A RealTime Dynamic Simulator and an Associated FrontEnd Representation Format for Simulating Complex Robots and Environments Robot Dynamic Simulators offer convenient implementation and testing of physical robots, thus accelerating research and development. While existing simulators support most realworld robots with serially linked kinematic and dynamic chains, they offer limited or conditional support for complex closedloop robots. On the other hand, many of the underlying physics computation libraries that these simulators employ support closedloop kinematic chains and redundant mechanisms. Such mechanisms are often utilized in surgical robots to achieve constrained motions (e.g., the remote center of motion (RCM)). To deal with such robots, we propose a new simulation framework based on a frontend description format and a robust realtime dynamic simulator. Although this study focuses on surgical robots, the proposed format and simulator are applicable to any type of robot. In this manuscript, we describe the philosophy and implementation of the frontend description format and demonstrate its performance and the simulatorxe2x80x99s capabilities using simulated models of realworld surgical robots.

An Asynchronous MultiBody Simulation Framework for RealTime Dynamics, Haptics and Learning with Application to Surgical Robots Surgical robots for laparoscopy consist of several patient side slave manipulators that are controlled via surgeon operated master telemanipulators. Commercial surgical robots do not perform any subtasks xe2x80x93 even of repetitive or noninvasive nature xe2x80x93 autonomously or provide intelligent assistance. While this is primarily due to safety and regulatory reasons, the state of such automation intelligence also lacks the reliability and robustness for use in highrisk applications. Recent developments in continuous control using Artificial Intelligence and Reinforcement Learning have prompted growing research interest in automating mundane subtasks. To build on this, we present an inspired Asynchronous Framework which incorporates realtime dynamic simulation xe2x80x93 manipulable with the masters of a surgical robot and various other input devices xe2x80x93 and interfaces with learning agents to train and potentially allow for the execution of shared subtasks. The scope of this framework is generic to cater to various surgical (as well as nonsurgical) training and control applications. This scope is demonstrated by examples of multiuser and multimanual applications which allow for realistic interactions by incorporating distributed control, shared task allocation and a welldefined communication pipeline for learning agents. These examples are discussed in conjunction with the design philosophy, specifications, systemarchitecture and metrics of the Asynchronous Framework and the accompanying Simulator. We show the stability of Simulator while achieving realtime dynamic simulation and interfacing with several haptic input devices and a training agent at the same time.