双臂空间机器人的避自碰轨迹规划研究*

本文针对自由漂浮的双臂空间机器人系统研究了一种基于危险域的避自碰轨迹规划方案。首先,引入危险域的概念,用来评估两个机械臂之间发生碰撞的危险程度。其次,在路径规划的基础之上,利用危险域的反馈信息,设计了一种安全避自碰的轨迹规划方案,用以保证两个机械臂可以运动在安全位型,从而避免发生自碰。最后,针对一个双臂冗余空间机器人系统进行运动仿真,仿真结果验证了本文方法的有效性。     

机器人的CP-nets优化类人轨迹规划

机器人移动轨迹按照人的手臂来模拟是提高机器人安全性和人机交互能力的有效方法,特别是针对机器人抓取路径不唯一的场合,类人行为对于人机系统表现更加自然。此前,通常利用Kinect等设备,基于人工神经网络和K近邻算法等智能算法对类人轨迹进行规划,但无法获得未采样过的最优轨迹。本文基于CP-nets采用偏好模型研究类人运动轨迹,然后将该模型应用于机器人控制,在没有采样的情况下,也可得到最优的类人轨迹。实验结果表明,基于CP-nets 的类人规划轨迹具有较高的效率和舒适性,符合人的运动特征。     

基于混合遗传算法的工业机器人最优轨迹规划

为兼顾工业机器人工作效率与轨迹的平稳性,提出一种基于混合遗传算法的二次轨迹规划方案.通过最优时间轨迹规划得到最小执行时间,在最小执行时间内进行最优冲击轨迹规划,进而规划出一条既高效又平滑的运动轨迹.采用五次均匀B样条在关节空间进行快速插值,不仅保证了各关节速度和加速度连续性还保证了各关节冲击的连续性.连续平滑的冲击可以减少机械振动,延长机器人的工作寿命.选用PUMA560为对象进行仿真与实验,结果表明,该方案可以获得比较理想的机器人运动轨迹,所提出的混合遗传算法能有效提高全局寻优的性能和算法运行的稳定性.     

自由漂浮空间机器人末端轨迹优化自适应控制

惯性参数不确定情况下的自由漂浮空间机器人(FFSR)轨迹跟踪控制是当前FFSR自主控制研究的重点与难点之一.针对该问题,提出一种FFSR末端轨迹优化自适应跟踪控制方法.该方法首先基于离散状态依赖黎卡提方程(DSDRE),设计两级DSDRE优化跟踪控制器,然后在控制器输出基础上,通过求解有约束条件下的非线性优化问题实现FFSR惯性参数的辨识,进而根据辨识结果调整控制器相关参数,实现FFSR末端轨迹的优化自适应跟踪控制.最后,采用平面两连杆FFSR模型进行仿真,验证了所提出方法的有效性.     

Unified multi-domain modelling and simulation of space robot for capturing a moving target

Space robotic systems are expected to play an increasingly important role in the future on-orbit service. The applications include repairing, refueling or de-orbiting of a satellite, or removal of the space debris. The dynamical performances of space robotic system result from the multi-physics interactions between mechanical, electrical, electronic, control, etc. In this paper, we developed a unified multi-domain modelling and simulation system. The system is composed of the following modules: the path planner, joint controllers, motor and its driver, gearing mechanism of the space manipulators, the Guidance, Navigation, and Control (GNC) system, the actuators of the base, and the orbital environment, orbital dynamic and the multi-body dynamic of the whole system, etc. Based on this system, the operation during different stages, including far range rendezvous, close range rendezvous (is usually divided into two sub-phases: closing and final approach) and target capturing can be studied from the view of multi-physics domains. The key algorithms, such as pose (position and attitude) measurement, GNC of the base, path planning and control of the space manipulator, and so on, can be validated using the system. As examples, the capturing processes of a moving target under free-floating and attitude-controlled modes are simulated and the simulation results are given.     

