基于场景匹配的移动机器人避障

研究环境未知情况下移动机器人的避障问题，提出一种基于模糊场景匹配的移动机器人避障方法．该方法对多种传感器的信息进行融合，生成当前环境的场景并与场景库中的场景进行匹配，利用匹配结果并通过模糊控制器得到机器人的运动参数，对机器人的避障进行控制,实验结果表明了该方法的正确性和有效性。     

移动机器人未知环境避障研究

针对移动机器人的避障问题,以AS-R移动机器人为实验平台,提出了一种改进人工势场和模糊逻辑相结合的路径规划方法.对于未知障碍物环境采用人工势场法进行实时路径规划,对于动态近距离动态障碍物采用模糊逻辑方法引导机器人做出避障行为.为了有效将2种方法结合,根据传感器信息对于人工势场方法引入转角的信任度,机器人运行方向由上述2...     

基于多传感器信息融合的移动机器人避障

为了更好地解决移动机器人在未知环境下的自主避障问题,采用多传感器信息融合的方法,通过多个超声传感器对障碍物信息进行采集。合理确立模糊控制器的输入输出,通过模糊推理将障碍物距离信息模糊化,建立模糊规则并解模糊,以达到对移动机器人的安全避障的控制。通过建立移动机器人运动模型,设计了仿真平台,得到实验结果表明:该算法具有良好的可行性。     

Obstacle avoidance for redundant robots using configuration control

The article presents a new and simple solution to the obstacle avoidance problem for redundant robots. In the proposed approach, called configuration control, the redundancy is utilized to configure the robot so as to satisfy a set of kinematic inequality constraints representing obstacle avoidance, while the end-effector is tracking a desired trajectory. The robot control scheme is very simple, and uses on-line adaptation to eliminate the need for the complex dynamic model and parameter values of the robot. Several simulation results for a four-link planar robot are presented to illustrate the versatility of the approach. These include reaching around a stationary obstacle, simultaneous avoidance of two obstacles, robot reconfiguration to avoid a moving obstacle, and avoidance of rectangular obstacles. The simplicity and computational efficiency of the proposed scheme allows on-line implementation with a high sampling rate for real-time obstacle avoidance in a dynamically varying environment.     

基于改进PRM的采摘机器人机械臂避障路径规划

针对采摘机器人机械臂在不确定的环境中进行采摘作业的要求,提出了一种基于改进概率地图(PRM)算法的机械臂避障路径规划方法。将机械臂工作空间分割成离散单元集合,通过遍历的方法,获得机械臂工作空间中任意离散单元与机械臂有撞位姿之间的映射关系。将空间障碍物分割成离散单元,并通过索引映射关系获得与障碍物有撞的所有机械臂位姿信息,并以此建立关节构形空间。通过PRM算法在关节构形空间中快速搜索机械臂避障路径。仿真结果表明:相比传统PRM算法,改进算法速度提高22. 2%,能够有效地实现机械臂无碰撞路径规划。     

两级传感器信息融合的移动机器人避障研究

针对移动机器人的避障问题,以AS-R移动机器人为研究平台,提出了一种将神经网络和模糊神经网络相结合的两级融合方法。采用BP神经网络对多超声波传感器信息进行融合,以减少传感器信息的不确定,提高对障碍物识别的准确率;采用模糊神经网络实现移动机器人的避障决策控制,使之更适合系统的避障要求。该方法使移动机器人在避障中具有较好的灵活性和鲁棒性。机器人避障实验验证了所提方法的有效性。     

Obstacle avoidance with translational and efficient rotational motion control considering movable gaps and footprint for autonomous mobile robot

This paper presents a sensor-based real-time obstacle avoidance method for an autonomous omnidirectional mobile robot based on simultaneous control of translational and efficient rotational motion considering movable gaps and the footprint. Autonomous mobile service robots that have been developed in recent years have arms that work and execute tasks. Depending on the task using moving parts, the shape of the robot (i.e., the footprint) changes. In this study, to improve the safety and possibility of reaching a goal even through a narrow gap with unknown obstacles, a sensor-based real-time obstacle avoidance method with simultaneous control of translational and efficient rotational motion (without unnecessary rotational motion) based on the evaluation of movable gaps and the footprint is proposed. To take account of the anisotropy footprint of the robot, multiple-circle robot model is proposed. In this paper, a novel control method based on fuzzy set theory is presented. To verify the effectiveness of the proposed method, several simulations and experiments are carried out.

