Deformable Robot Research Articles

Vision‐Based Online Key Point Estimation of Deformable Robots

The precise control of soft and continuum robots requires knowledge of their shape, which has, in contrast to classical rigid robots, infinite degrees of freedom. To partially reconstruct the shape, proprioceptive techniques use built‐in sensors, resulting in inaccurate results and increased fabrication complexity. Exteroceptive methods so far rely on expensive tracking systems with reflective markers placed on all components, which are infeasible for deformable robots interacting with the environment due to marker occlusion and damage. Here, a regression approach is presented for three‐dimensional key point estimation using a convolutional neural network. The proposed approach uses data‐driven supervised learning and is capable of online markerless estimation during inference. Two images of a robotic system are captured simultaneously at 25 Hz from different perspectives and fed to the network, which returns for each pair the parameterized key point or piecewise constant curvature shape representations. The proposed approach outperforms markerless state‐of‐the‐art methods by a maximum of 4.5% in estimation accuracy while being more robust and requiring no prior knowledge of the shape. Online evaluations on two types of soft robotic arms and a soft robotic fish demonstrate the method's accuracy and versatility on highly deformable systems.

Adaptable robotics for disaster response and search & rescue: Integration of deformable smart car design and pi control

In the context of disaster response and search and rescue operations, the need for adaptable and efficient robotic systems has become increasingly evident. This research paper addresses the evolving challenges in this domain by introducing a novel DIY deformable robot equipped with advanced PI (Proportional-Integral) control. The background of this study emerges from the growing urgency to enhance the capabilities of robotics in post-disaster scenarios, where navigation through complex terrains and the swift delivery of supplies are paramount.The primary objective of this paper is to develop and assess a versatile robotic platform using a multidisciplinary approach encompassing mechanical engineering, electronics, and control systems. The core of the investigation is a DIY deformable car consisting of two sensor-equipped containers and a linking module, making it well-suited for search and rescue missions. This paper contains the implementation of a PI control system to govern the robot's mobility and adaptability. This includes a detailed examination and demonstration of the PI control mechanism, encompassing its proportional and integral components. The actual results also indicate that the smart car controlled by the PI controller has better performance in both stability and speed.

Knowledge-based self-tuning of PID control gains for continuum soft robots

In recent years, a class of soft (deformable) robots has attracted the attention of researchers due to their continuum features being advantageous over rigid robots for dexterous and safe compliant motions. These distinct advantages are obtained from the elastomer hyperelastic material properties because continuum robots are manufactured and actuated through embedded pneumatic energy fields. In this way, the continuum deformation raises novel problems in modeling and control due to its highly nonlinear behavior. That is, the deformable shape of its components varies continuously, unlike rigid robots, suggesting that the controller should compensate for its varying continuum model. Motivated by the deformable soft robot subject to parametric uncertainties and unmodeled dynamics, this paper proposes an adaptive, instead of constant, tuning of feedback gains of a model-free controller. The tuning mechanism is based on a knowledge-based scheme using a discrete wavelet neural network (DWN) by an efficient input–output identification updating its parameters and weights online, with a gradient descent algorithm driven by the identification error. At the same time, the control feedback gains are self-tuned, minimizing a convex cost function of tracking errors. Dynamic simulations show the performance of the proposed approach considering the parameters of a real soft robot mimicking a gelatin-like behavior. Finally, some discussions on the proposed scheme’s computational cost, feasibility, and viability are briefly addressed.

Design and research of deformable wheel-legged robot based on origami mechanisms

This study presents a novel deformable wheeled robot based on an origami mechanism, designed to address the limited environmental adaptability of traditional wheeled robots. The research begins by rigorously establishing the fundamental parameters of the origami unit through an in-depth analysis of the Miura origami motion principle and a comprehensive study of the correlation between geometric parameters. Leveraging the theory of origami thickening, the origami unit is thickened and integrated into the design of the deformable Wheel-Legged mechanism. Controlled by a single motor, four Wheel-Legged structures enable seamless transformation between wheeled and legged forms. The paper provides a comprehensive analysis of the robot’s deformation, obstacle crossing, and other motion processes. Furthermore, it thoroughly investigates the effects of various gaits on the stability of the robot’s movement, followed by rigorous simulation and experimental verification. The experimental results unequivocally demonstrate the robot’s capability in deformation, steering, and obstacle avoidance.

