基于伪谱法的编队卫星队形重构防碰撞轨迹优化

提出了基于伪谱法的编队卫星队形重构最优轨迹规划方法.首先,应用Legendre伪谱法将队形重构问题离散化为非线性规划问题;然后,通过庞特里亚金极小值原理计算出不考虑碰撞规避问题时各星最优轨迹的解析形式,并由此计算出各星间的碰撞点;最后,在碰撞点附近设置符合高斯分布的测试点,进一步避免各星在配置点间发生碰撞.仿真结果表明,应用所提出方法得到的队形重构的最优轨迹能够较好地满足各种约束条件,计算精度高、速度快,使得编队卫星自主重构成为可能.     

An efficient system for combined route traversal and collision avoidance

Here we consider the problem of a robot that must follow a previously designated path outdoors. While the nominal path, a series of closely spaced via points, is provided with an assurance that it will lead to the destination, we can’t be guaranteed that it will be obstacle free. We present an efficient system capable of both following the path as well as being perceptive and agile enough to avoid obstacles in its way. We present a system that detects obstacles using laser ranging, as well as a layered system that continuously tracks the path, avoiding obstacles and replanning the route when necessary. The distinction of this system is that compared to the state of the art, it is minimal in sensing and computation while achieving high speeds. In this paper, we present an algorithm that is based on models of obstacle avoidance by humans and show variations of the model to deal with practical considerations. We show how the parameters of this model are automatically learned from observation of human operation and discuss limitations of the model. We then show how these models can be extended by adding online route planning and a formulation that allows for operation at varying speeds. We present experimental results from an autonomous vehicle that has operated several hundred kilometers to validate the methodology.

Robust sliding-mode formation control and collision avoidance via repulsive vector fields for a group of Quad-Rotors

This paper is focused on solving the collision avoidance problem for a group of Quad-Rotors which are affected by external disturbances when they are moving in a horizontal plane by means of Repulsive Vector Fields (RVFs). The RVFs are included in an attractive potential function control strategy, that allows the Quad-Rotors to reach the desired position in a geometric pattern, together with a Continuous Sliding-Mode Control (C-SMC) strategy based on Sliding-Mode Observers (SMOs) that are used to estimate, in a finite-time, the linear and angular velocities, respectively. For this purpose, a parameter, which depends on the distance among the Quad-Rotors and their velocities, is designed in order to scale the RVFs properly. In this sense, the repulsion force will be proportional to the velocity and acceleration of the Quad-Rotor when it detects any obstacle. A RVF not properly scaled may result in a collision or a Quad-Rotor movement far away from its desired position. The combination between the C-SMC strategy, the SMOs, the attractive potential functions and the RVFs robustly solves the formation control and avoidance collision problem under the presence of disturbances. Numerical simulations illustrate the performance of the RVFs when the Quad-Rotors are in risk of collision.     

Potential-based obstacle avoidance in formation control

Based on the double integrator mathematic model, a new kind of potential function is presented in this paper by referring to the concepts of the electric field; then a new formation control method is proposed, in which the potential functions are used between agent-agent and between agent-obstacle, while state feedback control is applied for the agent and its goal. This strategy makes the whole potential field simpler and helps avoid some local minima. The stability of this combination of potential functions and state feedback control is proven. Some simulations are presented to show the rationality of this control method.     

Autonomous quadrotor flight with vision-based obstacle avoidance in virtual environment

In this paper, vision-based autonomous flight with a quadrotor type unmanned aerial vehicle (UAV) is presented. Automatic detection of obstacles and junctions are achieved by the use of optical flow velocities. Variation in the optical flow is used to determine the reference yaw angle. Path to be followed is generated autonomously and the path following process is achieved via a PID controller operating as the low level control scheme. Proposed method is tested in the Google Earth® virtual environment for four different destination points. In each case, autonomous UAV flight is successfully simulated without observing collisions. The results show that the proposed method is a powerful candidate for vision based navigation in an urban environment. Claims are justified with a set of experiments and it is concluded that proper thresholding of the variance of the gradient of optical flow difference have a critical effect on the detectability of roads having different widths.     