     

基于模糊改进人工势场法的机器人避障方法研究

在内部密封、狭窄、多障碍的船舱环境中,障碍物的分布具有随机性和不确定性,对于移动机器人的避障方法而言,传统人工势场法存在目标不可达、局部极小值等问题.设计了一种基于模糊逻辑的改进人工势场法,在避障算法的局部极小值附近,基于模糊逻辑给予移动机器人辅助控制力,帮助机器人逃离局部极小值点,避免机器人在避障过程中陷入局部极小值点的问题,并且优化路径.仿真实验表明:在多障碍复杂环境下,该算法能实现机器人实时、安全的避障.     

多级模糊控制的月球车避障研究

针对月球车这个MIMO系统,考虑其在未知环境下的避障问题,设计了一个多级模糊控制器,将输入变量分组设计子模糊作为第1级,再将第1级的输出作为第2级的输入变量设计第2级子模糊系统,最后控制系统输出平移速度和角速度。这样就避免了常规模糊系统中规则数目过大和设计繁琐问题,提高了整个控制系统的性能。该控制器模糊规则数量少,控制方法简单,响应速度快。最后的实验证明了该方法的有效性。     

Obstacle avoidance tracking control with antiswing and tracking errors constraint for underactuated automated lifting robots with load hoisting/lowering

The existing automated lifting robot technology focuses merely on motion control and ignores the surrounding environment. In practice, obstacles inevitably exist in the movement path of the automated lifting robot, which affects construction safety. Furthermore, due to the underactuated characteristics of the automated lifting robot, the load can be difficult to control when it swings violently, which undoubtedly poses huge challenges to obstacle avoidance trajectory planning and controller design. In this paper, an obstacle avoidance trajectory and its tracking controller with antiswing and tracking errors constraint are proposed. To ensure accurate load positioning and effective obstacle avoidance, the proposed control method introduces a four-segment polynomial trajectory interpolation curve to construct an obstacle avoidance trajectory based on analyzing the geometric relationship between variables. To improve the transient coupling control performance of the system, combined with the passive analysis of the automated lifting robot system, this method constructs a potential function that limits the tracking error and a coupling signal that enhances the coupling relationship between the system variables. Barbalat's lemma and Lyapunov techniques are used to analyze the stability of the system. Simulation and experimental results show that the proposed control method can significantly suppress or even eliminate load oscillation, accurately locate the load, avoid obstacles, improve the safety and efficiency of the working automated lifting robot, and have strong robustness to changes in system parameters and the addition of external disturbances.     

Obstacle avoidance extremum seeking control based on constrained derivative-free optimization

A new control scheme based on extremum seeking control (ESC) which employs a constrained derivative-free optimization algorithm has been proposed in this paper. A theorem has been formulated to prove the convergence result of ESC based on constrained derivative-free optimization. Generalized pattern search method with filter algorithm for constraint is used to generate a sequence of ESC control state. Since generalized pattern search (GPS) method does not require continuously differentiable and Lipschitz conditions, noise cancellation algorithm is added to the proposed ESC algorithm which is then used for multi-agent robot system. The obstacles are expressed as constraint functions instead of the traditional way of calculating the performance function of obstacles. Simulation results illustrate a multi-agent obstacle avoidance system which utilized the control algorithm to avoid obstacles that appear on the path of multi-agent robots. Based on the simulation results, it can be observed that multi-agents maintain their formation as per initial condition and follow the target without colliding into obstacles while navigating in a noisy environment. Performance comparison of the proposed algorithm with a reference algorithm shows the efficiency of the proposed algorithm.     

Obstacle avoidance via articulation

This article presents a practical implementation of the theory for articulation of spatial robots such as the PUMA and TRS type robots. The “Blueprint Algorithm” is introduced as a simple rule-based planning algorithm in which the geometry of interference takes on the role of a basis in a collision-free path planning process amongst obstacles. This implementation presents a novel idea of “Machine Intelligence Via Robot Geometry” which utilizes robot attributes such as workspace and dexterity.     

Depth camera based collision avoidance via active robot control

A new type of depth cameras can improve the effectiveness of safety monitoring in human–robot collaborative environment. Especially on today's manufacturing shop floors, safe human–robot collaboration is of paramount importance for enhanced work efficiency, flexibility, and overall productivity. Within this context, this paper presents a depth camera based approach for cost-effective real-time safety monitoring of a human–robot collaborative assembly cell. The approach is further demonstrated in adaptive robot control. Stationary and known objects are first removed from the scene for efficient detection of obstacles in a monitored area. The collision detection is processed between a virtual model driven by real sensors, and 3D point cloud data of obstacles to allow different safety scenarios. The results show that this approach can be applied to real-time work cell monitoring.     

