Automated guided vehicles (AGVs) have recently acquired a lot of interest in the academic
research field and industry applications due to a variety of advantages, including increased …

Controlling complex tasks in robotic systems, such as circular motion for cleaning or
following curvy lines, can be dealt with using nonlinear vector fields. This article introduces a …

We present hierarchical policy blending as optimal transport (HiPBOT). HiPBOT
hierarchically adjusts the weights of low-level reactive expert policies of different agents by …

Large Language Models (LLMs) present a promising frontier in robotic task planning by
leveraging extensive human knowledge. Nevertheless, the current literature often overlooks …

Efficient and safe multi-agent swarm coordination in environments where humans operate,
such as warehouses, assistive living rooms, or automated hospitals, is crucial for adopting …

In logistics environments, collision avoidance is critical to prevent damage to people, assets
and infrastructure. Whether it is a manual or semi-automated fleet with human drivers, the …

Due to the length of the body, multiple number of wheels and the complexity of controlling, it
is difficult for a multi-axle wheeled robot to avoid obstacles autonomously in narrow space …

Using tactile signal is a natural way to perceive potential dangers and safeguard robots. One
possible method is to use full-body tactile sensors on the robot and perform safety …

The thesis at hand is concerned with robots' navigation in human crowds. Specifically,
methods are developed for planning a mobile robot's local motion between pedestrians, and …

In this work, we present FRTree planner, a novel robot navigation framework that leverages
a tree structure of free regions, specifically designed for navigation in cluttered and unknown …