Design and Control of a Miniaturized Magnetic-Driven Deformable Capsule Robot for Targeted Drug Delivery

Design and Control of a Miniaturized Magnetic-Driven Deformable Capsule Robot for Targeted Drug Delivery

Integrated optimization design and motion control of multi-configuration unmanned metamorphic vehicle

An unmanned metamorphic vehicle is a new deformable robot that can transform its configuration according to different road conditions in order to realize wheeled driving or legged walking. This paper proposes a method of multi-objective integrated optimization design based on the motion control of unmanned metamorphic vehicle. The aim of this method is to improve the stability and reduce energy consumption of multi-configuration motion. The vehicle state configuration and the humanoid state walking performance were designed. The kinematic model of reconfiguration and humanoid walking was established from screw theory, while the Lagrangian dynamics model for reconfiguration and humanoid walking using analytical mechanics. Reconfiguration and gait planning were carried out for an unmanned metamorphic vehicle, and a sliding mode controller was designed for position feedback control of the zero moment point in order to improve the stability of reconfiguration and walking. In order to improve the kinematic performance of an unmanned metamorphic vehicle under multiconfiguration, the NSGA-II intelligent optimization algorithm was used to optimize the multi-objective integrated design of the structural parameters, posture parameters, and control parameters of the sliding mode controller of the system. The simulation and test results showed that the integrated design performs higher reconfiguration stability, lower energy consumption, and higher control quality than the sequential design and pre-optimization under the reconfiguration condition; in the vehicle state, the transient steering stability and the steady-state steering stability of the system during driving are significantly improved; in the humanoid state, the energy consumption of the striding process and the movement of the center of mass to the single-legged support region in the walking process is reduced and the walking stability is improved, thus is more conducive to walking.

A robophysical model of spacetime dynamics

Systems consisting of spheres rolling on elastic membranes have been used to introduce a core conceptual idea of General Relativity: how curvature guides the movement of matter. However, such schemes cannot accurately represent relativistic dynamics in the laboratory because of the dominance of dissipation and external gravitational fields. Here we demonstrate that an “active” object (a wheeled robot), which moves in a straight line on level ground and can alter its speed depending on the curvature of the deformable terrain it moves on, can exactly capture dynamics in curved relativistic spacetimes. Via the systematic study of the robot’s dynamics in the radial and orbital directions, we develop a mapping of the emergent trajectories of a wheeled vehicle on a spandex membrane to the motion in a curved spacetime. Our mapping demonstrates how the driven robot’s dynamics mix space and time in a metric, and shows how active particles do not necessarily follow geodesics in the real space but instead follow geodesics in a fiducial spacetime. The mapping further reveals how parameters such as the membrane elasticity and instantaneous speed allow the programming of a desired spacetime, such as the Schwarzschild metric near a non-rotating blackhole. Our mapping and framework facilitate creation of a robophysical analog to a general relativistic system in the laboratory at low cost that can provide insights into active matter in deformable environments and robot exploration in complex landscapes.

Investigating frictional contact behavior for soft material robot simulations

The ability to interact safely with the environment is known as one of the major advantages of soft robots (SRs). Due to their low material stiffness, these continuously deformable robots offer inherent flexibility. These advantages make them suitable for application that involve human-robot collaboration in industrial settings as well as medical application such as minimally invasive surgery. To date only few research groups have analyzed the contact and frictional behavior of soft robots. In fact, the contact behavior is often oversimplified or neglected. Motivated by the idea to bridge this gap, this work presents measurements and the resulting coefficient of friction (COF) for silicone rubbers that are widely used in the field of SRs and different contact partners which depend on contact pressure and ambient temperature. From these measurements, a more representative contact model is established and used to more accurately simulate soft material robots’ frictional contact behavior. Moreover the influence of friction and therefore the need to implement frictional behavior is demonstrated for a typical application of a SR.

An energy dissipation metamaterial based on Coulomb friction and vibration

Compared with traditional energy dissipation structures, negative stiffness metamaterials can repeatedly dissipate energy without incurring irreversible plastic deformation. The existing negative stiffness structures are generally multistable, and their energy dissipation mechanism is either through internal component vibration or friction. In this paper, a self-recoverable negative stiffness structure was proposed which can dissipate energy through both vibration and Coulomb friction. The structure consists of an external I-shaped structure and a buckle-like structure composed of a plug and cantilever beams inside. The proposed structure achieves monostable characteristics by utilizing the concept of self-contact. To investigate the mechanical properties, quasi-static loading-unloading experiments were performed and verified using finite element simulation. The energy dissipated in the proposed structure by vibration and friction was quantified theoretically. The influence of geometric parameters on energy dissipation was studied using simulation and analytical methods. This type of metamaterial has the potential to be employed in the production of multi-functional metamaterial structures such as deformable robots or reusable bumpers.

