Circular Formation Control with Collision Avoidance Based on Probabilistic Position

In this paper,we study the circular formation problem for the second-order multi-agent systems in a plane,in which the agents maintain a circular formation based on a probabilistic position.A distributed hybrid control protocol based on a probabilistic position is designed to achieve circular formation stabilization and consensus.In the current framework,the mobile agents follow the following rules:1)the agent must follow a circular trajectory;2)all the agents in the same circular trajectory must have the same direction.The formation control objective includes two parts:1)drive all the agents to the circular formation;2)avoid a collision.Based on Lyapunov methods,convergence and stability of the proposed circular formation protocol are provided.Due to limitations in collision avoidance,we extend the results to LaSalle’s invariance principle.Some theoretical examples and numerical simulations show the effectiveness of the proposed scheme.

A Novel Multi-agent Formation Control Law With Collision Avoidance

In this paper a stable formation control law that simultaneously ensures collision avoidance has been proposed.It is assumed that the communication graph is undirected and connected.The proposed formation control law is a combination of the consensus term and the collision avoidance term(CAT).The first order consensus term is derived for the proposed model,while ensuring the Lyapunov stability.The consensus term creates and maintains the desired formation shape,while the CAT avoids the collision.During the collision avoidance,the potential function based CAT makes the agents repel from each other.This unrestricted repelling magnitude cannot ensure the graph connectivity at the time of collision avoidance.Hence we have proposed a formation control law,which ensures this connectivity even during the collision avoidance.This is achieved by the proposed novel adaptive potential function.The potential function adapts itself,with the online tuning of the critical variable associated with it.The tuning has been done based on the lower bound of the critical variable,which is derived from the proposed connectivity property.The efficacy of the proposed scheme has been validated using simulations done based on formations of six and thirty-two agents respectively.

Local Path Planning and Tracking Control of Vehicle Collision Avoidance System

Automotive collision avoidance technology can effectively avoid the accidents caused by dangerous traffic conditions or driver's manipulation errors.Moreover,it can promote the development of autonomous driving for intelligent vehicle in intelligent transportation.We present a collision avoidance system,which is composed of an evasive trajectory planner and a path following controller.Considering the stability of the vehicle in the conflict-free process,the evasive trajectory planner is designed by polynomial parametric method and optimized by genetic algorithm.The path following controller is proposed to make the car drive along the designed path by controlling the vehicle's lateral movement.Simulation results show that the vehicle with the proposed controller has good stability in the collision process,and it can ensure the vehicle driving in accordance with the planned trajectory at different speeds.The research results can provide a certain basis for the research and development of automotive collision avoidance technology.

Nonlinear control of spacecraft formation flying with disturbance rejection and collision avoidance

A nonlinear controller for disturbances rejection and collision avoidance is proposed for spacecraft formation flying.The formation flying is described by a nonlinear model with the J2 perturbation and atmospheric drag. Based on the theory of the state-dependent Riccati equation（SDRE）, a finite time nonlinear control law is developed for the nonlinear dynamics involved in formation flying. Then, a compensative internal mode（IM） control law is added to eliminate disturbances.These two control laws compose a finite time nonlinear tracking controller with disturbances rejection. Moreover, taking safety requirements into account, the repulsive control law is incorporated in the composite controller to perform collision avoidance manoeuvres. A numerical simulation is presented to demonstrate the effectiveness of the proposed method.Compared to the conventional control method, the proposed method provides better performance in the presence of the obstacles and external disturbances.

Cost-effective distributed FTFC for uncertain nonholonomic mobile robot fleet with collision avoidance and connectivity preservation

In this paper,the fault-tolerant formation control(FTFC)problem is investigated for a group of uncertain nonholonomic mobile robots with limited communication ranges and unpredicted actuator faults,where the communication between the robots is in a directed one-to-one way.In order to guarantee the connectivity preservation and collision avoidance among the robots,some properly chosen performance functions are incorporated into the controller to per-assign the asymmetrical bounds for relative distance and bearing angle between each pair of adjacent mobile robots.Particularly,the resultant control scheme remains at a costeffective level because its design does not use any velocity information from neighbors,any prior knowledge of system nonlinearities or any nonlinear approximator to account for them despite the presence of modeling uncertainties,unknown external disturbances,and unexpected actuator faults.Meanwhile,each follower is derived to track the leader with the tracking errors regarding relative distance and bearing angle subject to prescribed transient and steady-state performance guarantees,respectively.Moreover,all the closed-loop signals are ensured to be ultimately uniformly bounded.Finally,a numerical example is simulated to verify the effectiveness of this methodology.

