Formation control for multi-robot systems with collision avoidance

In this paper, distributed formation is studied for a team of mobile robots including leaders and followers. Followers are able to sense the relative displacements to neighbouring followers and all of the leaders, and the leaders can be sensed by the followers. Based on such assumption of sensing, distributed formation control scheme is designed, under which both followers team and leaders team are fully independent. The followers and leaders have exchangeable roles within their own group. The leaders can have an arbitrary formation, and around the leaders, the followers need to reach a regular polygon formation with a suitable orientation. Distributed control laws and localised collision avoidance algorithms are designed for each follower, and they use only local displacements. Speed and acceleration sensors are avoided. As the leaders and the followers are independent and exchangeable, both robot teams are scalable and robust against member failures and system delays.     

一种基于效益的多机器人避碰协调策略

多移动机器人系统在完成同时定位和地图构建SLAM任务时,机器人之间常常存在相互碰撞的问题,而这种碰撞的避免又不同于一般的避障,因为避障问题中的障碍物一般是不动的。为了解决机器人之间的避碰问题,提出了一种基于效益的多机器人避碰协调策略。该策略以提高多机器人系统探索效率为主,确定机器人通过交叉路口的顺序。同时考虑了动态协调避碰的情况,给出了确定机器人通过交叉路口顺序的算法。通过机器人在交叉路口实现避碰协调算法的仿真示例,对该方法的避碰协调过程进行了说明,并对仿真结果进行了分析,同时对仿真中机器人和目标位置的空间关系给出了合理的假设。     

Imperfect in-vehicle collision avoidance warning systems can aid drivers

An experiment was conducted to determine the effects of an in-vehicle collision avoidance warning system (IVCAWS) on driver performance. A driving simulator was driven by 135 licensed drivers. Of these, 120 received alerts from the IVCAWS when their headway to a lead car was less than 2 s, and the other 15 (the control group) received no alerts. Drivers received varied alert interfaces: auditory, visual, and multimodal. The system had varied levels of reliability, determined by both false alarm rate and failure of the IVCAWS to alert to short headway. Results indicated that the IVCAWS led to safer (longer) headway maintenance. High false alarm rates induced drivers to slow down unnecessarily; large numbers of missed alerts did not have any significant impact on drivers. Driver acceptance of the system was mixed. Interface played a role in driver reliance on the system, with the multimodal interfaces generating least reliance. Actual or potential applications of this research include IVCAWS interface selection for greater system efficacy and user acceptance and the advisability of implementation, even of imperfect systems, for drivers who seek to maintain a safer headway.     

Distributed cooperative reinforcement learning for multi-agent system with collision avoidance

In this work, we present an optimal cooperative control scheme for a multi-agent system in an unknown dynamic obstacle environment, based on an improved distributed cooperative reinforcement learning (RL) strategy with a three-layer collaborative mechanism. The three collaborative layers are collaborative perception layer, collaborative control layer, and collaborative evaluation layer. The incorporation of collaborative perception expands the perception range of a single agent, and improves the early warning ability of the agents for the obstacles. Neural networks (NNs) are employed to approximate the cost function and the optimal controller of each agent, where the NN weight matrices are collaboratively optimized to achieve global optimal performance. The distinction of the proposed control strategy is that cooperation of the agents is embodied not only in the input of NNs (in a collaborative perception layer) but also in their weight updating procedure (in the collaborative evaluation and collaborative control layers). Comparative simulations are carried out to demonstrate the effectiveness and performance of the proposed RL-based cooperative control scheme.     

基于多智能体深度强化学习的船舶协同避碰策略

船舶避碰是智能航行中首要解决的问题,多船会遇局面下,只有相互协作,共同规划避碰策略,才能有效降低碰撞风险.为使船舶智能避碰策略具有协同性、安全性和实用性,提出一种基于多智能体深度强化学习的船舶协同避碰决策方法.首先,研究船舶会遇局面辨识方法,设计满足《国际海上避碰规则》的多船避碰策略.其次,研究多船舶智能体合作方式,构建多船舶智能体协同避碰决策模型:利用注意力推理方法提取有助于避碰决策的关键数据;设计记忆驱动的经验学习方法,有效积累交互经验;引入噪音网络和多头注意力机制,增强船舶智能体决策探索能力.最后,分别在实验地图与真实海图上,对多船会遇场景进行仿真实验.结果表明,在协同性和安全性方面,相较于多个对比方法,所提出的避碰策略均能获得具有竞争力的结果,且满足实用性要求,从而为提高船舶智能航行水平和保障航行安全提供一种新的解决方案.     