DeforMoBot: A Bio-Inspired Deformable Mobile Robot for Navigation Among Obstacles

Many animals can move in cluttered environments by conforming their body shape to geometric constraints in their surroundings such as narrow gaps. Most robots are rigid structures and do not possess these capabilities. Navigation around movable or compliant obstacles results in a loss of efficiency—and possible mission failure—compared to progression through them. In this letter, we propose the novel design of a deformable mobile robot; it can adopt a wider stance for greater stability (and possible higher payload capacity), or a narrower stance to become capable of fitting through small gaps and progressing through flexible obstacles. We use a whisker-based feedback control approach to match the amount of the robot's deformation with the compliance level of the obstacle. We present a real-time algorithm which uses whisker feedback and performs shape adjustment in uncalibrated environments. The developed robot was tested navigating among obstacles with varying physical properties from different approach angles. Our results highlight the importance of co-development of environment perception and physical reaction capabilities for improved performance of mobile robots in unstructured environments.

Development of a Deformable Water-Mobile Robot

This article proposes a deformable water-mobile robot that can be used for rescue work. The robot body adopts an open-motion chain structure with two degrees of freedom, including two drive modules and one main control module. The three modules are connected through deformation joints, and each drive module is equipped with an underwater thruster. The robot can obtain a triangle, linear shape, curved shape, and U-shape through deformation and have three types of motion: linear shape motion, U-shaped motion, and curved shape motion. In the linear shape, a multi-island genetic algorithm was used to optimize the structural parameters with the minimum resistance and the maximum volume. Floating state analysis was conducted in the U-shape, and the structural parameters were reasonably designed. By experimenting with the robot prototype on water, the robot can achieve oscillating, linear, U-shaped, and horizontal rotary motion, has an automatic adjustment function, and effective buoyancy meets the required requirements.

Body Stiffness Control for Using Body-Environment Interaction with a Closed-Link Deformable Mobile Robot

It is necessary for the robot to use interactions from the environment through the body in order to adaptively move through various environments. When the robot is faced with a narrow path or a space with many pillars, it should be able to use its interaction with the environment to thin its own shape, i.e., it should have a flexible body. In contrast, in the case where we want the robot to move forward powerfully on a slope or uneven terrain (small steps), it is preferable for the robot to rigidify its own body and exert a strong propulsive force in response to interactions from the environment. In this paper, we present an idea of a mobile robot that can adjust its body flexibility (stiffness) to realize such adaptive behavior, and furthermore, we demonstrate its validity through experiments. Specifically, we propose a closed-link deformable mobile robot whose stiffness can be adjusted by indirectly driving joints. We design a function that increases the stiffness of the body by controlling the joints to follow the target angle quickly, and a function that decreases the stiffness of the body by controlling the joints to follow the angle slowly. The effectiveness of a robot that can adjust its stiffness is demonstrated through experiments of traversing narrow paths and steps. We also discuss propulsion control that takes advantage of the deformable mobile robot and its applicability to uneven slopes due to the flexibility of the links.

Toward Intrinsic Force Sensing and Control in Parallel Soft Robots

With soft robotics being increasingly employed in settings demanding high and controlled contact forces, recent research has demonstrated the use of soft robots to estimate or intrinsically sense forces without requiring external sensing mechanisms. While this has mainly been shown in tendon-based continuum manipulators or deformable robots comprising of push–pull rod actuation, fluid drives still pose great challenges due to high actuation variability and nonlinear mechanical system responses. In this work, we investigate the capabilities of a hydraulic, parallel soft robot to intrinsically sense and subsequently control contact forces. A comprehensive algorithm is derived for static, quasi-static, and dynamic force sensing, which relies on fluid volume and pressure information of the system. The algorithm is validated for a single degree-of-freedom soft fluidic actuator. Results indicate that axial forces acting on a single actuator can be estimated with mean error of 0.56 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\pm$</tex-math></inline-formula> 0.66 N within the validated range of 0–6 N in a quasi-static configuration. The force sensing methodology is applied to force control in a single actuator as well as the coupled parallel robot. It can be seen that forces are controllable for both systems, with the capability of controlling directional contact forces in case of the multidegree-of-freedom parallel soft robot.