Optimal planning of robot calibration experiments by genetic algorithms

In this article, techniques developed in the science of genetic computing are applied to solve the problem of optimally selecting robot measurement configurations, which is an important element in successfully completing a robot calibration experiment. Genetic algorithms are customized for a type of robot measurement configuration selection problem in which the robot workspace constraints are defined in terms of robot joint limits. Simulation studies are conducted to examine the effectiveness of the genetic algorithms for the application. ©1997 John Wiley & Sons, Inc.     

Coverage trajectory planning for a bush trimming robot arm

A novel motion planning algorithm for robotic bush trimming is presented. The algorithm is based on an optimal route search over a graph. Differently from other works in robotic surface coverage, it entails both accuracy in the surface sweeping task and smoothness in the motion of the robot arm. The proposed method requires the selection of a custom objective function in the joint space for optimal node traversal scheduling, as well as a kinematically constrained time interpolation. The algorithm was tested in simulation using a model of the Jaco arm and three target bush shapes. Analysis of the simulated motions showed how, differently from classical coverage techniques, the proposed algorithm is able to ensure high tool positioning accuracy while avoiding excessive arm motion jerkiness. It was reported that forbidding manipulation posture changes during the cutting phase of the motion is a key element for task accuracy, leading to a decrease of the tool positioning error up to 90%. Furthermore, the algorithm was validated in a real‐world trimming scenario with boxwood bushes. A target of 20 mm accuracy was proposed for a trimming result to be considered successful. Results showed that on average 82% of the bush surface was affected by trimming, and 51% of the trimmed surface was cut within the desired level of accuracy. Despite the fact that the trimming accuracy turned out to be lower than the stated requirements, it was found out this was mainly a consequence of the inaccurate, early stage vision system employed to compute the target trimming surface. By contrast, the trimming motion planning algorithm generated trajectories that smoothly followed their input target and allowed effective branch cutting.     

Evolutionary trajectory planning for an industrial robot

This paper presents a novel general method for computing optimal motions of an industrial robot manipulator (AdeptOne XL robot) in the presence of fixed and oscillating obstacles. The optimization model considers the nonlinear manipulator dynamics, actuator constraints, joint limits, and obstacle avoidance. The problem has 6 objective functions, 88 variables, and 21 constraints. Two evolutionary algorithms, namely, elitist non-dominated sorting genetic algorithm (NSGA-II) and multi-objective differential evolution (MODE), have been used for the optimization. Two methods (normalized weighting objective functions and average fitness factor) are used to select the best solution tradeoffs. Two multi-objective performance measures, namely solution spread measure and ratio of non-dominated individuals, are used to evaluate the Pareto optimal fronts. Two multi-objective performance measures, namely, optimizer overhead and algorithm effort, are used to find the computational effort of the optimization algorithm. The trajectories are defined by B-spline functions. The results obtained from NSGA-II and MODE are compared and analyzed.     

Optimal configuration for dual-arm space robot grasping a tumbling target based on task compatibility

Multibody System Dynamics - This paper presents a method to determine the optimal configuration for a dual-arm space robot grasping a tumbling target. In contrast to the existing studies that focus...     

Optimal trajectory planning for industrial robots

An analysis of the results of an algorithm for optimal trajectory planning of robot manipulators is described in this paper. The objective function to be minimized is a weighted sum of the integral squared jerk and the execution time. Two possible primitives for building the trajectory are considered: cubic splines or fifth-order B-splines. The proposed technique allows to set constraints on the robot motion, expressed as upper bounds on the absolute values of velocity, acceleration and jerk. The described method is then applied to a 6-d.o.f. robot (a Cartesian gantry manipulator with a spherical wrist); the results obtained using the two different primitives are presented and discussed.     

