Human-robot collaboration while sharing production activities in dynamic environment: SPADER system

Interactive robot doing collaborative work in hybrid work cell need adaptive trajectory planning strategy. Indeed, systems must be able to generate their own trajectories without colliding with dynamic obstacles like humans and assembly components moving inside the robot workspace. The aim of this paper is to improve collision-free motion planning in dynamic environment in order to insure human safety during collaborative tasks such as sharing production activities between human and robot. Our system proposes a trajectory generating method for an industrial manipulator in a shared workspace. A neural network using a supervised learning is applied to create the waypoints required for dynamic obstacles avoidance. These points are linked with a quintic polynomial function for smooth motion which is optimized using least-square to compute an optimal trajectory. Moreover, the evaluation of human motion forms has been taken into consideration in the proposed strategy. According to the results, the proposed approach is an effective solution for trajectories generation in a dynamic environment like a hybrid workspace.     

Joint workspace of parallel kinematic machines

Robot workspace is the set of positions a robot can reach. Workspace is one of the most useful measures for the evaluation of a robot. Workspace is usually defined as the reachable space of the end-effector in Cartesian coordinate system. However, it can be defined in joint coordinate system in terms of joint motions. In this paper, workspace of the end-effector is called task workspace, and workspace of the joint motions is called joint workspace. Joint workspace of a parallel kinematic machine (PKM) is focused, and a tripod machine tool with three degrees of freedom (DOF) is taken as an example. To study the joint workspace of this tripod machine tool, the forward kinematic model is established, and an interpolating approach is proposed to solve this model. The forward kinematic model is used to determine the joint workspace, which occupies a portion of the domain of joint motions. The following contributions have been made in this paper include: (i) a new concept so-called joint workspace has been proposed for design optimization and control of a PKM; (ii) an approach is developed to determine joint workspace based on the structural constraints of a PKM; (iii) it is observed that the trajectory planning in the joint coordinate system is not reliable without taking into considerations of cavities or holes in the joint workspace.     

Obstacle Modelling Oriented to Safe Motion Planning and Control for Planar Rigid Robot Manipulators

Trajectory planning and tracking are crucial tasks in any application using robot manipulators. These tasks become particularly challenging when obstacles are present in the manipulator workspace. In this paper a n-joint planar robot manipulator is considered and it is assumed that obstacles located in its workspace can be approximated in a conservative way with circles. The goal is to represent the obstacles in the robot configuration space. The representation allows to obtain an efficient and accurate trajectory planning and tracking. A simple but effective path planning strategy is proposed in the paper. Since path planning depends on tracking accuracy, in this paper an adequate tracking accuracy is guaranteed by means of a suitably designed Second Order Sliding Mode Controller (SOSMC). The proposed approach guarantees a collision-free motion of the manipulator in its workspace in spite of the presence of obstacles, as confirmed by experimental results.     

Dynamics and input–output feedback linearization control of a wheeled mobile cable-driven parallel robot

In comparison to the conventional parallel robots, cable-driven parallel robots (CDPRs) have generally superior features such as simple production technology, low energy consumption, large workspace, high payload to moving weight ratio, and also low cost. On the other hand, a wheeled mobile robot (WMR) which is capable of covering a vast area can be used when no specific space is designated for the stationary accessories of a robot. In this paper, the integration of a CDPR with a WMR is proposed to overcome some of the issues related to each of these robots. The kinematic equations of the robot are presented. To derive the dynamic equations, Gibbs–Appel (G–A) formulation is used, which in contrary to the Lagrange formulation benefits from advantages of quasi-velocities over generalized coordinates as well as not requiring Lagrange multipliers. The dynamic equations of the two parts are coupled, and the interacting effects are observable from the governing equations. By considering non-holonomic wheels for the robot, internal dynamics appears in the equations. However, based on some conditions, the equations are input–output linearizable via a static feedback. The platform trajectory is designed based on the given end-effector trajectory. The effectiveness of the controller is shown through simulations and experimental tests.     

