相关论文: Improving the Modularity of AUV Control Systems us…

Autonomous underwater vehicles (AUVs) are valuable for ocean exploration due to their flexibility and ability to carry communication and detection units. Nevertheless, AUVs alone often face challenges in harsh and extreme sea conditions.…

We propose a hybrid combination of active inference and behavior trees (BTs) for reactive action planning and execution in dynamic environments, showing how robotic tasks can be formulated as a free-energy minimization problem. The proposed…

This paper presents a modular software architecture that enables environmental-aware coordination of heterogeneous Autonomous Underwater Vehicles (AUVs) to improve underwater acoustic connectivity. The architecture combines a Robot…

Safety-critical Autonomous Systems require trustworthy and transparent decision-making process to be deployable in the real world. The advancement of Machine Learning introduces high performance but largely through black-box algorithms. We…

This study presents a novel environment-aware reinforcement learning (RL) framework designed to augment the operational capabilities of autonomous underwater vehicles (AUVs) in underwater environments. Departing from traditional RL…

Behavior Trees (BTs) are becoming a popular tool to model the behaviors of autonomous agents in the computer game and the robotics industry. One of the key advantages of BTs lies in their composability, where complex behaviors can be built…

Robotic assistance in robot arm teleoperation tasks has recently gained a lot of traction in industrial and domestic environment. A wide variety of input devices is used in such setups. Due to the noise in the input signals (e.g., Brain…

Recently, there have been numerous advances in the development of biologically inspired lightweight Micro Aerial Vehicles (MAVs). While autonomous navigation is fairly straight-forward for large UAVs as expensive sensors and monitoring…

Modern autonomous underwater vehicles (AUVs) have advanced sensing capabilities including sonar, cameras, acoustic communication, and diverse bio-sensors. Instead of just sensing its environment and storing the data for post-Mission…

Modular Aerial Robotic Systems (MARS) consist of multiple drone units assembled into a single, integrated rigid flying platform. With inherent redundancy, MARS can self-reconfigure into different configurations to mitigate rotor or unit…

We consider the problem of designing scalable and portable controllers for unmanned aerial vehicles (UAVs) to reach time-varying formations as quickly as possible. This brief confirms that deep reinforcement learning can be used in a…

Transformer-based architectures have shown remarkable performance in vision and language tasks but pose unique challenges for safety-critical applications. This paper presents a conceptual framework for integrating Transformers into…

Modularity in military vehicle designs enables on-base assembly, disassembly, and reconfiguration of vehicles, which can be beneficial in promoting fleet adaptability and life cycle cost savings. To properly manage the fleet operation and…

This paper addresses the trajectory planning for multiple autonomous underwater vehicles (AUVs) in strong waves that can disturb the AUVs' trajectory tracking ability and cause obstacle and inter-vehicle collisions. A novel approach based…

In this paper, we show how Behavior Trees that have performance guarantees, in terms of safety and goal convergence, can be extended with components that were designed using machine learning, without destroying those performance guarantees.…

In dynamic operational environments, particularly in collaborative robotics, the inevitability of failures necessitates robust and adaptable recovery strategies. Traditional automated recovery strategies, while effective for predefined…

The underwater Unmanned Vehicles(UUVs) are pivot tools for offshore engineering and oceanographic research. Most existing UUVs do not facilitate easy integration of new or upgraded sensors. A solution to this problem is to have a modular…

In this work, we present an approach to supervisory reinforcement learning control for unmanned aerial vehicles (UAVs). UAVs are dynamic systems where control decisions in response to disturbances in the environment have to be made in the…

This paper presents a hybrid route-path planning model for an Autonomous Underwater Vehicle's task assignment and management while the AUV is operating through the variable littoral waters. Several prioritized tasks distributed in a large…

Despite a slow neuromuscular system, humans easily outperform modern robot technology, especially in physical contact tasks. How is this possible? Biological evidence indicates that motor control of biological systems is achieved by a…