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Soft robots demonstrate superior flexibility and maneuverability than traditional rigid robots in many emerging applications. However, it is challenging to have a general modeling and control methodology to deal with soft body dynamics and its interactions with environment. We present a spline-based modeling and control framework for soft robotic systems. The dynamic model is built on non-uniform rational Bsplines (NURBS) that captures material and physical properties of soft body, while preserving exact geometric dynamics with environmental interactions. Using the NURBS-based dynamic model, the robotic optimal control based on general predictive control is designed through coordination among the finite number of control points. Therefore, the infinite-dimensional motion of soft body can be realized by significantly reduced finite particle motion control. We demonstrate the performance of the modeling and motion control framework using the snakeinspired robot simulations and experiments.

Biological systems are composed of a large number of continuum elements and they effectively realize their flexible and smooth functionalities by capitalizing on the rich dynamics occurring in their soft bodies. In particular, the diverse spatiotemporal patterns of the continuum body have recently been demonstrated as highly useful in implementing a certain class of computation, implying that soft bodies can work as computational devices like nervous systems. However, unlike nervous systems whose activities are basically chaotic and spontaneous, soft bodies are passive and eventually stop their movements without undergoing external force. In addition, both nervous systems and soft bodies are tightly coupled in biological systems and seamlessly contribute to establishing the functionalities as a whole, making it difficult to clarify the specific roles of each element and the degrees of contribution. In this paper, we quantitatively investigate a general role of the soft bodies by introducing a new concept called input reservoir and examining the contribution of the passive elements to information processing. Input reservoir refers to a dynamical system that acts as a filter with a fading memory property whose output is projected onto a chaotic dynamical system and works as an interface between the external stimulus and the chaotic system. Soft bodies can be considered as one type of input reservoir in terms of function because soft bodies are placed between the environment and the chaotic nervous system. We show that the performance of a certain type of temporal task can be improved by installing an input reservoir and training the internal weights of the connected chaotic neural network using a reservoir computing method called innate training . Moreover, we demonstrate that complicated spatiotemporal patterns collected by sensing the soft body dynamics significantly contribute to increasing the computational capacity of the whole by projecting them onto a chaotic neural network and modifying the network weights by innate training. These results imply that soft continuum elements in biological systems have a significant effect in the system's information processing even when the soft elements are firmly joined with the nervous system.

Position-based dynamics has emerged as an exceedingly popular approach for animating soft body dynamics. Unfortunately, the basic approach suffers from artificial loss of angular momentum. We propose a simple approach to preserve global linear and angular momenta of bodies by directly tracking these quantities and adjusting velocities to ensure they are preserved. This approach entails negligible computational cost, requires less than 25 lines of code, and exactly preserves global linear and angular momenta.

We propose an algorithm that is fully parallel and has linear time complexity for soft body simulation that addresses three principal issues; Visual Quality, Performance and Ease of use. It works using the power of precomputed collision result look-up data and basic approach of shape matching. Since data driven shape matching approach only uses user generated precomputed collision results, deformation results cannot be unexpected. This creates visual quality and improves ease of use. Also, usage of these look-up data opens ways to improve Performance. In our tests, we achieved direct linear speed up depending on the processor's core count.

We describe the gamification of a soft physics simulator. We developed a game, called Jelly Dude, that allows the player to change and modify the game engine by tinkering with various physics parameters, creating custom game levels and installing scripts. The game engine is capable of simulating soft-body physics and can display the simulation results visually in real-time. In order to ensure high quality graphics in real time, we have implemented intelligent computational offloading to the cloud using Jordan Neural Network (JNN) with a fuzzy logic scheme for short time prediction of network traffic between a client and a cloud server. The experimental results show that computation offloading allowed us to increase the speed of graphics rendering in terms of frames per second, and to improve the precision of soft body modeling in terms of the number of particles used to represent a soft body.

The octopus has been one of the major sources of inspiration for roboticists for many years. It can harness its complex body dynamics in a highly sophisticated manner despite the fact that its body does not contain any rigid components through the interaction between the characteristic organization of its nervous system and its specific body morphology and muscle characteristics, called muscular-hydrostats. Inspired by these biological findings, we investigated the potential information processing capacity of its soft body dynamics with the help of a machine learning approach called reservoir computing. We review a series of concepts and platforms, called muscular-hydrostat computers throughout our study and suggest that the diverse body dynamics of soft materials can be exploited as a computational resource. This approach could enable some controls to be embedded into the robot body.

In this paper we present a physics-based framework for simulation and control of human-like skeleton-driven soft body characters. We couple the skeleton dynamics and the soft body dynamics to enable two-way interactions between the skeleton, the skin geometry, and the environment. We propose a novel pose-based plasticity model that extends the corotated linear elasticity model to achieve large skin deformation around joints. We further reconstruct controls from reference trajectories captured from human subjects by augmenting a sampling-based algorithm. We demonstrate the effectiveness of our framework by results not attainable with a simple combination of previous methods.