Multi-spacecraft Intelligent Orbit Phasing Control Considering Collision Avoidance

This paper proposes an intelligent low-thrust orbit phasing control method for multiple spacecraft by simultaneously considering fuel optimization and collision avoidance. Firstly,the minimum-fuel orbit phasing control database is generated by the indirect method associated with the homotopy technique. Then,a deep network representing the minimum-fuel solution is trained. To avoid collision for multiple spacecraft,an artificial potential function is introduced in the collision-avoidance controller. Finally,an intelligent orbit phasing control method by combining the minimum-fuel neural network controller and the collision-avoidance controller is proposed. Numerical results show that the proposed intelligent orbit phasing control is valid for the multi-satellite constellation initialization without collision.

Collision avoidance for a mobile robot based on radial basis function hybrid force control technique

Collision avoidance is always difficult in the planning path for a mobile robot. In this paper, the virtual force field between a mobile robot and an obstacle is formed and regulated to maintain a desired distance by hybrid force control algorithm. Since uncertainties from robot dynamics and obstacle degrade the performance of a collision avoidance task, intelligent control is used to compensate for the uncertainties. A radial basis function （RBF） neural network is used to regulate the force field of an accurate distance between a robot and an obstacle in this paper and then simulation studies are conducted to confirm that the proposed algorithm is effective.

A Situation-Aware Collision Avoidance Strategy for Car-Following

Abstract--In this paper, we discuss how to develop an appropriate collision avoidance strategy for car-following. This strategy aims to keep a good balance between traffic safety and efficiency while also taking into consideration the unavoidable uncertainty of position/speed perception/measurement of vehicles and other drivers. Both theoretical analysis and numerical testing results are provided to show the effectiveness of the proposed strategy. Index Terms--Collision avoidance, safety, traffic efficiency, uncertainty.

Polygon formation of multiple nonholonomic mobile robots with double-level-control collision avoidance scheme

This paper considers a polygon formation control of multiple robots with nonholonomic constraintsenclosing a goal target and double-level-control collision avoidance scheme. Doublelevel-control scheme consisted of upper-level and lower-level controls are proposed for trajectorygeneration and tracking control of multi-robot systems. Both upper-level and lower-levelcontrols operate collision avoidance mechanisms based on potential functions. The proposedcontrol scheme guarantees that the group of robots are kept in the polygon formation and drivento a goal, while avoiding collisions during the travel. Moreover, the designed interaction betweenthe upper- and lower-level controls guarantees that the mobile robots are not trapped in localminima or deadlock case. Experiments of the formation of three-robots are conducted to showthe performance of the mobile robots in accomplishing a polygon formation while achieving thegoal without any collision and no local minima.

Real‑Time Optimal Trajectory Planning for Autonomous Driving with Collision Avoidance Using Convex Optimization

An online trajectory planning method for collision avoidance is proposed to improve vehicle driving safety and comfort simultaneously.The collision-free trajectory for autonomous driving is formulated as a nonlinear optimization problem.A novel approximate convex optimization approach is developed for the online optimal trajectory in both longitudinal and lateral directions.First,a dual variable is used to model the non-convex collision-free constraint for driving safety and is calculated by solving a dual problem of the relative distance between vehicles.Second,the trajectory is further optimized in a model predictive control framework considering the safety.It realizes continuous-time and dynamic feasible motion with collision avoidance.The geometry of object vehicles is described by polygons instead of circles or ellipses in traditional methods.In order to avoid aggressive maneuver in the longitudinal and lateral directions for driving comfort,rates of the acceleration and the steering angle are restricted.The final formulated optimization problem is convex,which can be solved by using quadratic programming solvers and is computationally efficient for online application.Simulation results show that this approach can obtain similar driving performance compared to a state-of-the-art nonlinear optimization method.Furthermore,various driving scenarios are tested to evaluate the robustness and the ability for handling complex driving tasks.

Target-enclosing affine formation control of two-layer networked spacecraft with collision avoidance

This paper addresses a target-enclosing problem for multiple spacecraft systems by proposing a two-layer affine formation control strategy. Compared with the existing methods,the adopted two-layer network structure in this paper is generally directed, which is suitable for practical space missions. Firstly, distributed finite-time sliding-mode estimators and formation controllers in both layers are designed separately to improve the flexibility of the formation control system. By introducing the properties of affine transformation into formation control protocol design,the controllers can be used to track different time-varying target formation patterns. Besides, multilayer time-varying encirclements can be achieved with particular shapes to surround the moving target. In the sequel, by integrating adaptive neural networks and specialized artificial potential functions into backstepping controllers, the problems of uncertain Euler-Lagrange models, collision avoidance as well as formation reconfiguration are solved simultaneously. The stability of the proposed controllers is verified by the Lyapunov direct method. Finally, two simulation examples of triangle formation and more complex hexagon formation are presented to illustrate the feasibility of the theoretical results.