具有速度、加速度约束的机器人编队避障控制

针对轮式移动机器人的编队避障问题,提出了一种改进的控制算法,能够有效实现避免碰撞和规避障碍.首先,建立多机器人不同控制增益的全员"航标"引导的非线性循环追踪控制编队,当编队过程某成员监测执行功能失效(但仍能运行)时,可对非失效机器人进行系统降级重组,并继续执行任务且避免机器人之间发生碰撞;再通过引入速度和加速度约束,以满足轮式移动机器人控制接口及保护电机的需要,从而保证控制算法的稳定与收敛;最后,通过引入惩罚因子对该控制算法进行改进,使编队成功规避障碍物并进行最短路径规划.结果表明,改进的控制算法增加了多机器人编队的鲁棒性、提高了抗干扰能力及编队恢复执行任务的可靠性,更有效地实现了编队避障控制.     

Obstacle avoidance control of redundant robots using variants of particle swarm optimization

Four variants of Particle Swarm Optimization (PSO) are proposed to solve the obstacle avoidance control problem of redundant robots. The study involved simulating the performance of a 5 degree-of-freedom (DOF) robot manipulator in an environment with static obstacle. The robot manipulator is required to move from one position to a desired goal position with minimum error while avoiding collision with obstacles in the workspace. The four variants of PSO are namely PSO-W, PSO-C, qPSO-W and qPSO-C where the latter two algorithms are hybrid version of the first two. The hybrid PSO is created by incorporating quadratic approximation operator (QA) alongside velocity update routine in updating particles' position. The computational results reveal that PSO-W yields better performance in terms of faster convergence and accuracy.     

Motion control of a snake robot moving between two non-parallel planes

A control method that makes the head of a snake robot follow an arbitrary trajectory on two non-parallel planes, including coexisting sloped and flat planes, is presented. We clarify an appropriate condition of contact between the robot and planes and design a controller for the part of the robot connecting the two planes that satisfies the contact condition. Assuming that the contact condition is satisfied, we derive a simplified model of the robot and design a controller for trajectory tracking of the robot’s head. The controller uses kinematic redundancy to avoid violating the limit of the joint angle and a collision between the robot and the edge of a plane. The effectiveness of the proposed method is demonstrated in experiments using an actual robot.     

Smooth control of an articulated mobile robot with switching constraints

The paper describes a smooth controller of an articulated mobile robot with switching constraints. The use of switching constraints associated with grounded/lifted wheels is an effective method of controlling various motions; e.g. the avoidance of a moving obstacle. A model of an articulated mobile robot that has active and passive wheels and active joints with switching constraints is derived. A controller that accomplishes the trajectory tracking of the robot’s head and subtasks using smooth joint input is proposed on the basis of the model. Simulations and experiments are presented to show the effectiveness of the proposed controller.     

基于模糊控制的移动机器人避障研究

针对移动机器人在未知环境中的不确定性,利用Matlab构建了多传感器仿真试验移动平台,在Simulink中搭建移动机器人运动学模型,利用多传感器采集环境中的障碍物信息与目标物的方位角,设计了具有避障功能的模糊控制算法.通过模糊控制器控制移动机器人的左右轮速度实现机器人的转弯以及直走,根据机器人实时的角度反馈信息不断修正机器人的位姿以精确避障.仿真实验验证了该方法的可行性及有效性.     

模糊控制在机器人超声避障系统的应用

本文介绍模糊控制技术与智能轮椅机器人超声波避障技术相结合的应用.本系统使用超声波的探测距离作为输入信号,经模糊控制技术处理后,输出机器人左右轮的转动速度来实现超声波避障.在MATLAB环境下开发模糊控制器并仿真出模糊控制策略.在智能轮椅机器人超声避障系统中得到成功应用.     

Obstacle avoidance using flow field divergence

The use of certain measures of flow field divergence is investigated as a qualitative cue for obstacle avoidance during visual navigation. It is shown that a quantity termed the directional divergence of the 2-D motion field can be used as a reliable indicator of the presence of obstacles in the visual field of an observer undergoing generalized rotational and translational motion. The necessary measurements can be robustly obtained from real image sequences. Experimental results are presented showing that the system responds as expected to divergence in real-world image sequences, and the use of the system to navigate between obstacles is demonstrated