Fuzzy collision avoidance system for ships

The paper discusses the problem of maritime traffic control. A model of the relative motion of two vessels is considered. An algorithm for the generation of alarms of various types in accordance with the verbal ship–ship danger level is considered. Navigation situations are separated into levels based on the ship’s maneuvering intensity and time to collision. A fuzzy decision-making system about the motion’s danger level that combines Mamdani and Sugeno fuzzy inference systems is proposed. The results of the numerical experiment that demonstrates the system’s operation under standard conditions and the results of the system’s field tests based on real ship traffic data in the waters adjacent to the port of Vladivostok are given.     

Proportional navigation-based collision avoidance for UAVs

A collision avoidance algorithm for unmanned aerial vehicles (UAVs) based on the conventional proportional navigation (PN) guidance law is investigated. The proportional navigation guidance law being applied to a wide range of missile guidance problems is tailored to the collision avoidance of UAVs. This can be accomplished by guiding the relative velocity vector of the aircraft to a vector connecting the current aircraft position to the safety boundary of the target aircraft. Stability of the proposed algorithm is also studied using the circle criterion. The stability condition can be established by choosing the navigation coefficient within a certain bound. The guidance law is extended to 3-dimensional maneuver problems. Inherent simplicity and robustness of the PN guidance law provides satisfactory collision avoidance performance with different initial conditions. Recommended by Editorial Board member Sangdeok Park under the direction of Editor Hyun Seok Yang. This research was performed for the Smart UAV Development Program, one of 21st Century Frontier R&D Programs funded by the Ministry of Science and Technology of Korea. Su-Cheol Han received the B.S. degree from Korea Airforce Academy, Korea, in 1997, and the M.S. degree from Korea Advanced Institute of Science and Technology, Korea, in 2005. At present, he is serving as a pilot in Korea Airforce. His research interests are UAV guidance and control, especially collision avoidance. Hyochoong Bang received the B.S. and M.S. degrees in aeronautical engineering from Seoul National University in 1985 and 1987, respectively. He also received the Ph.D. degree in 1992 from Texas A&M University. From 1992 to 1994, he worked as a Research Assistant Professor at the U.S. Naval Postgraduate School (NPS) conducting spacecraft attitude control research. From 1995 to 1999, he worked for Korea Aerospace Research Institute. Since 2001 he has been a Professor at Korea Advanced Institute of Science and Technology. His current research interest include spacecraft attitude control, spacecraft guidance, UAV guidance and control. Chang-Sun Yoo received the B.S. degree from Korea Aerospace University, Korea, in 1987, the M.S. degree from Korea Advanced Institute of Science and Technology, Korea, in 1991 and the Ph.D. degree from Chungnam National University, Korea, in 2003. Since 1991, he has been a Research Engineer in Korea Aerospace Research Institute, Korea. His research interests are flight simulation, flight control system, inertial and GPS navigation.     

CSMA with collision avoidance

Advances in local area networking have allowed users to run many different applications on one system. Users are now asking for greater access, more functions, more power and greater reliability. This requires that the system tasks should be distributed, and means that the interconnection system used should be highly reliable; ‘passive’, so that no failed component can bring the entire system down; support high through-put; and operate on low-cost cable. This paper describes a broadband transmission system based on a single, passive coaxial cable which detects possible collisions before the data is sent. Examples of two remote stations and two adjacent stations competing for transmission are given, along with performance comparisons of CSMA/CD and CSMA/CA.     

Distributed reactive collision avoidance

The work contained in this paper concerns a novel approach to the n-vehicle collision avoidance problem. The vehicle model used here allows for three-dimensional movement and represents a wide range of vehicles. The algorithm works in conjunction with any desired controller to guarantee all vehicles remain free of collisions while attempting to follow their desired control. This algorithm is reactive and distributed, making it well suited for real time applications, and explicitly accounts for actuation limits. A robustness analysis is presented which provides a means to account for delays and unmodeled dynamics. Robustness to an adversarial vehicle is also presented. Results are demonstrated in simulation.     

