Abstract: Simulation of complex agents, such as robots with many articulation links, can be performed utilizing a pre-computed a response matrix for each link. When an impulse is applied to a link for this agent, the response matrix for a root node can be used to determine an impact of that impulse on the root node, as well as changes in velocity for any direct child node. This process can be performed recursively for each link down to the leaf links of a hierarchical agent structure. These response matrices can be solved recursively from root to leaf while only visiting each hierarchical link once. Such an approach can be used to solve a full set of constraints acting on the agent in an amount of time per solver iteration that is on the order of the number of links, or O(N) time per solver iteration.

Abstract: Systems and methods herein address scalable contact-rich simulation in physics engines using one or more processing units to simulate movement between at least two objects in a simulation, the movement based at least on a plurality of sets of reduced points obtained from an iterative reduction using one or more threshold criteria, the iterative reduction applied to a plurality of points associated with at least one contact between the depictions.

Abstract: Systems and methods herein address momentum conservation in physics engines using one or more processing units to simulate an articulated body based at least on an adjustment to a velocity that is associated with a root link of the articulated body, and using at least a change in momentum determined from one or more external forces separately from a change in momentum determined from one or more internal forces to conserve momentum within the system.

Abstract: Modeling contact between two or more objects (such as a robotic arm placing a block on a stack of blocks) or articulations of a series of linked joints (such as modeling a backhoe) in a real-time computing application can introduce additional energy into the system or fail to resolve a constraint imposed on the system. Current techniques attempt to resolve these issues, for example, by using very small time steps. Very small time steps, however, can significantly increase computational costs of the modeling simulation. The introduced simulation techniques for rigid bodies use a time interval to reduce linearization artifacts due to the small time steps and reduce computational costs with faster solver convergence by permitting more efficient bias calculations. High mass handling can also be improved through the more efficient bias calculations.

Abstract: In modeling contact between two or more objects (such as a robotic arm placing a block on a stack of blocks) or articulations of a series of linked joints (such as modeling a backhoe), current techniques can introduce additional energy into the system or fail to resolve a constraint imposed on the system. The current techniques attempt to resolve these issues, for example, by using very small time steps. Very small time steps, however, can significantly increase computational costs of the modeling simulation. The disclosed simulation system for rigid bodies uses a time interval to reduce linearization artifacts due to the small time steps and reduce computational costs with faster solver convergence by permitting more efficient bias calculations. High mass handling can also be improved through the more efficient bias calculations.

Abstract: In modeling contact between two or more objects (such as a robotic arm placing a block on a stack of blocks) or articulations of a series of linked joints (such as modeling a backhoe), current techniques can introduce additional energy into the system or fail to resolve a constraint imposed on the system. The current techniques attempt to resolve these issues, for example, by using very small time steps. Very small time steps, however, can significantly increase computational costs of the modeling simulation. The disclosed simulation system for rigid bodies uses a time interval to reduce linearization artifacts due to the small time steps and reduce computational costs with faster solver convergence by permitting more efficient bias calculations. High mass handling can also be improved through the more efficient bias calculations.

Abstract: A method for implementing a hybrid scalable CPU/GPU rigid body pipeline. The method includes partitioning a rigid body pipeline into a GPU portion comprising GPU components and a CPU portion comprising CPU components. The method further includes executing the GPU components on the GPU of a computer system, and executing the CPU components on the CPU of the computer system. Communication data dependencies between the CPU and the GPU are managed as the GPU components and the CPU components process through the GPU and the CPU. The method concludes by outputting a resulting processed frame for display.

Abstract: A method for implementing a hybrid scalable CPU/GPU rigid body pipeline. The method includes partitioning a rigid body pipeline into a GPU portion comprising GPU components and a CPU portion comprising CPU components. The method further includes executing the GPU components on the GPU of a computer system, and executing the CPU components on the CPU of the computer system. Communication data dependencies between the CPU and the GPU are managed as the GPU components and the CPU components process through the GPU and the CPU. The method concludes by outputting a resulting processed frame for display.