Abstract: Custom robotics systems often have complicated dynamics that are difficult to form into an analytical model. Robotics systems are already commonly defined in model configuration files such as URDFand AMBF description files (ADF). These files contain all the dynamics and kinematics information of the robot for simulation purposes. However, there is no straightforward method of using this information for dynamics calculations for use in controllers. We present a dynamics modeling service that can parse model description files and build a robot dynamics model for use by a model-based controller in real-time. This dynamic server takes in a model configuration file and will parse it into a Newton-Euler-based model for fast computation. By wrapping the system using ROS, the dynamics server can be accessed cross-platform and allows for a custom controller that incorporates dynamics of arbitrary robots to be readily implemented. Additionally, a control package is presented that leverages the dynamic server to implement the custom controller. This software architecture enables model-based controllers to be developed for, and evaluated on, different simulation and physical systems.

Shreyas Chandra Sekhar is a Robotics Researcher at Worcester Polytechnic Institute (WPI). His research at WPI focuses on the design and control of medical robots, reinforcement learning, human-robot interaction, and virtual reality. Particularly he is interested in creating self-learning Endoscopic movement of DaVinci robots to provide the best camera view to surgeons. Previously, he was a Principal software architect for multiple start-ups. He is working for Salesforce as a full-time Research Engineer.