Analysis and Design of the Reconfiguration Motion Qualities of a Deformable Robot Based on a Metamorphic Mechanism

Analysis and Design of the Reconfiguration Motion Qualities of a Deformable Robot Based on a Metamorphic Mechanism

Multifunctional Shape Memory Composites for Joule Heating, Self‐Healing, and Highly Efficient Microwave Absorption

AbstractTraditional microwaves absorption materials (MAMs) are applied in the form of coatings, generally inflexible, with high production costs and poor adaptability to applications in different locations. The diversification of application scenarios requires materials with multifunctionalities, but it is extremely challenging to integrate multifunctionalities within single material at present. Herein, a multifunctional CoNC@GN/PCL/TPU MAMs is synthesized. The CoNC@GN nano‐micro absorber has high‐efficiency microwave absorption ability. The electromagnetic microwave absorption performance is ultra‐light (4 wt.%), ultra‐thin (2.3 mm), and broadband (6.21 GHz), which is better than similar MAMs. Additionally, the samples have highly efficient electro‐thermal conversion properties, enabling controlled electrical heating performance and excellent self‐healing properties. More remarkably, the sample has an electrically driven shape memory effect that allows the material to target the absorption of multi‐angle incident electromagnetic waves. Therefore, CoNC@GN/PCL/TPU absorbers are the key to truly opening up opportunities for flexible, shape memory, and multifunctional absorbers in frontier applications such as wearables, deformable robots, and chip protection.

Practical Obstacle-Overcoming Robot with a Heterogeneous Sensing System: Design and Experiments

It is challenging for robots to improve their ability to pass through unstructured environments while maximizing motion performance in cities and factories. This paper presents an omnidirectional deformable wheeled robot based on a heterogeneous sensing system. We presented a novel structure with dual swing arms and six wheels. Moreover, the heterogeneous sensing system can perceive critical environmental data, such as friction and temperature, to assist the robot in executing different functions. In addition, a top-down ‘Order–Decision–Behaviour’ overall motion strategy is proposed based on the data acquisition. The strategy combines the key condition parameters with a kinetic model to integrate the robot’s movement, overcoming of obstacles, and mode switching. The robot is flexible and fast in moving mode and can overcome obstacles safely, reliably, and simply. This study describes the robot’s design, strategy, simulation, and experiments. Motion performance and strategy were investigated and evaluated in field environments.

From a Deployable Soft Mechanism Inspired by a Nemertea Proboscis to a Robotic Blood Vessel Mechanism

In this project, we aim to establish a design theory as well as implementation methods for deformable robot mechanisms that can branch and change in shape, structure, and stiffness. As the first step in our research on this project, we present an initial prototype of a branched torus mechanism that uses an inflatable structure inspired by a nemertea proboscis. We develop a basic mechanical model of this proboscis structure, and we confirm the basic performance and effective functionality of the configuration experimentally using a real prototype, specifically, a deployable torus mechanism and a retractable torus mechanism with an incompressible fluid. In addition, as an expanded concept from the branched torus mechanism, robotic blood vessels that can have an active self-healing function are prototyped, and the basic performance of the actual prototype is confirmed through experiments.

Hierarchical Point Cloud Encoding and Decoding With Lightweight Self-Attention Based Model

In this letter we present SA-CNN, a hierarchical and lightweight self-attention based encoding and decoding architecture for representation learning of point cloud data. The proposed SA-CNN introduces convolution and transposed convolution stacks to capture and generate contextual information among unordered 3D points. Following conventional hierarchical pipeline, the encoding process extracts feature in local-to-global manner, while the decoding process generates feature and point cloud in coarse-to-fine, multi-resolution stages. We demonstrate that SA-CNN is capable of a wide range of applications, namely classification, part segmentation, reconstruction, shape retrieval, and unsupervised classification. While achieving the state-of-the-art or comparable performance in the benchmarks, SA-CNN maintains its model complexity several order of magnitude lower than the others. In term of qualitative results, we visualize the multi-stage point cloud reconstructions and latent walks on rigid objects as well as deformable non-rigid human and robot models.

Design and Analysis of a Novel Deformable Wheel-legged Robot

Design and Analysis of a Novel Deformable Wheel-legged Robot

Design, Modeling and Validation of a Deformable Capsule-Like Crawling Robot Based on Scissor Elements

Design, Modeling and Validation of a Deformable Capsule-Like Crawling Robot Based on Scissor Elements