SUMMARY

Robust and flexible behavior generation for robot task execution remains a difficult problem due to the wide variety of constraints, disturbances, and uncertainties present in the environment. Behavior Trees (BTs) have emerged as a powerful Control Architecture for reliable and flexible autonomous action execution that is capable of authoring complicated logic. More specifically, BTs can execute high level actions based on a tree of composed primitive policies to accomplish a task. This thesis examines the design of two unified robot frameworks that integrate BTs as a robust middleware between high-level decision making as well as low-level motion planning and control. Firstly, a framework for legged locomotion with disturbance rejection is proposed, which incorporates model based trajectory optimization for motion primitive generation and a hybrid dynamic tracking controller for bipedal stability. Each node of the BT is integrated as a single walking step that can be sequentially combined for multi-step locomotion plans with robustness to disturbances. A high level decision maker, Linear Temporal Logic with reactive synthesis, is then used to automatically generate scalable actions with the understanding of potential disturbances. Secondly, a manipulation framework was designed that incorporates a variety of motion primitives with a supporting perception framework for solving generic manipulation problems. At the task planning level, the ROS2 PlanSys2 architecture was used to generate a plan based on BTs and solve multi-step plans. Assembly and disassembly tasks are specifically demonstrated using pick, place, alignment, locking, unlocking, insertion, removal, and many other action primitives for the maintenance of industrial and aerospace environments.