羽毛球机器人机械臂运动轨迹多目标规划

为了实现羽毛球机器人机械臂高速连续平滑地击打羽毛球动作,提出了一种新的多目标机械臂运动轨迹优化模型。首先,该轨迹优化模型根据D-H运动学模型,通过坐标变换建立机械臂的位姿表达式。然后,采用牛顿下山法求出给定路径关键点的运动学逆解集,并基于最短路径算法从逆解集中求出最优解。最后,根据所求出最优解,采用三次样条插值建立电机转角函数,以实现机械臂的连续平滑运动。实验结果表明：新的轨迹优化模型能够有效地降低电机能耗和提高转动效率,从而保证了机械臂响应速度。     

Position estimation of a mobile robot using images of a moving target in intelligent space with distributed sensors

Latest advances in hardware technology and state-of-the-art of mobile robots and artificial intelligence research can be employed to develop autonomous and distributed monitoring systems. A mobile service robot requires the perception of its present position to co-exist with humans and support humans effectively in populated environments. To realize this, a robot needs to keep track of relevant changes in the environment. This paper proposes localization of a mobile robot using images recognized by distributed intelligent networked devices in intelligent space (ISpace) in order to achieve these goals. This scheme combines data from the observed position, using dead-reckoning sensors, and the estimated position, using images of moving objects, such as a walking human captured by a camera system, to determine the location of a mobile robot. The moving object is assumed to be a point-object and projected onto an image plane to form a geometrical constraint equation that provides position data of the object based on the kinematics of the ISpace. Using the a priori known path of a moving object and a perspective camera model, the geometric constraint equations that represent the relation between image frame coordinates for a moving object and the estimated robot's position are derived. The proposed method utilizes the error between the observed and estimated image coordinates to localize the mobile robot, and the Kalman filtering scheme is used for the estimation of the mobile robot location. The proposed approach is applied for a mobile robot in ISpace to show the reduction of uncertainty in determining the location of a mobile robot, and its performance is verified by computer simulation and experiment.     

Vision-based interception of a moving target with a nonholonomic mobile robot

A novel vision-based scheme is presented for driving a nonholonomic mobile robot to intercept a moving target. The proposed method has a two-level structure. On the lower level, the pan–tilt platform carrying the on-board camera is controlled so as to keep the target as close as possible to the center of the image plane. On the higher level, the relative position of the target is retrieved from its image coordinates and the camera pan–tilt angles through simple geometry, and used to compute a control law which drives the robot to the target. Various possible choices are discussed for the high-level robot controller, and the associated stability properties are rigorously analysed. The proposed visual interception method is validated through simulations as well as experiments on the mobile robot MagellanPro.     

Optimal parametrization of curves for robot trajectory design

A numerical method is presented for the offline determination of the minimum-time parameterization of a fixed path in robot joint space, assuming start and end at rest conditions and subject to constraints on manipulator joint torques. A numerical method for solving the problem is discussed in which the derivative of the change of variables is approximated by a cubic spline. Numerical results for a three-axis manipulator are presented     

Time-optimal and jerk-continuous trajectory planning for robot manipulators with kinematic constraints

In this paper a high smooth trajectory planning method is presented to improve the practical performance of tracking control for robot manipulators. The strategy is designed as a combination of the planning with multi-degree splines in Cartesian space and multi-degree B-splines in joint space. Following implementation, under the premise of precisely passing the via-points required, the cubic spline is used in Cartesian space planning to make either the velocities or the accelerations at the initial and ending moments controllable for the end effector. While the septuple B-spline is applied in joint space planning to make the velocities, accelerations and jerks bounded and continuous, with the initial and ending values of them configurable. In the meantime, minimum-time optimization problem is also discussed. Experimental results show that, the proposed approach is an effective solution to trajectory planning, with ensuring a both smooth and efficiency tracking performance with fluent movement for the robot manipulators.     

