# Trajectory Planning for Intelligent Robotic and
## 2 Special Issue  
This Special Issue collects papers in open-access format on a broad number of aspects of trajectory planning for intelligent robotic and mechatronic systems introduced above. The call for the Special Issue \"Trajectory Planning for Intelligent Robotic and Mechatronic Systems\" received 15 manuscripts, 12 of which were accepted for publication. In most of thearticles, numerical simulations are corroborated by experimental results. The contributions are listed below in order of publication. Contribution 1 presents a research study on the trajectory and operational performance of a wheel loader automatic shoveling. A test platform for the operational performance of loaders is developed, and nine parallel shoveling trajectories of different depths are designed and compared in terms of total time, fuel and energy consumption, as well as operation resistance. In Contribution 2, the authors describe the implementation and experimental validation of an obstacle avoidance algorithm using the UR5e robot. An error analysis of simulation and experiments allows one to conclude that the developed approach was effectively applied to a real collaborative robotic system, exhibiting behavior similar to what simulations predicted. Another work dealing with a collaborative robotic application can be found in Contribution 3, where a bin-picking task is enhanced to achieve a successful and fluent collaboration between human and robot. Experimental results show that the use of a robot in collaboration with a human operator can be particularly useful to overcome typical bin picking failures and to improve the fault tolerance of the system, increasing its flexibility and reducing down times. The authors of the paper in Contribution 4 illustrate the application of a motion profile with elliptic jerk to the Cartesian space position control of serial robots. A SCARA-like manipulator with four degrees of freedom (DOFs) and elastic balancing is considered, and both integer-order and fractional-order controllers are applied to simulate the behavior of the robot using the elliptic jerk profile. The influence of joint stiffness and motion time on the trajectories of underactuated robots is analyzed in Contribution 5. More in detail, trajectories for a 3-DOF robot moving in the horizontal plane with two actuators and a torsional spring are planned, and combinations of torsional stiffness and motion time that minimize the motion torques or the swept area are discussed. The paper in Contribution 6 provides a comprehensive review on use of reinforcement learning for dynamic obstacle avoidance and path planning algorithms. Publications from the last 5 years (2018-2022) are collected and analyzed to evaluate the latest trends in mobile robotics using reinforcement learning, including a discussion on performance metrics and research gaps in this field. In Contribution 7, an approach for frame-based slip detection for an underactuated robotic gripper for assistance of users with disabilities is presented. The proposed method effectively handles common issues associated with purely vision-based slip detection methods, such as optical path occlusion or compliant objects, showing high performance in terms of accuracy and robustness against changes of the environment. Contribution 8 proposes a technique for positioning applications that involves employing a platform subjected to planar oscillations along circular, elliptical, and complex trajectories. Dynamic and mathematical models of the motion of a small object on the platform were developed to investigate the motion characteristics of the part by controlling frequency and amplitude of the excitation force. In Contribution 9, different learning methods based on artificial neural networks are examined to replace the default speed controller for high-precision position control and drift attenuation in robotic manipulators.