameters, the vibration signature of a morphing wing design plays a vital role in terms of its structural as well as aeroelastic characteristics. In the present paper, the dynamic characteristics of a re-configurable modular morphing wing developed in-house by a research team at Toronto Metropolitan University are investigated. This modular morphing wing, developed based on the idea of a parallel robot, consists of a number of structural elements connected to each other and to the wing ribs through eyebolt joints. Timoshenko bending beam theories, in conjunction with finite element methodology, are exploited. The free vibration of un-morphed (original) and morphed configurations undergoing multiple levels of sweep and spanwise morphing is presented through a design of experiment methodology. Full article

The field of soft matter is rapidly growing and pushing the limits of conventional materials science and engineering. Soft matter refers to materials that are easily deformed by thermal fluctuations and external forces, allowing for better adaptation and interaction with the environment. This has opened up opportunities for applications such as stretchable electronics, soft robotics, and microfluidics. In particular, soft matter plays a crucial role in microfluidics, where viscous forces at the microscale pose a challenge to controlling dynamic material behavior and operating functional devices. Field-driven active colloidal systems are a promising model system for building smart functional devices, where dispersed colloidal particles can be activated and controlled by external fields such as magnetic and electric fields. This review focuses on building smart functional devices from field-driven collective patterns, specifically the dynamic structuring of hierarchically ordered structures. These structures self-organize from colloidal building blocks and exhibit reconfigurable collective patterns that can implement smart functions such as shape shifting and self-healing. The review clarifies the basic mechanisms of field-driven particle dynamic behaviors and how particle–particle interactions determine the collective patterns of dynamic structures. Finally, the review concludes by highlighting representative application areas and future directions. Full article

Reconfigurable robots design based on polyominos or n-Omino is increasingly being explored in cleaning and maintenance (CnM) tasks due to their ability to change shape using intra- and inter-reconfiguration, resulting in various footprints of the robot. On one hand, reconfiguration during a CnM task in a given environment or map results in enhanced area coverage over fixed-form robots. However, it also consumes more energy due to the additional effort required to continuously change shape while covering a given map, leading to a deterioration in overall performance. This paper proposes a new strategy for n-Omino-based robots to select a range of optimal morphologies that maximizes area coverage and minimizes energy consumption. The optimal “morphology” is based on two factors: the shape or footprint obtained by varying the angles between the n-Omino blocks and the number of n-Omino blocks, i.e., “n”. The proposed approach combines a Footprint-Based Complete coverage Path planner (FBCP) with a metaheuristic optimization algorithm to identify an n-Omino-based reconfigurable robot’s optimal configuration, assuming energy consumption is proportional to the path length taken by the robot. The proposed approach is demonstrated using an n-Omino-based robot named Smorphi, which has square-shaped omino blocks with holonomic locomotion and the ability to change from monomino to tetromino. Three different simulated environments are used to find the optimal morphologies of $Smorphi$ using three metaheuristic optimization techniques, namely, MOEA/D, OMOPSO, and HypE. The results of the study show that the morphology produced by this approach is energy efficient, minimizing energy consumption and maximizing area coverage. Furthermore, the HypE algorithm is identified as more efficient for generating optimal morphology as it took less time to converge than the other two algorithms. Full article

This paper presents a universal approach to shaping the mechanical properties of the interaction between a collaborative robot and its environment through an end-effector Cartesian compliance shaping. More specifically, the focus is on the class of kinematically redundant robots, for which a novel redundancy reconfiguration scheme for online optimization of the Cartesian compliance of the end-effector is presented. The null-space reconfiguration aims to enable the more efficient and versatile use of collaborative robots, including robots with passive compliant joints. The proposed approach is model-based and gradient-based to enable real-time computation and reconfiguration of the robot for Cartesian compliance while ensuring accurate position tracking. The optimization algorithm combines two coordinate frames: the global (world) coordinate frame commonly used for end-effector trajectory tracking; and the coordinate frame fixed to the end-effector in which optimization is computed. Another attractive feature of the approach is the bound on the magnitude of the interaction force in contact tasks. The results are validated on a torque-controlled 7-DOF KUKA LWR robot emulating joint compliance in a quasi-static experiment (the robot exerts a force on an external object) and a peg-in-hole experiment emulating an assembly task. Full article

Multiple robots are used in robotic applications to achieve tasks that are impossible to perform as individual robotic modules. At the microscale/nanoscale, controlling multiple robots is difficult due to the limitations of fabrication technologies and the availability of on-board controllers. This highlights the requirement of different approaches compared to macro systems for a group of microrobotic systems. Current microrobotic systems have the capability to form different configurations, either as a collectively actuated swarm or a selectively actuated group of agents. Magnetic, acoustic, electric, optical, and hybrid methods are reviewed under collective formation methods, and surface anchoring, heterogeneous design, and non-uniform control input are significant in the selective formation of microrobotic systems. In addition, actuation principles play an important role in designing microrobotic systems with multiple microrobots, and the various control systems are also reviewed because they affect the development of such systems at the microscale. Reconfigurability, self-adaptable motion, and enhanced imaging due to the aggregation of modules have shown potential applications specifically in the biomedical sector. This review presents the current state of shape formation using microrobots with regard to forming techniques, actuation principles, and control systems. Finally, the future developments of these systems are presented. Full article

