Safe and Efficient Motion Planning for Material Transportation Robots considering Intention Prediction of Obstacles

To effectively address labor shortages in construction sites, material transportation robots, a type of construction robots, need to be both safe and efficient. In environments where robots and workers share the same space, motion planning algorithms that consider only the static environment may operate in a way that is inefficient and dangerous. In this work, motion planning is carried out with reference to the prediction of the obstacle movement intentions, thus avoiding unnecessary obstacle avoidance behaviors. We implemented our approach on a robot in a simulated environment and demonstrated that it can successfully navigate efficiently and safely in dynamic and complex construction environments.