Collision avoidance system

About: Collision avoidance system is a research topic. Over the lifetime, 1788 publications have been published within this topic receiving 23667 citations.

Development and operation of the Traffic Alert and Collision Avoidance System (TCAS)

Abstract: The authors describe the development of the Traffic Alert and Collision Avoidance System (TCAS), provide a description of the TCAS II system operation, offer results of operational evaluations conducted in cooperation with Piedmont, United, and Northwest Airlines, and outline the status and progress of the TCAS implementation. In recent years, the TCAS effort has focused on concepts that make use of the radar transponders carried by aircraft for ground air traffic control purposes. A transponder-based collision avoidance system can provide immediate protection against the vast population of aircraft already equipped with either the current Air Traffic Control Radar Beacon System (ATCRBS) transponder or the new Mode S transponder. The TCAS concept encompasses a range of capabilities, including TCAS I, which provides traffic advisories (bearing, range, and relative altitude) to assist the pilot in visually acquiring the threat aircraft; TCAS II, which provides traffic and resolution advisories (recommended escape maneuvers) in the vertical plane; and TCAS III, which provides traffic and resolution advisories in both the vertical and horizontal planes. >

Intelligent Ocean Navigation and Fuzzy-Bayesian Decision/Action Formulation

Abstract: This paper focuses on the formulation of a decision-action execution model that can facilitate intelligent collision avoidance features in ocean navigation systems, while respecting the Convention on the International Regulations for Preventing Collisions at Sea (COLREGs) rules and regulations of collision avoidance. The decision/action process in this work consists of a fuzzy-logic-based parallel decision-making (PDM) module whose decisions are formulated into sequential actions by a Bayesian-network-based module. Therefore, the paper presents a collision avoidance system (CAS) that is capable of making multiple parallel collision avoidance decisions regarding several target vessel collision conditions, and those decisions are executed as sequential actions to avoid complex collision situations in ocean navigation.

Model Predictive Trajectory Tracking and Collision Avoidance for Reliable Outdoor Deployment of Unmanned Aerial Vehicles

Abstract: We propose a novel approach for optimal trajectory tracking for unmanned aerial vehicles (UAV), using a linear model predictive controller (MPC) in combination with non-linear state feedback. The solution relies on fast onboard simulation of the translational dynamics of the UAV, which is guided by a linear MPC. By sampling the states of the virtual UAV, we create a control command for fast non-linear feedback, which is capable of performing agile maneuvers with high precision. In addition, the proposed pipeline provides an interface for a decentralized collision avoidance system for multi-UAY scenarios. Our solution makes use of the long prediction horizon of the linear MPC and allows safe outdoors execution of multi-UAV experiments without the need for in-advance collision-free planning. The practicality of the tracking mechanism is shown in combination with priority-based collision resolution strategy, which performs sufficiently in experiments with up to 5 UAVs. We present a statistical and experimental evaluation of the platform in both simulation and real-world examples, demonstrating the usability of the approach.

Multi-robot collision avoidance with localization uncertainty

Abstract: This paper describes a multi-robot collision avoidance system based on the velocity obstacle paradigm. In contrast to previous approaches, we alleviate the strong requirement for perfect sensing (i.e. global positioning) using Adaptive Monte-Carlo Localization on a per-agent level. While such methods as Optimal Reciprocal Collision Avoidance guarantee local collision-free motion for a large number of robots, given perfect knowledge of positions and speeds, a realistic implementation requires further extensions to deal with inaccurate localization and message passing delays. The presented algorithm bounds the error introduced by localization and combines the computation for collision-free motion with localization uncertainty. We provide an open source implementation using the Robot Operating System (ROS). The system is tested and evaluated with up to eight robots in simulation and on four differential drive robots in a real-world situation.