Path planning and stability control of collision avoidance system based on active front steering

Vehicle collision avoidance system is a kind of auxiliary driving system based on vehicle active safety,which can assist the driver to take the initiative to avoid obstacles under certain conditions,so as to effectively improve the driving safety of vehicle.This paper presents a collision avoidance system for an autonomous vehicle based on an active front steering,which mainly consists of a path planner and a robust tracking controller.A path planner is designed based on polynomial parameterization optimized by simulated annealing algorithm,which plans an evasive trajectory to bypass the obstacle and avoid crashes.The dynamic models of the AFS system,vehicle as well as the driver model are established,and based on these,a robust tracking controller is proposed,which controls the system to resist external disturbances and work in accordance with the planning trajectory.The proposed collision avoidance system is testified through CarSim and Simulink combined simulation platform.The simulation results show that it can effectively track the planning trajectory,and improve the steering stability and anti-interference performance of the vehicle.

Active Collision Avoidance System Design Based on Model Predictive Control with Varying Sampling Time

In active collision avoidance,the trajectory tracking controller determines the deviation from the reference path and the vehicle stability.The main objective of this study was to reduce the tracking error and improve the tracking performance in collision avoidance.Unlike the previously proposed model predictive control(MPC)strategies with constant sampling time,an improved MPC controller with varying sampling time based on the hierarchical control framework was proposed in this paper.Compared with the original MPC tracking controller,the improved MPC controller demonstrated better adaptive capability for the varying road adhesion coefficients and vehicle speed on a curved road.The simulation results revealed that the hierarchical control framework generated an optimal trajectory for collision avoidance in real-time by minimizing the potential field energy.

Fixed-time position coordinated tracking control for spacecraft formation flying with collision avoidance

In this paper,the fixed-time stability of spacecraft formation reconfiguration(position tracking)is studied.Firstly,a novel nonsingular terminal sliding mode surface is designed and based on which a fixed-time coordinated controller is designed to keep the closed-loop system states have a finite settling time bounded by some predefined constants.Secondly,another nonsingular terminal sliding mode surface is designed by combining the artificial potential function and the aforementioned sliding surface,which meets the mutual distance constraint during transition process among spacecraft when it is bounded.Then another coordinated controller with fixed-time observer considering mutual distance constraint is presented,which guarantees the closed-loop system states stable also in bounded settling time.Finally,simulation results are shown to validate the correctness of the proposed theorems.It is worth mentioning that the control schemes also work even though there is a properly limit on the control input.

Periodic event-triggered formation control for multi-UAV systems with collision avoidance

In this paper,periodic event-triggered formation control problems with collision avoidance are studied for leader–follower multiple Unmanned Aerial Vehicles(UAVs).Firstly,based on the Artificial Potential Field(APF)method,a novel sliding manifold is proposed for controller design,which can solve the problem of collision avoidance.Then,the event-triggered strategy is applied to the distributed formation control of multi-UAV systems,where the evaluation of the event condition is continuous.In addition,the exclusion of Zeno behavior can be guaranteed by the inter-event time between two successive trigger events have a positive lower bound.Next,a periodic event-triggered mechanism is developed for formation control based on the continuous eventtriggered mechanism.The periodic trigger mechanism does not need additional hardware circuits and sophisticated sensors,which can reduce the control cost.The stability of the control system is proved by the Lyapunov function method.Finally,some numerical simulations are presented to illustrate the effectiveness of the proposed control protocol.

Using improved particle swarm optimization to tune PID controllers in cooperative collision avoidance systems

The introduction ofproportional-integral-dorivative （PID） controllers into cooperative collision avoidance systems （CCASs） has been hindered by difficulties in their optimization and by a lack of study of their effects on vehicle driving stability, comfort, and fuel economy. In this paper, we propose a method to optimize PID controllers using an improved particle swarm optimization （PSO） algorithm, and to bettor manipulate cooperative collision avoidance with other vehicles. First, we use PRESCAN and MATLAB/Simulink to conduct a united simulation, which constructs a CCAS composed of a PID controller, maneuver strategy judging modules, and a path planning module. Then we apply the improved PSO algorithm to optimize the PID controller based on the dynamic vehicle data obtained. Finally, we perform a simulation test of performance before and after the optimization of the PID controller, in which vehicles equipped with a CCAS undertake deceleration driving and steering under the two states of low speed （≤50 km/h） and high speed （≥100 km/h） cruising. The results show that the PID controller optimized using the proposed method can achieve not only the basic functions of a CCAS, but also improvements in vehicle dynamic stability, riding comfort, and fuel economy.

