A new method for smooth trajectory planning of robot manipulators

A technique for optimal trajectory planning of robot manipulators is presented in this paper. In order to get the optimal trajectory, an objective function composed of two terms is minimized: a first term proportional to the total execution time and another one proportional to the integral of the squared jerk (defined as the derivative of the acceleration) along the trajectory. This latter term ensures that the resulting trajectory is smooth enough. The proposed technique enables one to take into account kinematic constraints on the robot motion, expressed as upper bounds on the absolute values of velocity, acceleration and jerk. Moreover, it does not require the total execution time of the trajectory to be set a priori. The algorithm has been tested in simulation yielding good results, also in comparison with those provided by another important trajectory planning technique.

A technique for time-jerk optimal planning of robot trajectories

Optimal trajectory planning for industrial robots

Reducing the energy consumption of industrial robots (IR) that are used in manufacturing systems has become a main focus in the development of green production systems. This is due to the reality that almost all automated manufacturing processes are using IR as the main component. Thus, reducing the energy consumption of IR will automatically reduce operating costs and CO2 emissions. Therefore, a method for reducing the energy consumption of IR in manufacturing systems is desired. Firstly, this paper presents a literature survey of the research in energy consumption analysis of IR that is used in manufacturing processes. The survey found that current research in this field is focused on the development of simulation models of IR that are able to be used to predict its energy consumption. Secondly, a modular model to analyze power consumption and dynamic behavior of IR is developed. Afterward, an experimental investigation is carried out to validate and estimate the accuracy of the model developed. The investigation shows that the developed modular model can be conveniently used to optimize the industrial robot’s operating parameters, which are commonly needed for production planning and at the process optimization stage. In addition, the investigation shows that the process constraints, environment layout, productivity requirement, as well as the robot payload and operating speed are the key factors that must be considered for optimizing the productivity and efficiency of IR.

Reducing the energy consumption of industrial robots in manufacturing systems

https://www.mdpi.com/2218-6581/6/4/39/pdf

A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems

This paper proposes a technique of iterative dynamic programming to plan minimum energy consumption trajectories for robotic manipulators. The dynamic programming method is modified to perform a series of dynamic programming passes over a small reconfigurable grid covering only a portion of the solution space at any one pass. Although strictly no longer a global optimization process, this iterative approach retains the ability to avoid some poor local minima while avoiding the curse of dimensionality associated with a pure dynamic programming approach. The algorithm has an inherent parallel structure, allowing for reduced computation time on parallel architecture computers. No limiting assumptions are made about the performance index, or function to be optimized. As such, extremely complex functions and constraints are easily handled. Joint actuator and time constraints are considered in this work. The modified dynamic programming approach is verified experimentally by planning and executing a minimum energy consumption path for a Reis V15 industrial manipulator.

Iterative dynamic programming: an approach to minimum energy trajectory planning for robotic manipulators

In Su and Stepanenko (1995), a hybrid adaptive controller for rigid-link electrically-driven robot manipulators was proposed. Semi-global asymptotic stability of the controller was established in the Lyapunov sense. However, there are two limitations in it. One is that the controller requires the joint velocity measurements, that with the required accuracy can be difficult to realize in practical applications. The other one assumes the boundedness of estimated inertia parameters of the manipulator in order to reduce the computation complexity. In this paper, we propose a modification of the hybrid adaptive controller, which eliminate the above-mentioned limitations. Hence the range of applicability of the method in the above article can be greatly broadened. The capabilities of the proposed control strategies are illustrated through computer simulation.

Redesign of hybrid adaptive/robust motion control of rigid-link electrically-driven robot manipulators

In a recent work of the authors (1995), a hybrid adaptive controller for rigid-link electrically-driven robot manipulators was proposed. Semi-global asymptotic stability of the controller was established in the Lyapunov sense. However, there are two limitations in it. One is that the controller requires the joint velocity measurements, that with the required accuracy can be difficult to realize in practical applications. The other one assumes the boundedness of estimated inertia parameters of the manipulator in order to reduce the computational complexity. In this paper, we propose a modification of the hybrid adaptive controller, which eliminate the above mentioned limitations. Hence the range of applicability of the method given previously can be greatly broadened. The capabilities of the proposed control strategies are illustrated through computer simulation.

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Iterative dynamic programming: an approach to minimum energy trajectory planning for robotic manipulators

Redesign of hybrid adaptive/robust motion control of rigid-link electrically-driven robot manipulators

Redesign of hybrid adaptive/robust motion control of rigid-link electrically-driven robot manipulators