Formation control for multiquadrotor aircraft: Connectivity preserving and collision avoidance

In this article, we investigate the formation control problem of multiquadrotor aircraft system subject to connectivity preservation and collision avoidance. First, based on the backstepping design method, a novel formation control algorithm is developed to enable multiquadrotor aircraft to move along the desired trajectory while becoming the predefined formation pattern. Meanwhile, the connectivity of the communication network is maintained and the collision among multiquadrotor is avoided. Second, for each quadrotor's desired attitude obtained by the formation controller, an improved finite‐time attitude tracking law is designed to guarantee that the desired attitude can be tracked by the real attitude in a fast finite time. Finally, a numerical example is given to demonstrate the effectiveness of the proposed algorithms.     

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.     

Improving collision avoidance for mobile robots in partially known environments: the beam curvature method

This paper presents a new approach to obstacle avoidance for mobile robots in cluttered and unknown or partially unknown environments. The method combines a new directional method, called beam method (BM), to improve the performance of a local obstacle avoidance approach called curvature velocity method (CVM). BM calculates the best one-step heading which is used by CVM to obtain the optimal linear and angular velocities. The resulting combined technique is called beam curvature method (BCM).

Different experiments in populated and dynamic environments have proved to be very successful. The method is able to guide the robot safely and efficiently during long time periods. We present some of these results compared with other methods.     

Fuzzy neural networks for obstacle pattern recognition and collision avoidance of fish robots

The problems of detection and pattern recognition of obstacles are the most important concerns for fish robots’ path planning to make natural and smooth movements as well as to avoid collision. We can get better control results of fish robot trajectories if we obtain more information in detail about obstacle shapes. The method employing only simple distance measuring IR sensors without cameras and image processing is proposed. The capability of a fish robot to recognize the features of an obstacle to avoid collision is improved using neuro-fuzzy inferences. Approaching angles of the fish robot to an obstacle as well as the evident features such as obstacles’ sizes and shape angles are obtained through neural network training algorithms based on the scanned data. Experimental results show the successful path control of the fish robot without hitting on obstacles.     

多移动机器人的领航-跟随编队避障控制

针对多移动机器人的编队控制问题,提出了一种结合Polar Histogram避障法的领航-跟随协调编队控制算法。该算法在领航-跟随l-φ编队控制结构的基础上引入虚拟跟随机器人,将编队控制转化为跟随机器人对虚拟跟随机器人的轨迹跟踪控制。结合移动机器人自身传感器技术,在简单甚至复杂的环境下为机器人提供相应的路径运动策略,实现实时导航的目的。以两轮差动Qbot移动机器人为研究对象,搭建半实物仿真平台,进行仿真实验。仿真结果表明:该方法可以有效地实现多移动机器人协调编队和避障控制。     

On-line collision avoidance system for two PTP command-based manipulators with distributed controller

This research aims to solve online collision avoidance problem of two manipulators with independent controller. Since industrial robot controller is a closed commercial system, trajectory generation part of robot controlling is always proprietary or unknown. Thus, this paper proposes a collision avoidance system of two manipulators which are controlled by point-to-point (PTP) commands, in condition that the internal of robot controller is unknown and unchangeable. Based on this condition, collision avoidance is supposed to be realized by online scheduling of these PTP controlling commands. This paper proposes the collision avoidance method that assumes the three-dimensional common workspace between two manipulators can be partitioned into many subregion elements. And with managing these subregion elements, which are occupied by robot motion, PTP commands are scheduled to adjust execution timing for collision avoidance. A deadlock problem caused by the partition of the workspace is also taken into consideration in the method. And the effectiveness and efficiency of the method have been verified by simulations and experiments.     

Smooth continuous transition between tasks on a kinematic control level: Obstacle avoidance as a control problem

Kinematically redundant robots allow simultaneous execution of several tasks with different priorities. Beside the main task, obstacle avoidance is one commonly used subtask. The ability to avoid obstacles is especially important when the robot is working in a human environment. In this paper, we propose a novel control method for kinematically redundant robots, where we focus on a smooth, continuous transition between different tasks. The method is based on a new and very simple null-space formulation. Sufficient conditions for the tasks design are given using the Lyapunov-based stability discussion. The effectiveness of the proposed control method is demonstrated by simulation and on a real robot. Pros and cons of the proposed method and the comparison with other control methods are also discussed.     