Finite-time adaptive formation control for multi-agent systems with uncertainties under collision avoidance and connectivity maintenance

In this paper,the problem of adaptive finite time formation control is investigated for double integrator multi-agent systems with uncertainties.Firstly,considering the multi-agent systems with uncertain dynamic reference and external bounded disturbance,a distributed adaptive estimator control algorithm is designed to realize formation tracking control in finite-time.It is important that the collision avoidance and maintaining connectivity of the multi-agent systems are realized by constructing an effective potential function based on distance constraints.On the other hand,the problem of formation production control for the double integrator systems is discussed with desired formation shape in finite-time.Achieving four control objectives is the main contributions in all the phases,including the estimation of uncertainties,collision avoidance,connectivity maintenance,and finite-time convergence.Finally,an application example of the formation production control is presented to verify accuracy of the proposed theoretical method.

A Scalable Adaptive Approach to Multi-Vehicle Formation Control with Obstacle Avoidance

This paper deals with the problem of distributed formation tracking control and obstacle avoidance of multivehicle systems(MVSs)in complex obstacle-laden environments.The MVS under consideration consists of a leader vehicle with an unknown control input and a group of follower vehicles,connected via a directed interaction topology,subject to simultaneous unknown heterogeneous nonlinearities and external disturbances.The central aim is to achieve effective and collisionfree formation tracking control for the nonlinear and uncertain MVS with obstacles encountered in formation maneuvering,while not demanding global information of the interaction topology.Toward this goal,a radial basis function neural network is used to model the unknown nonlinearity of vehicle dynamics in each vehicle and repulsive potentials are employed for obstacle avoidance.Furthermore,a scalable distributed adaptive formation tracking control protocol with a built-in obstacle avoidance mechanism is developed.It is proved that,with the proposed protocol,the resulting formation tracking errors are uniformly ultimately bounded and obstacle collision avoidance is guaranteed.Comprehensive simulation results are elaborated to substantiate the effectiveness and the promising collision avoidance performance of the proposed scalable adaptive formation control approach.

A survey of safety separation management and collision avoidance approaches of civil UAS operating in integration national airspace system

Recent years have witnessed a booming of the industry of civil Unmanned Aircraft System(UAS).As an emerging industry,the UAS industry has been attracting great attention from governments of all countries and the aviation industry.UAS are highly digitalized,informationized,and intelligent;therefore,their integration into the national airspace system has become an important trend in the development of civil aviation.However,the complexity of UAS operation poses great challenges to the traditional aviation regulatory system and technical means.How to prevent collisions between UASs and between UAS and manned aircraft to achieve safe and efficient operation in the integrated operating airspace has become a common challenge for industry and academia around the world.In recent years,the international community has carried out a great amount of work and experiments in the air traffic management of UAS and some of the key technologies.This paper attempts to make a review of the UAS separation management and key technologies in collision avoidance in the integrated airspace,mainly focusing on the current situation of UAS Traffic Management(UTM),safety separation standards,detection system,collision risk prediction,collision avoidance,safety risk assessment,etc.,as well as an analysis of the bottlenecks that the current researches encountered and their development trends,so as to provide some insights and references for further research in this regard.Finally,this paper makes a further summary of some of the research highlights and challenges.

Distributed robust MPC for nonholonomic robots with obstacle and collision avoidance

Considering that the inevitable disturbances and coupled constraints pose an ongoing challenge to distributed control algorithms,this paper proposes a distributed robust model predictive control(MPC)algorithm for a multi-agent system with additive external disturbances and obstacle and collision avoidance constraints.In particular,all the agents are allowed to solve optimization problems simultaneously at each time step to obtain their control inputs,and the obstacle and collision avoidance are accomplished in the context of full-dimensional controlled objects and obstacles.To achieve the collision avoidance between agents in the distributed framework,an assumed state trajectory is introduced for each agent which is transmitted to its neighbors to construct the polyhedral over-approximations of it.Then the polyhedral over-approximations of the agent and the obstacles are used to smoothly reformulate the original nonconvex obstacle and collision avoidance constraints.And a compatibility constraint is designed to restrict the deviation between the predicted and assumed trajectories.Moreover,recursive feasibility of each local MPC optimization problem with all these constraints derived and input-to-state stability of the closed-loop system can be ensured through a sufficient condition on controller parameters.Finally,simulations with four agents and two obstacles demonstrate the efficiency of the proposed algorithm.