Area coverage is an important problem in robotics applications, which has been widely used
in search and rescue, offshore industrial inspection, and smart agriculture. This paper …

Autonomous pedestrian-aware navigation in shared human-robot environments is a
challenging problem. Here we consider a common situation in which a large crowd of …

We present a novel approach for risk-aware planning with human agents in multi-agent
traffic scenarios. Our approach takes into account the wide range of human driver behaviors …

This dissertation addressed many key problems in autonomous driving towards handling
dense, heterogeneous, and unstructured traffic environments. Autonomous vehicles (AV) at …

Human-robot collaboration (HRC) based on speed and separation monitoring should
consider the difference of risk factors in the scene; otherwise, the sudden invasion of non …

This paper proposes a formulation for the risk-aware path planning problem which utilizes
multi-objective optimization to dynamically plan trajectories that satisfy multiple complex …

Cooperative multi-agent systems make it possible to employ miniature robots in order to
perform different experiments for data collection in wide open areas to physical interactions …

Path planning in complex environments remains a challenging task for unmanned vehicles.
In this paper, we propose a decoupled path-planning algorithm with the help of a deep …

By utilizing only depth information, the paper introduces a novel two-stage planning
approach that enhances computational efficiency and planning performances for …

Effective path planning is crucial for autonomous mobile robots navigating complex
environments. The “global–local” coupled path planning algorithm exhibits superior global …