Exploring Active Inference and Model Predictive Path Integral Control: A Journey from Low-Level Commands to Task and Motion Planning

In an ever-evolving society, the demand for autonomous robots equipped with human-level capabilities is becoming increasingly imperative. Various factors, such as an aging population and a shortage of labor for repetitive and physically demanding tasks, have underscored the need for capable autonomous robots to assist us in our daily activities....

Scalarizing Multi-Objective Robot Planning Problems Using Weighted Maximization

When designing a motion planner for autonomous robots there are usually multiple objectives to be considered. However, a cost function that yields the desired trade-off between objectives is not easily obtainable. A common technique across many applications is to use a weighted sum of relevant objective functions and then carefully adapt the...

Multi-Modal MPPI and Active Inference for Reactive Task and Motion Planning

Task and Motion Planning (TAMP) has progressed significantly in solving intricate manipulation tasks in recent years, but the robust execution of these plans remains less touched. Particularly, generalizing to diverse geometric scenarios is still challenging during execution. In this work, we propose a reactive TAMP method to deal with...

Search-based task and motion planning for hybrid systems: Agile autonomous vehicles

To achieve optimal robot behavior in dynamic scenarios we need to consider complex dynamics in a predictive manner. In the vehicle dynamics community, it is well know that to achieve time-optimal driving on low friction surface, the vehicle should utilize drifting. Hence, many authors have devised rules to split circuits and employ drifting...

SpaTiaL: monitoring and planning of robotic tasks using spatio-temporal logic specifications

Many tasks require robots to manipulate objects while satisfying a complex interplay of spatial and temporal constraints. For instance, a table setting robot first needs to place a mug and then fill it with coffee, while satisfying spatial relations such as forks need to placed left of plates. We propose the spatio-temporal framework SpaTiaL...

Integrated Task Assignment and Path Planning for Capacitated Multi-Agent Pickup and Delivery

Multi-agent Pickup and Delivery (MAPD) is a challenging industrial problem where a team of robots is tasked with transporting a set of tasks, each from an initial location and each to a specified target location. Appearing in the context of automated warehouse logistics and automated mail sortation, MAPD requires first deciding which robot is...