Abstract: Distributed optimization provides a framework for deriving distributed algorithms for a variety of multi-robot problems. This tutorial constitutes the first part of a two-part series on ...

Abstract: The book situates itself in a unique niche “between proportional-integral-derivative (PID) and model predictive control (MPC),” as a compromise between the tradeoffs and advantages of each.

The RRT* path planner is implemented in C++ and generates Dubins paths using geometric primitives. To achieve self-balancing locomotion, TASER is trained using reinforcement learning with Isaac Lab ...