Based on the FEA software ANSYS Workbench, the soft body dynamics performance of the gear pump gear mesh of a hydraulic pump company was analyzed. In the practical engineering applications, gear pump gear teeth are effected by alternating pressure in the two working cavity. It can cause pitting corrosion damage for gear tooth, and even cause tooth crack and fracture. At first, a three dimension finite element models of the gear pump gear teeth was established. In the start-up process, the gear pump tooth mesh deputy of tooth contact stress strain and dynamic characteristics of gear teeth was analyzed. Obtain the velocity curves, acceleration curve and tooth contact stress and strain dynamic curves of the tooth of gear pump. Providing a new analysis method for gear pump of gear Structure design and having a practical application value.

Bullet physics library is an open source, professional physics library which does the 3D collision detection, applies laws of physics on the rigid bodies and performs the rigid body and soft body dynamics. It is used in games, movies for simulating the rigid bodies according to the laws of physics. Bullet uses the inbuilt feature for continuous tracking and updating the world transform of the colliding and the moving object. The main aim of the paper is utilization of GPU for visual effects through bullet physics.GPU computing is the use of a GPU (graphics processing unit) together with a CPU to accelerate general-purpose scientific and engineering applications [2]. CPU in association with GPU proves to be powerful combination as CPU contains optimized cores for serial processing while GPU consist of 100s of cores which can be used for parallel computation. GPU can act as an accelerator for compute intensive processing by offloading those tasks on to GPU [1].In this paper we intent to harness this unused processing power of the GPU for performing the complex graphics operations as well as the compute intensive operations of the bullet physics library. An application is developed using shaders for running it on the graphics processing unit and integrate the bullet physics library into it. The GPU used for this process is Nvidia graphics card, Quadro NVS 295. Finally, the code is ported onto the Pandaboard and Snowball for ensuring it's compatibility with the orly platform.

The solution of large sparse systems of linear constraints is at the base of most interactive solvers for physically-based animation of soft body dynamics. We focus on applications with hard and tight per-frame resource budgets, such as video games, where the solution of soft body dynamics needs to be computed in a few milliseconds. Linear iterative methods are preferred in these cases since they provide approximate solutions within a given error tolerance and in a short amount of time. We present a parallel randomized Gauss-Seidel method which can be effectively employed to enable the animation of 3D soft objects discretized as large and irregular triangular or tetrahedral meshes. At the beginning of each frame, we partition the set of equations governing the system using a randomized graph coloring algorithm. The unknowns in the equations belonging to the same partition are independent of each other. Then, all the equations belonging to the same partition are solved at the same time in parallel. Our algorithm runs completely on the GPU and can support changes in the constraints topology. We tested our method as a solver for soft body dynamics within the Projective Dynamics and Position Based Dynamics frameworks. We show how the algorithmic simplicity of this iterative strategy enables great numerical stability and fast convergence speed, which are essential features for physically based animations with fixed and small hard time budgets. Compared to the state of the art, we found our method to be faster and scale better while providing stabler solutions for very small time budgets.

In this paper, we investigate the impact of the deformable bodies on the control algorithms for physically simulated characters. We hypothesize that ignoring the effect of deformable bodies at the site of contact negatively affects the control algorithms, leading to less robust and unnatural character motions. To verify the hypothesis, we introduce a compact representation for an articulated character with deformable soft tissue and develop a practical system to simulate two-way coupling between rigid and deformable bodies in a robust and efficient manner. We then apply a few simple and widely used control algorithms, such as pose-space tracking control, Cartesian-space tracking control, and a biped controller (SIMBICON), to simulate a variety of behaviors for both full-body locomotion and hand manipulation. We conduct a series of experiments to compare our results with the motion generated by these algorithms on a character comprising only rigid bodies. The evaluation shows that the character with soft contact can withstand larger perturbations in a more noisy environment, as well as produce more realistic motion.

Endowing buildings with the capacity for movement and transformation, animated architecture represents the expansion of animation from cinematic and televisual space to real-space environments. A key example of animation in architecture is Oosterhuis.nl's proposal for a new World Trade Center. In line with similar work by fellow Dutch firm NOX, Oosterhuis.nl's Ground Zero embraces animation through references to mobility, liveliness and metamorphosis. It points to the prominence of animated form in contemporary design practice and the ubiquitous use of animation software in the process of architectural design. At the same time, Ground Zero reveals post-9/11 anxieties surrounding the soft and tender flesh of the object world. The author's analysis of Ground Zero's discursive production of life maps crucial changes in our spatial imagination and the politics of form.