空间机器人抓捕目标后基于任务相容性的消旋策略

针对双臂空间机器人抓捕自旋目标后的镇定操作,在考虑机器人系统输入约束的条件下,提出了一种基于任务相容性的消旋规划与控制方法。首先,给出空间机器人抓捕目标后的组合系统的动力学模型,作为规划与控制的基础。然后,根据动力学可操作度和任务相容性设计了目标的快速消旋策略,其期望加速度的方向和大小分别取作速度的反方向和机器人系统输入约束允许的最大值。最后,基于所推导的运动学和动力学模型,通过对目标和机械臂末端分别建立柔顺度等式,提出了一种跟踪期望运动轨迹同时对末端接触力进行调节的柔顺控制方法。通过双臂7自由度空间机器人消除目标自旋运动的仿真结果,验证了所提方法的有效性。     

Modeling and Control of Head Raising Snake Robots by Using Kinematic Redundancy

In this paper, we consider trajectory tracking control of a head raising snake robot on a flat plane by using kinematic redundancy. We discuss the motion control requirements to accomplish trajectory tracking and other tasks, such as singular configuration avoidance and obstacle avoidance, for the snake robot. The features of the internal motion caused by kinematic redundancy are considered, and a kinematic model and a dynamic model of the snake robot are derived by introducing two types of shape controllable point. The first is the head shape controllable point, and the other is the base shape controllable point. We analyzed the features of the two kinds of shape controllable point and proposed a controller to accomplish the trajectory tracking of the robot’s head as its main task along with several sub-tasks by using redundancy. The proposed method to accomplish several sub-tasks is useful for both the kinematic model and the dynamic model. Experimental results using a head raising snake robot which can control the angular velocity of its joints show the effectiveness of the proposed controller.     

A Sequential Bi-criteria Search Algorithm for Robot Path Planning in the Box Pushing Problem

The collision-free trajectory planning method subject to control constraints for mobile manipulators is presented. The robot task is to move from the current configuration to a given final position in the workspace. The motions are planned in order to maximise an instantaneous manipulability measure to avoid manipulator singularities. Inequality constraints on state variables i.e. collision avoidance conditions and mechanical constraints are taken into consideration. The collision avoidance is accomplished by local perturbation of the mobile manipulator motion in the obstacles neighbourhood. The fulfilment of mechanical constraints is ensured by using a penalty function approach. The proposed method guarantees satisfying control limitations resulting from capabilities of robot actuators by applying the trajectory scaling approach. Nonholonomic constraints in a Pfaffian form are explicitly incorporated into the control algorithm. A computer example involving a mobile manipulator consisting of nonholonomic platform (2,0) class and 3DOF RPR type holonomic manipulator operating in a three-dimensional task space is also presented.     

Path feasibility and modification

Kinematic feasibility of a planned robot path is restrained by the kinematic constraints of the robot executing the task, such as workspace, configuration, and singularity. Since these kinematic constraints can be described utilizing the geometry of the given robot, corresponding regions within the robot workspace can be expressed in geometrical representation. Consequently, geometric information can be derived from the planned path and the geometric boundaries of these regions. Then, by utilizing the geometric information and proper modification strategies, a Cartesian robot path that is kinematically infeasible can be modified according to different task requirements. To demonstrate the proposed feasibility and modification schemes, simulations for a 6R robot manipulator are executed.     

空间机器人目标捕获的自适应规划

与地面固定基座机器人不同的是,空间机器人的运动学方程中含有动力学参数。在执行目标捕获任务时,目标动力学参数的不精确会给空间机器人的规划带来致命的影响。针对目标捕获后动力学参数不精确情况下的关节空间规划问题,在建立了自由飘浮空间机器人运动学模型的基础上,给出了雅可比矩阵及其动量守恒方程中的惯性参数以及惯性参数的组合参数线性化的具体形式,提出了一种关节空间的自适应规划方法。以平面二连杆空间机器人为研究对象进行仿真验证。结果表明,所提出的自适应规划方法可以有效降低惯性参数不精确给运动规划带来的影响,为空间机器人执行目标捕获等任务时提供了任务空间内精确轨迹跟踪的能力。     

A Technique to Analytically Formulate and to Solve the 2-Dimensional Constrained Trajectory Planning Problem for a Mobile Robot

A new technique for trajectory planning of a mobile robot in a two-dimensional space is presented in this paper. The main concept is to use a special representation of the robot trajectory, namely a parametric curve consisting in a sum of harmonics (sine and cosine functions), and to apply an optimization method to solve the trajectory planning problem for the parameters (i.e., the coefficients) appearing in the sum of harmonics. This type of curve has very nice features with respect to smoothness and continuity of derivatives, of whatever order. Moreover, its analytical expression is available in closed form and is very suitable for both symbolic and numerical computation. This enables one to easily take into account kinematic and dynamic constraints set on the robot motion. Namely, non-holonomic constraints on the robot kinematics as well as requirements on the trajectory curvature can be expressed in closed form, and act as input data for the trajectory planning algorithm. Moreover, obstacle avoidance can be performed by expressing the obstacle boundaries by means of parametric curves as well. Once the expressions of the trajectory and of the constraints have been set, the trajectory planning problem can be formulated as a standard mathematical problem of constrained optimization, which can be solved by any adequate numerical method. The results of several simulations are also reported in the paper to show the effectiveness of the proposed technique to generate trajectories which meet all requirements relative to kinematic and dynamic constraints, as well as to obstacle avoidance.     

