Distributed coordination for collision avoidance of multiple ships considering ship maneuverability

Over the past two decades, a number of methods have been proposed for solving maritime collision avoidance problems. Most of these works take a single ship's perspective and focus on one-to-one or one-to-many situations. To more complicated many-to-many situations, less attention has been paid. To deal with the many-to-many collision...

Optimizing the joint collision avoidance operations of multiple ships from an overall perspective

Ship collision is the main type of maritime accidents, which causes great losses on human lives and economy, and brings negative impacts to the maritime environment. In crowded waters such as the sea area near a seaport, multiple ships encountering situations happen frequently. While several methods have been proposed for solving multiple...

A forward collision avoidance algorithm based on driver braking behavior

Measuring risk is critical for collision avoidance. The paper aims to develop an online risk level classification algorithm for forward collision avoidance systems. Assuming risk levels are reflected by braking profiles, deceleration curves from critical evasive braking events from the Virginia “100-car” database were first extracted. The...

What is the potential of a bird strike advisory system?

This paper presents a collision avoidance algorithm to prevent bird strikes for aircraft departing from an airport. By using trajectory-information of aircraft and birds, the algorithm predicts potential collisions. Collision avoidance is performed by delaying departing aircraft until they can follow a collision-free trajectory. An...

Model predictive ship collision avoidance based on Q-learning beetle swarm antenna search and neural networks

Real-time collision avoidance with full consideration of ship maneuverability, collision risks and International Regulations for Preventing Collisions at Sea (COLREGs) is difficult in multi-ship encounters. To deal with this problem, a novel method is proposed based on model predictive control (MPC), an improved Q-learning beetle swarm...

Model predictive contouring control for collision avoidance in unstructured dynamic environments

This letter presents a method for local motion planning in unstructured environments with static and moving obstacles, such as humans. Given a reference path and speed, our optimization-based receding-horizon approach computes a local trajectory that minimizes the tracking error while avoiding obstacles. We build on nonlinear model-predictive...

On-board communication-based relative localization for collision avoidance in Micro Air Vehicle teams

To avoid collisions, Micro Air Vehicles (MAVs) flying in teams require estimates of their relative locations, preferably with minimal mass and processing burden. We present a relative localization method where MAVs need only to communicate with each other using their wireless transceiver. The MAVs exchange on-board states (velocity, height,...

Sample efficient learning of path following and obstacle avoidance behavior for Quadrotors

In this letter, we propose an algorithm for the training of neural network control policies for quadrotors. The learned control policy computes control commands directly from sensor inputs and is, hence, computationally efficient. An imitation learning algorithm produces a policy that reproduces the behavior of a supervisor. The supervisor...

Distributed multi-robot formation control in dynamic environments

This paper presents a distributed method for formation control of a homogeneous team of aerial or ground mobile robots navigating in environments with static and dynamic obstacles. Each robot in the team has a finite communication and visibility radius and shares information with its neighbors to coordinate. Our approach leverages both...

Robust collision avoidance for multiple micro aerial vehicles using nonlinear model predictive control

When several Multirotor Micro Aerial Vehicles (MAVs) share the same airspace, reliable and robust collision avoidance is required. In this paper we address the problem of multi-MAV reactive collision avoidance. We employ a model-based controller to simultaneously track a reference trajectory and avoid collisions. Moreover, to achieve a higher...

Model-based systems engineering to design collaborative robotics applications

Novel robot technologies are becoming available to automate more complex tasks, more flexibly, and collaborating with humans. Methods and tools are needed in the automation and robotics industry to develop and integrate this new breed of robotic systems. In this paper, the ISE&PPOOA methodology for Model-Based Systems Engineering is...