Soft materials are not only highly deformable but they also possess rich and diverse body dynamics. Soft body dynamics exhibit a variety of properties, including nonlinearity, elasticity, and potentially infinitely many degrees of freedom. Here we demonstrate that such soft body dynamics can be employed to conduct certain types of computation. Using body dynamics generated from a soft silicone arm, we show that they can be exploited to emulate functions that require memory and to embed robust closed-loop control into the arm. Our results suggest that soft body dynamics have a short-term memory and can serve as a computational resource. This finding paves the way toward exploiting passive body dynamics for control of a large class of underactuated systems., 22 pages, 11 figures; email address corrected

In this chapter, you will change the player character from a rigid object to a soft-body physics object. A soft body is an object whose predetermined shape can bend and flex under the forces applied to it. If the body is also trying to relax back into its predetermined shape, it is often referred to as “jelly” physics—especially if the shape is easily deforming and altogether wobbly. That’s the kind of soft body you’ll create in this chapter.

The paper presents the preliminary implementation of eLaparo4D, an immersive training space designed for videolaparoscopic surgery. This is a low-cost training space which integrates haptic devices with realistic surgery tools and 3D rendering with physically deformable 3D CG models of the human internal organs. The main objective of the eLaparo4D first prototype is to design effective training exercises for medicine students within a realistic scenario of a videolaparoscopic operating room. The simulator is based on a client/server layered architecture in order to act as a sort of data gateway: the hardware is interfaced with the physics 3D engine to obtain real-time performances, with an HTML5-based 3D output visual interface in order to integrate the tracking of operating sessions within a custom training platform.

Deformation of objects geometry in computer graphics has been based on a number of different approaches. Two classes of methods are highlighted: physics-based and geometry-based. Physics-based methods, such as Mass-Spring Damper, Finite Element Method and Point-Associated Finite Field have been applied to model soft tissue. However, they all have difficulties in handling the compromise between physical realism and performance. Such difficulties can comprehend the complexity in setting physical parameters of the object, large computational cost and high complexity in implementation. This work proposes a case study evaluation on the Mass-Spring Damper model. A set of well known physical engines are analyzed, allowing to understand how the implementation decisions influence performance and accuracy. These results are compared with an implementation especially proposed for this study.

Pectus excavatum is the most common congenital deformity of the anterior chest wall, in which an abnormal formation of the rib cage gives the chest a caved-in or sunken appearance. Today, the surgical correction of this deformity is carried out in children and adults through Nuss technic, which consists in the placement of a prosthetic bar under the sternum and over the ribs. Although this technique has been shown to be safe and reliable, not all patients have achieved adequate cosmetic outcome. This often leads to psychological problems and social stress, before and after the surgical correction. This paper targets this particular problem by presenting a method to predict the patient surgical outcome based on pre-surgical imagiologic information and chest skin dynamic modulation. The proposed approach uses the patient pre-surgical thoracic CT scan and anatomical-surgical references to perform a 3D segmentation of the left ribs, right ribs, sternum and skin. The technique encompasses three steps: a) approximation of the cartilages, between the ribs and the sternum, trough b-spline interpolation; b) a volumetric mass spring model that connects two layers - inner skin layer based on the outer pleura contour and the outer surface skin; and c) displacement of the sternum according to the prosthetic bar position. A dynamic model of the skin around the chest wall region was generated, capable of simulating the effect of the movement of the prosthetic bar along the sternum. The results were compared and validated with patient postsurgical skin surface acquired with Polhemus FastSCAN system.

Pectus excavatum is the most common congenital deformity of the anterior chest wall, in which an abnormal formation of the rib cage gives the chest a caved-in or sunken appearance. Today, the surgical correction of this deformity is carried out in children and adults through Nuss technic, which consists in the placement of a prosthetic bar under the sternum and over the ribs. Alth ough this technique has been shown to be safe and reliable, not all patients have achieved adequate cosmetic outcome. This often leads to psyc hological problems and social stress, before and after the surgical correction. This paper targets this particular problem by presenting a method to predict the patient surgical outcome based on pre-surgical imagiologic information and chest skin dynamic modulation. The proposed approach uses the patient pre-surgical thoracic CT scan and anatomical-surg ical references to perform a 3D segmentation of the left ribs, right ribs, sternum and skin. The technique encompasses three steps: a) approximation of the cartilages, between the ribs and the sternum, trough b-spline interpolation; b) a volu metric mass spring model that connects two layers - inner skin layer based on the outer pleura contour and the outer su rface skin; and c) displacement of the sternum according to the prosthetic bar position. A dynamic model of the skin around the chest wall region was generated, capable of simulating the effect of the movement of the prosthetic bar along the sternum. The results were compared and validated with patient postsurgical skin surface acquired with Polhemus FastSCAN system., Fundação para a Ciência e Tecnologia

One of the largest improvements to CINEMA 4D R12 is in the dynamics engine that drives the Rigid and Soft Body dynamics. The relationship between these engines and the MoGraph elements are especially rewarding. Along with checking out the latest and greatest in dynamic simulations, we’ll also take a look at some of the best special effects options in the Hair and Cloth engines as well as CINEMA 4D's particle-effects powerhouse, PyroCluster.