A Fast Approach for Robot Motion Planning

This paper describes a new approach to robot motion planning that combines the end-point motion planning with joint trajectory planning for collision avoidance of the links. Local and global methods are proposed for end-point motion planning. The joint trajectory planning is achieved through a pseudoinverse kinematic formulation of the problem. This approach enables collision avoidance of the links by a fast null-space vector computation. The power of the proposed planner derives from: its speed; the good properties of the potential function for end-point motion planning; and from the simultaneous avoidance of the links collision, kinematic singularities, and local minima of the potential function. The planner is not defined over computationally expensive configuration space and can be applied for real-time applications. The planner shows to be faster than many previous planners and can be applied to robots with many degrees of freedom. The effectiveness of the proposed local and global planning methods as well as the general robot motion planning approach have been experimented using the computer-simulated robots. Some of the simulation results are included in this paper.     

Simultaneous dynamic optimization: A trajectory planning method for nonholonomic car-like robots

Trajectory planning in robotics refers to the process of finding a motion law that enables a robot to reach its terminal configuration, with some predefined requirements considered at the same time. This study focuses on planning the time-optimal trajectories for car-like robots. We formulate a dynamic optimization problem, where the kinematic principles are accurately described through differential equations and the constraints are strictly expressed using algebraic inequalities. The formulated dynamic optimization problem is then solved by an interior-point-method-based simultaneous approach. Compared with the prevailing methods in the field of trajectory planning, our proposed method can handle various user-specified requirements and different optimization objectives in a unified manner. Simulation results indicate that our proposal efficiently deals with different kinds of physical constraints, terminal conditions and collision-avoidance requirements that are imposed on the trajectory planning mission. Moreover, we utilize a Hamiltonian-based optimality index to evaluate how close an obtained solution is to being optimal.     

Real-time Velocity Alteration Strategy for Collision-free Trajectory Planning of Two Articulated Robot Manipulators

Two articulated robots working in a shared workspace can be programmed by planning the tip trajectory of each robot independently. To account for collision avoidance between links, a real-time velocity alteration strategy based on fast and accurate collision detection is proposed in this paper to determine the step of next motion of slave (low priority) robot for collision-free trajectory planning of two robots with priorities. The effectiveness of the method depends largely on a newly developed method of accurate estimate of distance between links. By using the enclosing and enclosed ellipsoids representations of polyhedral models of links of robots, the minimum distance estimate and collision detection between the links can be performed more efficiently and accurately. The proposed strategy is implemented in an environment where the geometric paths of robots are pre-planned and the preprogrammed velocities are piecewise constant but adjustable. Under the control of the proposed strategy, the master robot always moves at a constant speed. The slave robot moves at the selected velocity, selected by a tradeoff between collision trend index and velocity reduction in one collision checking time, to keep moving as far as possible and as fast as possible while avoid possible collisions along the path. The collision trend index is a fusion of distance and relative velocity between links of two robots to reflect the possibility of collision at present and in the future. Graphic simulations of two PUMA560 robot arms working in common workspace but with independent goals are conducted. Simulations demonstrate the collision avoidance capability of the proposed approach as compared to the approach based on bounding volumes. It shows that advantage of our approach is less number of speed alterations required to react to potential collisions.     

Path planning in the presence of obstacles based on task requirements

We propose a novel and efficient scheme for planning a kinematically feasible path in the presence of obstacles according to task requirements. By employing geometrical analysis, we derive expressions to describe the relationship between the planned path, kinematic constraints, and obstacles in the robot workspace. The freedom available according to task requirements is then utilized to modify the infeasible portions of the planned path. We use a 6R (revolute) wrist-partitioned type of robot manipulator and a spherical obstacle as a case study to demonstrate the proposed scheme. We then extend our results to general wrist-partitioned types of robot manipulators and arbitrarily-shaped or multiple obstacles. © 1994 John Wiley & Sons, Inc.     

关节锁定空间机械臂负载操作能力评估与轨迹规划

为了使单关节锁定空间机械臂继续执行负载任务,提出关节锁定空间机械臂负载操作能力评估方法及轨迹规划策略.首先,将动态负载能力分析方法与蒙特卡洛法相结合建立动态负载能力容错工作空间,该空间可以直观反映关节锁定空间机械臂负载操作能力及可达性;然后,栅格化该空间,并在代价函数中加入负载能力项以改进A*算法进行搜索轨迹;最后,通过仿真验证关节锁定空间机械臂负载能力评估及轨迹规划方法的正确性,所得轨迹平均带载能力比任务要求高42.5%.     

