SUMMARYThe Inverse Kinematics (IK) problem of manipulators can be divided into two distinct steps: (1) Problem formulation, where the problem is developed into a form which can then be solved using various methods. (2) Problem solution, where the IK problem is actually solved by producing the values of different joint space variables (joint angles, joint velocities or joint accelerations). The main focus of this paper is concentrated on the discussion of the IK problem of redundant manipulators, formulated as a quadratic programming optimization problem solved by different kinds of recurrent neural networks.

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SUMMARY Fossil fuel sources are well suited to fulfill the energy needs of human beings. Unfortunately, there are some limitations and disadvantages pertaining to fossil fuels, some of which are drastic. The main issues are: firstly, there is a finite supply of these fuels, eventually this supply will be exhausted; secondly, burning fossil fuels contributes to global warming, leading to disastrous consequences for the environment and the health of humans. Switching to renewable energy sources is the viable solution to the aforementioned issues. Robots bring numerous benefits in a wide variety of applications. Introducing robots to production environments and other applications results in a remarkable improvement in terms of productivity and efficiency. In this paper, the integration between robots and renewable energy sources is discussed. In other words, two main points are investigated: (1) how can renewable energy be a viable source of energy for robots and (2) how can the renewable energy industry benefit from utilizing robots in the execution of renewable energy-related tasks. Some of the recent developments concerning the integration between robots and renewable energy are reviewed. In addition, more opportunities and expected advancements are also discussed.