Dynamic modelling of constrained deformable bodies that undergo large rigid body displacements are discussed. Particular attention is focused on finite element formulations. The computer formulation of the joint constraints between deformable bodies are discussed.A decoupled joint-elastic acceleration recursive formulation is also presented.

Though there is much research on physically-based animation of soft bodies, simulating soft body objects in real-time remains challenging problem. This paper presents an algorithm for simulating leaking effects in real-time soft body simulations where fast calculation is priority. To simulate leaking effects in a soft body, geometrical cases of broken springs are defined and an algorithm rearranges the topology of neighbors in which the broken springs are connected. Then, internal forces are applied to surface points to model the leaking effect and deform the soft body. Experiments show that the soft body objects with leaking effects can be realistically simulated at interactive speeds on common hardware.

The implicit approach can be used to efficiently model realistically deformable objects for large constraints such as stiffness or time. In soft bodies with pressure forces, models are composed of mesh points connected by springs and applied with pressure forces. System parameters such as spring constant, damping constant, etc. are defined to describe the behaviors of the deformable objects. Since the simulation of soft bodies with pressure force fails when the constraints are large, this paper proposes the method to solve this problem by using the implicit integration method for soft bodies with particular force. The results show that our method can realistically simulate the soft bodies when large constraints are applied

Publisher Summary This chapter aims to present a brief coverage of the governing equations most widely adopted in the present element methods (DEM) approaches. It assumes that the general reader is familiar with the basics of continuum mechanics, the finite element method (FEM) as well as tensor analysis techniques. It provides Newton's equations of motion for particles. A rigid body characterized by a domain of constant volume and mass does not deform. The distance between any two points in a rigid body remains unchanged. A rigid body is an idealization as all bodies deform under the action of external forces. However, this idealization is acceptable in many rock engineering problems, especially large-scale block movements under low stress conditions. Rigid body dynamics is governed by Newton's law of motion and Euler's rotations of rigid bodies. The equations of motion for the deformable bodies are acceptable descriptions if the ‘small displacement’ assumption is accepted. However, the small deformation or rigid body assumptions are just two extreme cases of uncoupled deformation-motion conditions, and are not necessarily universally valid. Under certain circumstances, deformable bodies may undergo large-scale displacements but have small strains that need to be taken into account. The chapter also presents the basic equations for conductive heat transfer and some key thermal properties.

Real-time simulation for global deformation of soft tissue, using Mass-Spring or traditional finite element method (FEM), is difficult because of the following reasons: (1) The linear elastic model is inappropriate for simulating large deformation for the probably unreasonable distortion; (2) The size of the 3D problem (the number of elements in the Mass-Spring or FEM mesh) is much larger than a 2D issue. In this paper, we propose a novel approach for these 2 problems: (1) deploying a deformable centerline, combined with medial representation method instead of the traditional linear elastic model, to simulate large motion and global deformation of a 3D tube like object; (2) applying a simplified algorithm which reconstructs the soft tissue surface by the medial representation method and reduces the complexity of a 3D problem

Numerous situations are encountered where treatment of the entire system as deformable bodies is neither necessary nor practical. This chapter presents the study of the first class of problems. This class of problems divides itself into two further subclasses: one where it is necessary to include some simple mechanisms of deformation in each body and the second in which the individual bodies have no deformation at all. The first class is called pseudo-rigid body deformational and the second rigid body behavior. This chapter illustrates how such behavior can be described and combined in a finite element system. It considers analysis of systems that are composed of many small bodies, each of which is assumed to undergo large displacements and a uniform deformation. A faceted shape can be constructed directly from a finite element discretization in which the elements are designated as all belonging to a single solid object or the individual bodies can be described by simple geometric forms, such as discs or ellipsoids. The pseudo-rigid body form can be directly extended to rigid bodies by using the polar decomposition on the deformation tensor.

There is an increasing interest in the use of soft technologies for robotic application, however, the lack of advanced sensory motor capabilities is currently a significant limitation. Sensing of soft robots, in particular, is still not fully understood and methods by which a large deformable continuum body can be effectively sensed without loosing the intrinsic soft body dynamics are limited. This paper proposes a novel soft body sensing method, localized differential sensing, whereby the sensing of localized deformation on a large soft structure can be achieved with a pair of strain sensors. The design principles for this method are given. To demonstrate this sensing method Conductive Thermoplastic Elastomer (CTPE) is used for the sensing of deformation of soft body structures. A feasibility study of the approach is also presented, with strain sensors incorporated into the universal gripper to allow detection of grasped objects. © 2017 IEEE.