Coordination and Control of Multi-fingered Robot Hands with Rolling and Sliding Contacts

In this paper, the problem of controlling multi-fingered robot hands with rolling and sliding contacts is addressed. Several issues are explored. These issues involve the kinematic analysis and modeling, the dynamic analysis and control, and the coordination of a multi-fingered robot hand system. Based on a hand-object system in which the contacts are allowed to both roll and slide, a kinematic model is derived and analyzed. Also, the dynamic model of the hand-object system with relative motion contacts is studied. A control law is proposed to guarantee the asymptotic tracking of the object trajectory together with the desired rolling and/or sliding motions along the surface of the object. A planning approach is then introduced to minimize the contact forces so that the desired motion of the object and the relative motions between the fingers and the object can be achieved. Simulation results which support the theoretical development are presented.     

A neural network approach to complete coverage path planning.

Complete coverage path planning requires the robot path to cover every part of the workspace, which is an essential issue in cleaning robots and many other robotic applications such as vacuum robots, painter robots, land mine detectors, lawn mowers, automated harvesters, and window cleaners. In this paper, a novel neural network approach is proposed for complete coverage path planning with obstacle avoidance of cleaning robots in nonstationary environments. The dynamics of each neuron in the topologically organized neural network is characterized by a shunting equation derived from Hodgkin and Huxley's (1952) membrane equation. There are only local lateral connections among neurons. The robot path is autonomously generated from the dynamic activity landscape of the neural network and the previous robot location. The proposed model algorithm is computationally simple. Simulation results show that the proposed model is capable of planning collision-free complete coverage robot paths.     

Kinematics for multisection continuum robots

We introduce a new method for synthesizing kinematic relationships for a general class of continuous backbone, or continuum , robots. The resulting kinematics enable real-time task and shape control by relating workspace (Cartesian) coordinates to actuator inputs, such as tendon lengths or pneumatic pressures, via robot shape coordinates. This novel approach, which carefully considers physical manipulator constraints, avoids artifacts of simplifying assumptions associated with previous approaches, such as the need to fit the resulting solutions to the physical robot. It is applicable to a wide class of existing continuum robots and models extension, as well as bending, of individual sections. In addition, this approach produces correct results for orientation, in contrast to some previously published approaches. Results of real-time implementations on two types of spatial multisection continuum manipulators are reported.     

Application of robots in assembly automation

The development of flexible assembly is closely related to the introduction of robots in assembly automation. If has long been recognized that automatic parts assembly by robots is one of the most delicate and most difficult tasks in industrial robotics. This task involves two control problems, trajectory planning for the whole automatic assembly process and reduction of the reaction forces appearing between the parts being assembled. This paper addresses both aspects of this control task. The strategical control level for the manipulation of robots and various approaches to trajectory planning tasks in assembly processes are discussed. A new approach to the determination of the strategical control level, including various models (geometric, kinematic and dynamic) for manipulation robots, is briefly described.The last and most delicate phase of the assembly process is parts mating, which is rather like inserting a peg in a hole. In order to reduce the reaction forces appearing between the parts being assembled, force feedback control is applied. The experimental results of the industrial robot insertion process with force feedback are also presented in the paper.     

Dual-edge robotic gear chamfering with registration error compensation

This paper describes a novel method for robotic gear chamfering called dual-edge chamfering which can facilitate simultaneous chamfering of the two edges of adjacent gear teeth and overcome typical registration errors arising due to the placement of the workpiece in the robot workspace. Deviations of the robot end-effector trajectory when compared to the nominal trajectory due to registration errors are discussed first; such trajectory deviations caused by typical registration errors due to gear center translation and rotation are quantified. Dual-edge chamfering process is described and an efficient trajectory design strategy is developed by considering the kinematic constraints imposed by the profiles of the gear edge and the abrasive tool. The dual-edge chamfering robot trajectory is facilitated by a simple procedure for identifying the gear and gear root centers by employing the robot. To execute the dual-edge chamfering trajectory, an efficient motion/force control strategy that includes active compliance from the tool mounted on the robot is proposed. A number of real-time experiments are conducted to evaluate the proposed method by employing a commercial six degree-of-freedom robot. Two types of large cylindrical metal gears are utilized for testing, an external gear with teeth on the outside and an internal gear with teeth on the inside. In addition to these, two different robotic compliant tools with axial and radial compliance are tested. A representative sample of the experimental results are presented and discussed.