Maximum-miss aircraft collision avoidance

Aircraft densities in terminal areas increase each year, and the risk of collision grows proportionally. The maintenance of clearance between aircraft in this environment sometimes calls for evasive maneuvers, which depend on the relative position and relative velocity of two aircraft. In this study, small-amplitude maneuvers are found for either or both aircraft in near-miss configurations. Using practical low-order dynamics, individual maneuvers are found that maximize the miss distance. These optimal maneuvers combine longitudinal (speed) and normal (lift) accelerations. The signs of the accelerations of both aircraft depend on their magnitudes. An evasive climb maneuver, for example, becomes a dive maneuver if the acceleration amplitude exceeds a certain value. The maximum-miss maneuvers appear to have practical potential, because they can be determined on-line from estimated position data for both aircraft, without consideration of detailed inertial and aerodynamic properties of the aircraft. Recommended by H. Stalford     

Control and optimization in a collision avoidance problem in oscillating systems

The development of control algorithms, including optimal control ones, in the collision avoidance problem for a system of two pendulums with a controllable common base is considered. Two problems are solved. The first one searches for the law of variation of the bounded control force that makes the system move from its initial state of rest to the given final state of rest during a finite time and ensures the pendulums do not collide in the process of oscillatory motions. The second problem searches for the performance-optimal law of variation of acceleration of the base and the bounded force that generates the acceleration. The algorithms for constructing the sought controls that use Kalman controllability conditions and Pontryagin’s maximum principle method are presented. The dynamics of the system involved is simulated for the constructed control laws. The numerical results of both problems are compared to find that implementation of the developed performance-optimal control algorithm can help significantly decrease the releasing time of the pendulums while preventing a possible collision.     

Multisensory in-car warning signals for collision avoidance

OBJECTIVE: A driving simulator study was conducted in order to assess the relative utility of unimodal auditory, unimodal vibrotactile, and combined audiotactile (i.e., multisensory) in-car warning signals to alert and inform drivers of likely front-to-rear-end collision events in a situation modeled on real-world driving. BACKGROUND: The implementation of nonvisual in-car warning signals may have important safety implications in lessening any visual overload during driving. Multisensory integration can provide synergistic facilitation effects. METHOD: The participants drove along a rural road in a car-following scenario in either the presence or absence of a radio program in the background. The brake light signals of the lead vehicle were also unpredictably either enabled or disabled on a trial-by-trial basis. RESULTS: The results showed that the participants initiated their braking responses significantly more rapidly following the presentation of audiotactile warning signals than following the presentation of either unimodal auditory or unimodal vibrotactile warning signals. CONCLUSION: Multisensory warning signals offer a particularly effective means of capturing driver attention in demanding situations such as driving. APPLICATION: The potential value of such multisensory in-car warning signals is explained with reference to recent cognitive neuroscience research.     

A user-centred approach for designing driving support systems: the case of collision avoidance

The work described in this paper is focused on an approach for implementing in real working contexts the guidelines of user-centred design contained in formal standards and in many research studies. The application concerns the EUCLIDE project (enhanced human–machine interface for on vehicle integrated driving support system), which aimed at developing a driving support system to avoid collisions with obstacles in reduced visibility conditions. The design of the system followed a user-centred approach which started by identifying the model of cognition to be applied throughout the whole design process. The definition of the warning strategies of the system was firstly analysed with the aim to achieve the highest balance between a totally supportive system and a non-disturbing system. Then an initial set of design solutions for the human–machine interface was tested in a static driving simulator. A second set of possible interfaces was evaluated in a dynamic simulator before developing a final design. This solution was implemented in two real vehicles and tested in real traffic situations. This paper describes the whole design process and concentrates on the final step of “in-vehicle” integration process. The road tests performed at the end of the whole process are discussed in detail focusing on the safety implications associated with the design solution finally selected and implemented.