Orthotopic neobladder reconstruction is becoming an increasing option as a urinary diversion following cystectomy for bladder cancer. The purpose of the following article is to describe, step-by-step, our technique for the robotic intracorporeal neobladder, the Vesuvian Orthotopic Neobladder. The primary aim of this new surgical procedure is to simplify and speed up the reservoir reconstruction, while at the same time obtaining an appropriate reservoir capacity. The Vesuvian Orthotopic Neobladder was performed employing an intestinal tract of 36 cm which was successively shaped in order to form a reservoir with three horns (left, right, and caudal), formed via the use of a mechanical stapler. Both ureters were stented and anastomosed to the left and right horn while the urethral-neobladder anastomosis was performed with the caudal horn. In this initial experience, two male patients with non-metastatic muscle-invasive bladder cancer underwent radical cystectomy followed by Vesuvian Orthotopic Neobladder reconfiguration. The mean age was 58.5 ± 3.53 years while the mean overall operative time was 435 ± 35.35 min, with an average neobladder reconstruction time of 59 ± 4.24 min. No intraoperative or postoperative complications were reported. The new intracorporeal Vesuvian Orthotopic Neobladder technique is a feasible and good alternative to traditional robotic intracorporeal orthotopic bladder procedures, permitting us to reduce operative time and obtain a neobladder with a fair reservoir capacity. Full article

Flexible materials that provide an electric, magnetic, or optic response upon deformation or tactile pressure could be important for the development of smart monitors, intelligent textiles, or in the development of robotic skins. In this work we demonstrate the capabilities of a flexible and electrically conductive polymer material that produces an electrical response with any deformation, namely the electrical resistance of the material changes proportionally with the deformation pressure. Furthermore, the material exhibits a memory effect. When compressed beyond the elastic regime, it retains the memory of the plastic deformation by increasing its resistance. The material was obtained by in situ polymerization of semiconducting polyaniline (PANi) in a polyvinyl alcohol/glycerol (PVA/Gly) hydrogel matrix at −17 °C. Upon drying of the hydrogel, an elastomer composite is obtained, with rubber-like characteristics. When compressed/decompressed, the electrical resistance of the material exhibits an unusually long equilibration/relaxation time, proportional with the load applied. These phenomena indicate a complex relaxation and reconfiguration process of the PANi/PVA elastomer matrix, with the shape change of the material due to mechanical stress. Full article

Cebrenus Rechenburgi, a member of the huntsman spider family have inspired researchers to adopt different locomotion modes in reconfigurable robotic development. Object-of-interest perception is crucial for such a robot to provide fundamental information on the traversed pathways and guide its locomotion mode transformation. Therefore, we present a object-of-interest perception in a reconfigurable rolling-crawling robot and identifying appropriate locomotion modes. We demonstrate it in Scorpio, our in-house developed robot with two locomotion modes: rolling and crawling. We train the locomotion mode recognition framework, named Pyramid Scene Parsing Network (PSPNet), with a self-collected dataset composed of two categories paths, unobstructed paths (e.g., floor) for rolling and obstructed paths (e.g., with person, railing, stairs, static objects and wall) for crawling, respectively. The efficiency of the proposed framework has been validated with evaluation metrics in offline and real-time field trial tests. The experiment results show that the trained model can achieve an mIOU score of 72.28 and 70.63 in offline and online testing, respectively for both environments. The proposed framework’s performance is compared with semantic framework (HRNet and Deeplabv3) where the proposed framework outperforms in terms of mIOU and speed. Furthermore, the experimental results has revealed that the robot’s maneuverability is stable, and the proposed framework can successfully determine the appropriate locomotion modes with enhanced accuracy during complex pathways. Full article

Liquid metal (LM)–polymer composites that combine the thermal and electrical conductivity of LMs with the shape-morphing capability of polymers are attracting a great deal of attention in the fields of reconfigurable electronics and soft robotics. However, investigation of the synergetic effect between the shape-changing properties of LMs and polymer matrices is lacking. Herein, a self-healable and recyclable dual-shape memory composite, comprising an LM (gallium) and a Diels–Alder (DA) crosslinked crystalline polyurethane (PU) elastomer, is reported. The composite exhibits a bilayer structure and achieves excellent shape programming abilities, due to the phase transitions of the LM and the crystalline PU elastomers. To demonstrate these shape-morphing abilities, a heat-triggered soft gripper, which can grasp and release objects according to the environmental temperature, is designed and built. Similarly, combining the electrical conductivity and the dual-shape memory effect of the composite, a light-controlled reconfigurable switch for a circuit is produced. In addition, due to the reversible nature of DA bonds, the composite is self-healable and recyclable. Both the LM and PU elastomer are recyclable, demonstrating the extremely high recycling efficiency (up to 96.7%) of the LM, as well as similar mechanical properties between the reprocessed elastomers and the pristine ones. Full article

This paper presents the design and experiment of an autonomous underwater robot which can change the geometric configuration of its actuators, according to mission requirements or environmental constraints. The robot consists of two subsystems: forward part with three thrusters and backward part with four thrusters. The position and orientation of these thrusters can be dynamically changed during missions. Being different from most of other reconfigurable underwater robots which were designed as linked-modules, our robot has a unified design. It is suitable for specific mission in confined environments (e.g., karst exploration) in which the robot has to modify its shape to go through a narrow section or align the most part of its thrusters in the direction of a strong current, for examples. The design procedure, from hardware to software, of the robot is presented and experimental results are shown to demonstrate the versatility of the robot. Furthermore, the discussion and comparison between our robot and other underwater robots with adaptable actuation geometry are presented to highlight advantages of our design. Finally, the idea of using our robot for classic docking problem, which has some common features with karst exploration requirements in using dynamically reconfigurable robots, is discussed. Full article