Collision avoidance

About: Collision avoidance is a research topic. Over the lifetime, 8014 publications have been published within this topic receiving 111414 citations.

Coordinated Maneuvering of Automated Vehicles in Platoons

Abstract: To eventually have automated vehicles operate in platoons, it is necessary to study what information each vehicle must have and to whom it must communicate for safe and efficient maneuvering in all possible conditions. This paper formulates the problem in terms of sensing and communicated information. By emulating platoons using a group of mobile robots, the authors demonstrate the feasibility of maneuvers (such as entering, exiting, and recuperating from an accident) using different distributed coordination strategies. The coordination strategies studied range from no communication to unidirectional or bidirectional exchanges between vehicles and to fully centralized decision by the leading vehicle. One particularity of this paper is that instead of assuming that the platoon leader or all vehicles globally monitor what is going on, only the vehicles involved in a particular maneuver are concerned, distributing decisions locally among the platoon. This paper reports experimental trials using robots having limited and directional perception of other things, using vision and obstacle avoidance sensing. Results confirm the feasibility of the coordination strategies in different conditions and various uses of communicated information to compensate for sensing limitations

COLREG-RRT: An RRT-Based COLREGS-Compliant Motion Planner for Surface Vehicle Navigation

Abstract: Motion planning for autonomous surface vehicles (ASVs) is challenging since surface vessels are nonlinear underactuated kinodynamic systems with often large inertia. Thus, ASV planners must identify long-term trajectories in order to avoid guiding the ASV into inevitable collision states. Furthermore, maritime vessels are required to follow COLlision REGulationS (COLREGS), which dictate collision avoidance patterns. Current state-of-the-art methods are based on model predictive control (MPC) and assume that other vessels move at constant velocities without the consideration of COLREGS. In this letter, we propose COLREG-RRT, an RRT-based planner capable of identifying long-term, COLREGS-compliant trajectories with a high navigation success rate. This is achieved by conducting joint forward simulations of both the ASV and the other vessels during RRT growth in order to anticipate future collisions. The COLREGS-compliance is enforced by constructing virtual obstacles that inhibit tree growth. We demonstrate COLREGS-compliance in single-ship encounters and compare against two state-of-the-art methods in multiship encounters with up to 20 other vessels. Experiments indicate that COLREG-RRT has a 32% higher success rate and is real-time capable in the most difficult environment tested. Additionally, COLREG-RRT identifies longer trajectories, as compared to MPC. This property aids with collision avoidance with other ships.

External Wrench Estimation, Collision Detection, and Reflex Reaction for Flying Robots

Abstract: Flying in unknown environments may lead to unforeseen collisions, which may cause serious damage to the robot and/or its environment. In this context, fast and robust collision detection combined with safe reaction is, therefore, essential and may be achieved using external wrench information. Also, deliberate physical interaction requires a control loop designed for such a purpose and may require knowledge of the contact wrench. In principle, the external wrench may be measured or estimated. Whereas measurement poses large demands on sensor equipment, additional weight, and overall system robustness, in this paper we present a novel model-based method for external wrench estimation in flying robots. The algorithm is based on the onboard inertial measurement unit and the robot's dynamics model only. We design admittance and impedance controllers that use this estimate for sensitive and robust physical interaction. Furthermore, the performance of several collision detection and reaction schemes is investigated in order to ensure collision safety. The identified collision location and associated normal vector located on the robot's convex hull may then be used for sensorless tactile sensing. Finally, a low-level collision reflex layer is provided for flying robots when obstacle avoidance fails, also under wind influence. Our experimental and simulation results show evidence that the methodologies are easily implemented and effective in practice.

A "divide and conquer" strategy based on situations to achieve reactive collision avoidance in troublesome scenarios

Abstract: This paper addresses reactive collision avoidance for robots that move in arduous environments (i.e., very dense, complex and cluttered). To achieve this goal, the technique simplifies the difficulty of the navigation by a divide and conquer strategy, which is based on identifying navigational situations and applying the corresponding motion laws. The state of the art in reactive navigation still presents classic limitations such as trap situations due to U-shape obstacles, difficulty to achieve motion among very close obstacles, to obtain oscillation-free and stable motion, to move over directions far from the goal direction or towards the obstacles, or to tune the heuristic or internal parameters. This paper presents a method that overcomes all these limitations. As a result, navigation with this method is successfully achieved in scenarios where existing techniques present a high degree of difficulty to navigate. Outstanding navigation results are reported using a wheelchair vehicle. A discussion and comparison with existing techniques is provided.

A three-layered architecture for real time path planning and obstacle avoidance for surveillance USVs operating in harbour fields

Abstract: The use of unmanned vehicles in the field of underwater and marine applications is increasing significantly in recent years. Autonomous vehicles (like AUVs and gliders) or teleoperated ones (like ROVs) are currently employed for executing a number of different underwater tasks, like inspecting submerged pipes, executing maintenance interventions on underwater gas- or oil-platforms, collecting environmental or oceanographic data, performing surveys on sites of archeological interest. In parallel with the development of underwater vehicles, unmanned surface vehicles (USVs), are they also witnessing an increasing interest from the robotic community, especially with the goal of performing surveillance applications, like patrolling and maintaining safeguarded against intruders harbours or other “crucial” sites. The potential benefits offered by automated vessels equipped with sensors such as cameras or sonars are quite evident, since they could be used to quickly identify the level of menace of unknown radar track without exposing any human operators to possible threats. However USVs, unlike in the underwater case, have to face the problem of avoiding other vessels which in most cases are manned ones. This is a crucial point especially in that kind of application, where the automated vessel has to move quickly towards a possible menace while at the same time avoiding all the other boats normally operating in the harbour area. Unfortunately, at the current state of art, a reliable methodology to avoid the other vessels and the availability of effective and accurate obstacle detection sensors is still missing. This paper focus its attention on the case of USV used for security applications within a harbour, devising a solution that can be real-time implemented for the obstacle avoidance problem under critical situations where the vehicle as to reach its target as fast as possible while guaranteeing the safety of the other vessels. The presented solution is based on a three layered hierarchical architecture: the first layer computes a global path taking into account static obstacles known a priori, the second layer modifies this path in a locally optimal way (under certain assumptions) exploiting kinematic data of the moving obstacles, while the last layer reactively avoids obstacles for which such data is not available. The paper will be therefore organized as follows: in the first section an introduction and state of art are presented, in the successive section the work will discuss the first layer and the methods for the static obstacles avoidance, while in the third the paper will focus on the moving obstacles and the proposed avoidance algorithm, while also presenting many different detailed simulation results regarding the performances achievable by the overall architecture. Finally a concluding section will also indicate some still open problems and future work directions to be developed.