A bounded distributed connectivity preserving aggregation strategy with collision avoidance property

This paper presents a bounded connectivity preserving control strategy for the aggregation of multi-agent systems. The problem is investigated for two cases of single-integrator agents and unicycles. Under the proposed control strategy, if two agents are in the connectivity range at some point in time, they will stay connected thereafter. The agents finally aggregate while avoiding collision in such a way that the average of the distances between every pair of neighboring agents is bounded by a pre-specified positive real number, which can be chosen arbitrarily small. The results are developed based on some important characteristics of the positive limit set of the closed-loop system under the proposed control strategy and a fundamental property of convex real functions. The theoretical results are verified by simulation.     

Lyapunov function-based obstacle avoidance scheme for a two-wheeled mobile robot

An obstacle avoidance scheme of a two-wheeled mobile robot is shown by selecting an appropriate Lya- punov function. When considering the obstacle, the Lyapunov function may have some local minima. A method which erases the local minima is proposed by using a function which covers the minima with a plane surface. The effectiveness of the proposed method is verified by numerical simulations.     

Neural network–based reconfiguration control for spacecraft formation in obstacle environments

This paper proposes an adaptive formation reconfiguration control scheme based on the leader‐follower strategy for multiple spacecraft systems. By taking the predesigned desired velocities and the trajectories as reference signals, a set of coordination tracking controllers is constructed by combining the reconstructed dynamic system and the neural network–based reconfiguration algorithm together. To avoid collisions between spacecraft and obstacles during the formation configuration process, the null space–based behavioral control is integrated into the control design. Since the spacecraft dynamics contains unknown nonlinearity and disturbance, it is challenging to make the system robust to uncertainties and improve the control precision simultaneously. To solve this problem, both the adaptive neural network strategy and the finite‐time control theory are employed. Finally, 2 simulation examples are carried out to verify the proposed algorithm, showing that the formation reconfiguration task can be executed successfully while achieving high control precision.     

Distributed dynamic matrix control with constrained optimization for collision and obstacle avoidance of simulated multiple quadcopters

A system of fast moving quadcopters has a high risk of collisions with neighboring quadcopters or obstacles. The objective of this work is to develop a control strategy for collision and obstacle avoidance of multiple quadcopters. In this paper, the problem of distributed dynamic matrix control (DMC) for collision avoidance among a team of multiple quadcopters attempting to reach consensus in the horizontal plane and yaw direction ( $x,y$, and $\psi$) is investigated. Violations of a predetermined safety radius generates output constraints on the DMC optimization function, which has not been dealt with in the literature. Different from past works, the proposed strategy can perform collision avoidance in the $x$, $y$, and $z$-directions. In addition, logarithmic barrier functions are implemented as input rate constraints on the control actions. Extensive simulation studies for a team of quadcopters illustrate promising results of the proposed control strategy and case variations. In addition, DMC parameter effects on the system performance are studied, and a successful study for obstacle avoidance is presented.     

Coordination control of multiple ellipsoidal agents with collision avoidance and limited sensing ranges

This paper contributes a design of cooperative controllers that force N mobile agents with an ellipsoidal shape and a limited sensing range to track desired trajectories and to avoid collision between them. A separation condition for ellipsoidal agents is first derived. Smooth step functions are then introduced. These functions and the separation condition between the ellipsoidal agents are embedded in novel pairwise collision avoidance functions to design coordination controllers. The proposed control design guarantees (1) smooth coordination controllers despite the agents’ limited sensing ranges, (2) no collision between any agents, (3) asymptotical stability of desired equilibrium set, and (4) instability of all other undesired critical sets of the closed loop system.     

Formation and obstacle avoidance control for multiagent systems

This paper considers the problems of formation and obstacle avoidance for multiagent systems.The objective is to design a term of agents that can reach a desired formation while avoiding collision with obstacles.To reduce the amount of information interaction between agents and target,we adopt the leader-follower formation strategy.By using the receding horizon control (RHC),an optimal problem is formulated in terms of cost minimization under constraints.Information on obstacles is incorporated online as sensed in a limited sensing range.The communication requirements between agents are that the followers should obtain the previous optimal control trajectory of the leader to each update time.The stability is guaranteed by adding a terminal-state penalty to the cost function and a terminal-state region to optimal problem.Finally,simulation studies are provided to verify the effectiveness of the proposed approach.