On the use of simulation in robotics: Opportunities, challenges, and suggestions for moving forward.

The last five years marked a surge in interest for and use of smart robots, which operate in dynamic and unstructured environments and might interact with humans. We posit that well-validated computer simulation can provide a virtual proving ground that in many cases is instrumental in understanding safely, faster, at lower costs, and more thoroughly how the robots of the future should be designed and controlled for safe operation and improved performance. Against this backdrop, we discuss how simulation can help in robotics, barriers that currently prevent its broad adoption, and potential steps that can eliminate some of these barriers. The points and recommendations made concern the following simulation-in-robotics aspects: simulation of the dynamics of the robot; simulation of the virtual world; simulation of the sensing of this virtual world; simulation of the interaction between the human and the robot; and, in less depth, simulation of the communication between robots. This Perspectives contribution summarizes the points of view that coalesced during a 2018 National Science Foundation/Department of Defense/National Institute for Standards and Technology workshop dedicated to the topic at hand. The meeting brought together participants from a range of organizations, disciplines, and application fields, with expertise at the intersection of robotics, machine learning, and physics-based simulation.

Simulation of surface strain in tibiofemoral cartilage during walking for the prediction of collagen fiber orientation.

The collagen fibers in the superficial layer of tibiofemoral articular cartilage exhibit distinct patterns in orientation revealed by split lines. In this study, we introduce a simulation framework to predict cartilage surface loading during walking to investigate if split line orientations correspond with principal strain directions in the cartilage surface. The two-step framework uses a multibody musculoskeletal model to predict tibiofemoral kinematics which are then imposed on a deformable surface model to predict surface strains. The deformable surface model uses absolute nodal coordinate formulation (ANCF) shell elements to represent the articular surface and a system of spring-dampers and internal pressure to represent the underlying cartilage. Simulations were performed to predict surface strains due to osmotic pressure, loading induced by walking, and the combination of both loading due to pressure and walking. Time-averaged magnitude-weighted first principal strain directions agreed well with split line maps from the literature for both the osmotic pressure and combined cases. This result suggests there is indeed a connection between collagen fiber orientation and mechanical loading, and indicates the importance of accounting for the pre-strain in the cartilage surface due to osmotic pressure.

Dynamics of scattering in undulatory active collisions.

Natural and artificial self-propelled systems must manage environmental interactions during movement. In complex environments, these interactions include active collisions, in which propulsive forces create persistent contacts with heterogeneities. Due to the driven and dissipative nature of these systems, such collisions are fundamentally different from those typically studied in classical physics. Here we experimentally and numerically study the effects of active collisions on a laterally undulating sensory-deprived robophysical model, whose dynamics are relevant to self-propelled systems across length scales and environments. Interactions with a single rigid post scatter the robot, and this deflection is dominated by head-post contact. These results motivate a model which reduces the snake to a circular particle with two key features: The collision dynamics are set by internal driving subject to the geometric constraints of the post, and the particle has an effective length equal to the wavelength of the snake. Interactions with a single row of evenly spaced posts (with interpost spacing d) produce distributions reminiscent of far-field diffraction patterns: As d decreases, distinct secondary peaks emerge as large deflections become more likely. Surprisingly, we find that the presence of multiple posts does not change the nature of individual collisions; instead, multimodal scattering patterns arise from multiple posts altering the likelihood of individual collisions to occur. As d decreases, collisions near the leading edges of the posts become more probable, and we find that these interactions are associated with larger deflections. Our results, which highlight the surprising dynamics that can occur during active collisions of self-propelled systems, can inform control principles for locomotors in complex terrain and facilitate design of task-capable active matter.

Quasicontinuum-like reduction of density functional theory calculations of nanostructures.