基于防碰撞的移动SAN 对分布参数系统的控制

在考虑移动执行器动力学行为和防碰撞的条件下,研究在控制分布参数系统过程中执行器的移动策略。移动传感-执行器网络中的传感器对分布参数系统进行测量,由执行器对空间分布过程执行相应的控制信号以控制分布参数系统。基于Lyapunov稳定性理论,对每个执行器设计一种新的移动策略,实现每个移动执行器对分布参数系统的协同控制,并保证各移动执行器之间不会发生碰撞。仿真实例表明了所提出方法的有效性。     

Formal verification and simulation for platform screen doors and collision avoidance in subway control systems

For hybrid systems, hybrid automata-based tools are capable of verification, while Matlab Simulink/Stateflow is proficient in simulation. We propose a co-verification procedure, in which the verification tool SpaceEx/PHAVer and simulation tool Matlab are integrated to analyze and verify hybrid systems. For the application of this procedure, a platform screen door system (PSDS, a subsystem of the subway control system), is modeled with hybrid automata and Simulink/Stateflow charts, respectively. The models of PSDS are simulated by Matlab and verified by SpaceEx/PHAVer. The simulation and verification results indicate that the sandwiched situation can be avoided under time interval conditions. We improve the model with four trains and four stations on a subway line and analyze the urgent control scenario for the safety distance requirement. In this paper, the Simulink/Stateflow model is a refinement of the SpaceEx/PHAVer model, which is closer to a final implementation. Moreover, the two models are complementary for some features (e.g.,visualization of simulation, correctness proving by verification), stressing different aspects of the overall system and permitting complementary analysis techniques, i.e., verification versus simulation. We conclude that this integration procedure is competent in verifying subway control systems.     

Decision support system for collision avoidance of vessels

Although there are many advanced systems to assist vessels with passing through narrow waterways, it continues to be a serious problem because of disturbance factors and geographic structure. By taking Istanbul Strait as a model for this study, we aimed to develop a decision support system and/or a guidance method to assist reciprocally passing vessels. The main purpose is to develop an Artificial Neural Network (ANN) that uses the data of manually controlled vessels to generate predictions about the future locations of those vessels. If there is any possibility of collision, this system is aimed to warn the operators in the Vessel Traffic Services (VTS) centre and to guide the personnel of the vessels. In this study, manually controlled and reciprocally passing vessels’ data were used (including coordinates, speed, and environmental conditions), neural networks were trained, and predictions were made about the locations of vessels three minutes after the initial point of evaluation (this duration was determined by considering the conditions of Istanbul Strait). With this purpose, we used data gathered from vessels and proved the success of the system, especially concerning predictions made during turnings, by determining the possibility of collision between two vessels three minutes after the data was gathered.     

Spacecraft formation reconfiguration with collision avoidance

In this paper we present a behavioral control solution for reconfiguration of a spacecraft formation using the Null-Space Based (NSB) concept. The solution is task based, and aims to reconfigure and maintain a rigid formation while avoiding collisions between spacecraft. A model of relative translation is derived, together with a passivity-based sliding surface controller which globally stabilizes the equilibrium point of the closed-loop system. The NSB control method is implemented by giving each task different priorities and then calculating desired velocity and a Jacobian matrix for each spacecraft and each task. The velocity vector for each task is then projected into the null-space for higher prioritized tasks to remove conflicting velocity components. Simulation results are presented, showing that each spacecraft moves into the predefined formation without breaking any rules for the higher priority tasks, and all collisions are avoided.     

面向车辆防撞的车底阴影检测方法

为解决常用车底阴影检测方法在复杂光照及背景条件下检测结果不稳定的问题,提出一种基于聚类分析的车底阴影检测方法。使用改进的高斯混合模型聚类算法对交通图像中的目标,即路面、车道线、车辆、车底阴影进行聚类,利用高斯阴影模型的均值与方差自适应阈值分割图像,提取路面与车底阴影的交线,利用阴影的几何结构特征对检测到的阴影线进行两次合并,得到最终结果。实验结果表明,该方法能有效检测车底阴影,适应白天不同时段、光强变化,在复杂投影的干扰下能实现准确检测。     

Modeling pedestrian flow accounting for collision avoidance during evacuation

Collision avoidance behavior has become an open challenging problem since it is one of critical factors that influence the pedestrian flow dynamics. In this paper, a cellular automaton (CA) model is developed to depict the pedestrian movements when collision avoidance behaviors exist during evacuation. Then, we utilize the proposed model to simulate the influences of the collision avoidance on the pedestrian movements during the evacuation in a classroom with two exits. The numerical results indicate that more collision avoidance behaviors have negative influences on the evacuation efficiency, and that more competition behaviors generate more collisions while have no prominent positive impacts on the evacuation efficiency. Moreover, the evacuation time increases with the decreasing number of aisles in the classroom and the number of collisions increases with the increasing number of parts in the classroom divided by aisles. The above results are helpful to develop effective evacuation strategies and design the internal layouts of buildings.