Trajectory Planning and Control of Industrial Robot Manipulators

European Journal of Mechanics A-solids, 2004

We discuss the problem of minimum cost trajectory planning for robotic manipulators. It consists of linking two points in the operational space while minimizing a cost function, taking into account dynamic equations of motion as well as bounds on joint positions, velocities, jerks and torques. This generic optimal control problem is transformed, via a clamped cubic spline model of joint temporal evolutions, into a non-linear constrained optimization problem which is treated then by the Sequential Quadratic Programming (SQP) method. Applications involving grasping mobile object or obstacle avoidance are shown to illustrate the efficiency of the proposed planner.  2004 Elsevier SAS. All rights reserved.

Journal of Robotic Systems, 2000

This article presents a method for determining smooth and time-optimal path constrained trajectories for robotic manipulators and investigates the performance of these trajectories both through simulations and experiments. The desired smoothness of the trajectory is imposed through limits on the torque rates. The third derivative of the path parameter with respect to time, the pseudo-jerk, is the controlled input. The limits on the actuator torques translate into state-dependent limits on the pseudoacceleration. The time-optimal control objective is cast as an optimization problem by using cubic splines to parametrize the state space trajectory. The optimization problem is solved using the flexible tolerance method. The experimental results presented show that the planned smooth trajectories provide superior feasible time-optimal motion.

MATEC Web of Conferences

In one of the many definitions of the industrial robots in ISO 8373:2012 [1] is said that an industrial robot is an "actuated mechanism programmable in two or more axes with a degree of autonomy, moving within its environment, to perform intended tasks". There are different types and models of industrial robots, which can be classified, as M. W. Spong, S. Hutchinson and M. Vidyasagar [2] say, according to different criteria, such as the power source or the way in which their joints are actuated, their mechanical or kinematic structure, the payload capacity, the volume of their workspace, their method of control or their intended application area. Current and future challenges to effectively respond to the global competitiveness and the consumer behaviour, and using the advantages of the new technologies, aim, as M. Hägele, K. Nilsson, N. Pires and R. Bischoff say [3], to design the industrial robots after new principles, so they can be used in many fields and industries, to be more performance and less expensive, to interact intuitively with workers. H. Chen, B. Zhang and G. Zhang [4] note that such intelligent industrial robotics systems are attracting more and more attention of the specialists because of the growing need for adaptation to the complex and flexible industrial processes. C. Mineo, S. G. Pierce, P. I. Nicholson and I. Cooper [5] prove that automatic programming of control systems based on robots does increase flexibility by minimizing the effort and time needed for implementation. R. Bloss [6] shows that a class of robots that successfully meet such challenges is the category of the collaborative robots, which can be used in many applications where traditional robots fail, providing rapid major improvements in productivity, safety, ease of programming, portability and costs over time. R. Bogue [7] and B. Carlisle [8] take into account the use of the collaborative robots in applications such as the manufacture and assembly of the electronic products or those from the automotive; they can be used by the small and medium-sized companies or by the companies seeking agile production methods. Z. Lu, C. Xu, Q. Pan, D. Xiao, F. Meng and J. Hao [9] analyse the use of the collaborative robots for non-destructive testing of curved surfaces.

1998

This work proposes and demonstrates a strategy for planning smooth path-constrained timeoptimal trajectories for manipulators. Such trajectories are obtained by limiting the actuator jerks required by the planned motion. Existing planning strategies incorporate the smoothness requirement either as smoothness of the actuator torques or as smoothness of the joint trajectories. The smoothness requirement is desirable for reducing strain on robot actuators while still requiring low cycle times. In this work, the trajectory smoothness is de ned in the phase plane and the planning observes the limits on the actuator jerks. The solution proposed for determining the optimal trajectories consists of approximating the time optimal control problem by a nonlinear parameter optimization problem which is solved using the exible tolerance method. It is shown that the approximate solution converges to the time optimal motion when the actuator jerks become very high. A number of simulations are perf...

Robotica, 2010

In the industrial environment several constraints affect the robot motion planning. Those are imposed by manufacturing considerations, such as, e.g., to strictly follow a given path, or by physical constraints, such as, e.g., to avoid torque saturation. Among the others, limitation on the velocity, acceleration and jerk at the joints are often required by the robots manufacturers. In this paper, a motion planning algorithm for robot manipulators that take into account several constraints simultaneously is presented. The algorithm developed approaches the motion planning algorithm from a wide perspective, solving systematically the joint as well as the Cartesian motion, both for the point-to-point and the fly movements. The validation has been performed first by numerical simulations and then on two different industrial manipulators, with different size, with and without the presence of a payload, by imposing demanding trajectories where all the constraints have been excited.

2013 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2013

We consider planning and implementation of fast motions for industrial manipulators constrained to a given geometric path. With such a problem formulation, which is quite reasonable for many standard operation scenarios, it is intuitively clear that a feedback controller should be designed to achieve orbital stabilization of a time-optimal trajectory instead asymptotic. We propose an algorithm to convert an asymptotically stabilizing controller into an orbitally stabilizing one and check achievable performance in simulations and, more importantly, in experiments performed on a standard industrial robot ABB IRB 140 with the IRC5-system extended with an open control interface. It is verified that the proposed redesign allows significantly reduced deviations of the actual trajectories from the desired one at high speeds not only for a chosen base feedback design but also outperforming the state-of-theart commercial implementation offered by ABB Robotics.

2011

This paper presents a method for developing robot trajectories that achieve minimum energy consumption for a point-to-point motion under kinematic and dynamic constraints. The method represents trajectories as a fourth degree B-spline function. The parameters of the function are optimised using a multi-parametric optimization algorithm. Actuator torques have been considered for the formulation of the cost function, which utilizes an inverse dynamics analysis. Compared to other trajectory optimization techniques, the proposed method allows kinematic and dynamic constraints to be included in the cost function. Thus, the complexity and computational effort of the optimization algorithm is reduced. A two-link simulated robot manipulator is used to demonstrate the effectiveness of the method.

2012

Journal of Mechanisms and Robotics, 2011

In this paper, an experimental analysis and validation of a minimum time-jerk trajectory planning algorithm is presented. The technique considers both the execution time and the integral of the squared jerk along the whole trajectory, so as to take into account the need for fast execution and the need for a smooth trajectory, by adjusting the values of two weights. The experimental tests have been carried out by using an accelerometer mounted on a Cartesian robot. The algorithm does not require a dynamic model of the robot, but just its mechanical constraints, and can be implemented in any industrial robot. The outcomes of the tests have been compared with both simulation and experimental results yielded by two trajectory planning algorithms taken from the literature.