Density functional theory can accurately predict chemical and mechanical properties of nanostructures, although at a high computational cost. A quasicontinuum-like framework is proposed to substantially increase the size of the nanostructures accessible to simulation. It takes advantage of the near periodicity of the atomic positions in some regions of nanocrystalline materials to establish an interpolation scheme for the electronic density in the system. The electronic problem embeds interpolation and coupled cross-domain optimization techniques through a process called electronic reconstruction. For the optimization of nuclei positions, computational gains result from explicit consideration of a reduced number of representative nuclei and interpolating the positions of the rest of nuclei following the quasicontinuum paradigm. Numerical tests using the Thomas-Fermi-Dirac functional demonstrate the validity of the proposed framework within the orbital-free density functional theory.

Efficient Computation of Cartilage Contact Pressures within Dynamic Simulations of Movement.

The objective of this study was to assess the use of an advanced collision detection algorithm to simulate cartilage contact pressure patterns within dynamic musculoskeletal simulations of movement. We created a knee model that included articular cartilage contact for the tibiofemoral and patellofemoral joints. Knee mechanics were then predicted within the context of a dynamic gait simulation. At each time step of a simulation, ray-casting was used in conjunction with hierarchical oriented bounding boxes (OBB) to rapidly identify regions of overlap between articulating cartilage surfaces. Local cartilage contact pressure was then computed using an elastic foundation model. Collision detection implemented in parallel on a GPU provided up to a 10× speed increase when using high resolution mesh densities that had >10 triangles/mm2. However, pressure magnitudes converged at considerably lower mesh densities (2.6 triangles/mm2) where CPU and GPU implementations of collision detection exhibited equivalent performance. Simulated tibiofemoral contact locations were comparable to prior experimental measurements, while pressure magnitudes were similar to those predicted by finite element models. We conclude the use of ray-casting with hierarchical OBB for collision detection is a viable method for simulating joint contact mechanics in human movement.

Compliant contact versus rigid contact: A comparison in the context of granular dynamics.

We summarize and numerically compare two approaches for modeling and simulating the dynamics of dry granular matter. The first one, the discrete-element method via penalty (DEM-P), is commonly used in the soft matter physics and geomechanics communities; it can be traced back to the work of Cundall and Strack [P. Cundall, Proc. Symp. ISRM, Nancy, France 1, 129 (1971); P. Cundall and O. Strack, Geotechnique 29, 47 (1979)GTNQA80016-850510.1680/geot.1979.29.1.47]. The second approach, the discrete-element method via complementarity (DEM-C), considers the grains perfectly rigid and enforces nonpenetration via complementarity conditions; it is commonly used in robotics and computer graphics applications and had two strong promoters in Moreau and Jean [J. J. Moreau, in Nonsmooth Mechanics and Applications, edited by J. J. Moreau and P. D. Panagiotopoulos (Springer, Berlin, 1988), pp. 1-82; J. J. Moreau and M. Jean, Proceedings of the Third Biennial Joint Conference on Engineering Systems and Analysis, Montpellier, France, 1996, pp. 201-208]. The DEM-P and DEM-C are manifestly unlike each other: They use different (i) approaches to model the frictional contact problem, (ii) sets of model parameters to capture the physics of interest, and (iii) classes of numerical methods to solve the differential equations that govern the dynamics of the granular material. Herein, we report numerical results for five experiments: shock wave propagation, cone penetration, direct shear, triaxial loading, and hopper flow, which we use to compare the DEM-P and DEM-C solutions. This exercise helps us reach two conclusions. First, both the DEM-P and DEM-C are predictive, i.e., they predict well the macroscale emergent behavior by capturing the dynamics at the microscale. Second, there are classes of problems for which one of the methods has an advantage. Unlike the DEM-P, the DEM-C cannot capture shock-wave propagation through granular media. However, the DEM-C is proficient at handling arbitrary grain geometries and solves, at large integration step sizes, smaller problems, i.e., containing thousands of elements, very effectively. The DEM-P vs DEM-C comparison is carried out using a public-domain, open-source software package; the models used are available online.