Joint space trajectory planning for flexible manipulators

A trajectory planning approach for controlling flexible manipulators is proposed. It is demonstrated that choosing actual joint angles as the generalized rigid coordinates is the key to applying the proposed approach. From the observation of the special structure of the input matrix, the concepts of motion-induced vibration and inverse dynamics under a specified motion history of the joints are formed naturally. Based on the above concepts, trajectory planning in joint space is proposed by using the optimization technique to determine the motion of joints along a specified path in joint space or work space and for general point-to-point motion. The motion for each joint is assumed to be in a class consisting of a fifth-order polynomial and a finite terms of Fourier series. This parameterization of motion allows the optimal trajectory planning to be formulated as a standard nonlinear programming problem, which avoids the necessity of solving a two-point-boundary-value problem and using dynamic programming. Setting the accelerations to zero at the initial and the final times is used to obtain smoother motion to reduce the spillover energy into unmodeled high-frequency dynamics. A penalty term on vibration energy contained in the performance index is used to minimize the vibration of the system modeled by lower frequency only. The final simulation results show the effectiveness of the proposed approach and the advantage for proper trajectory planning. © 2995 John Wiley & Sons, Inc.     

多障碍环境中移动机器人的光滑轨迹规划

根据轮式移动机器人参数化轨迹生成模型,结合多障碍物结构化环境中障碍物的建模,把其和参数化轨迹规划模型融合,得到了具有一般性的多障碍物环境中轮式移动机器人光滑轨迹规划模型;并利用最优化控制原理,建立了任意性能指标下,多障碍物环境中最优参数化轨迹生成模型。结合数值求解方法,推导了多障碍物环境中参数化轨迹规划非线性求解模型的求解方法。最后通过仿真验证了参数化轨迹规划求解模型的正确性。     

自由漂浮空间机器人的笛卡尔连续路径规划

对于自由漂浮空间机器人,位置级逆运动学方程不适合于笛卡尔连续路径的规划,而且机械臂的运动会对基座产生扰动.为此提出了基于速度级逆运动学方程的方法,可实现5个目标:1)惯性空间连续位姿跟踪;2)基座姿态无扰动的连续位置跟踪;3)基座姿态无扰动的连续姿态跟踪;4)基座姿态调整的连续位置跟踪;5)基座姿态调整的连续姿态跟踪.采用阻尼最小方差法回避动力学奇异,所规划的路径连续平滑.仿真结果表明了该方法的有效性.     

Arm path planning of a space robot with angular momentum

Arm path planning of a space robot with angular momentum is considered in this paper. A space robot changes its attitude by the arm motion and angular momentum of the space robot has the possibility to reduce the attitude change. A path planning method of the arm where the final satellite attitude becomes the same as the initial one is proposed. The method derives an approximate path first based on the attitude change when the arm moves along an infinitely small closed curve and then modifies the path by the Newton method. The amplitude of the arm motion decreases with the magnitude of the angular momentum, which shows that the proposed method utilizes the angular momentum effectively.     

Gait and foot trajectory planning for versatile motions of a six-legged robot

This article deals with the problem of planning and controlling a radially symmetric six-legged walker on an uneven terrain when a smooth time-varying body motion is required. The main difficulties lie on the planning of gaits and foot trajectories. As for the gaits, this article discusses the forward wave gait of a variable duty factor and a variable wave direction. With the commanded body motion, the maximum possible duty factor is computed using the speed limit of the leg swing motion. Guaranteeing this maximum duty factor contributes to obtain higher stability. We prove the “continuity” of this forward wave gait planning algorithm adds the versatility to gaits planned. The foot trajectory planning algorithm dynamically generates a smooth foot trajectory as a function of the instantaneous body motions by modifying standard leg motion templates. The robot can negotiate an uneven terrain by modifying a vertical leg motion by a signal of tactile sensors on the foot. The experiments prove that the robot can successfully track smooth curves with body rotations on an uneven terrain, and thus prove the robustness of the algorithms. © 1997 John Wiley & Sons, Inc.