Unified robot task and motion planning with extended planner using ROS simulator

Safe and efficient exploration of unknown and unstructured environments is critical for an autonomous mobile robot in high-dimensional workspace. Autonomous exploration is essential to safely and robustly build a complete and accurate path in an environment map with obstacles. Task planning tends to find a sequence of discrete actions in solving the symbolic problems. Motion planning finds the optimal path by avoiding the geometric obstacles in the environment. Fusion of these two approaches is advantageous in finding a path in unknown environments. This paper presents a hybrid path planning approach, termed RobMAP (Robotic Motion and Action Planning) for achieving efficient navigation by performing desired tasks in a sequence and thereby generate the optimal path in a large- scale indoor environment. In achieving this, action-planning is done using Planning Domain Definition Language (PDDL) planner through ROSPlan framework and collision-free path is generated using sampling-based Rapidly exploring Random Tree (RRT) algorithm. The ROSPlan system is used in less constrained workspace and it estimates the optimized information gain in exploring each action. Further, the integration of these two methods leads to an intelligent motion planner that searches for an optimal path towards a goal based on the PDDL action planner specification. Extensive experimentation is performed using Robot Operating System (ROS) controlled Rviz tool on a synthetic indoor environment by executing a sequence of actions specified using PDDL. The Turtlebot is equipped with a laser sensor and it explores the environment map with higher precision and accuracy in finding the optimal path. The demonstrated results corroborate that the proposed method of integrating RRT with PDDL provides optimal solutions with lesser path length in much lesser run time. The accuracy, precision and coverage area are higher when compared with other exploration strategies used in the existing work.