Optimization of the PID coefficients for the line-follower mobile robot controller employing genetic algorithm

O b j e c t i v e s. To develop a control system for the movement of a mobile robot along a color-contrast line, as well as to find the values of the coefficients of a proportional-integral-differentiating (PID) controller that allows the robot to move along the line at a given speed.M e t ho d s. To adjust the values of the coefficients of the PID controller, methods of enumeration, automatic tuning and a genetic algorithm are used.Re s u l t s. A software package for tuning the PID controller of the educational mobile robot RoboCake, designed to move along a closed color-contrast line at a given speed, has been developed. The software package consists of a simulation model of the specified robot in the Simulink environment, several virtual traces-polygons and a specialized solver based on the developed genetic algorithm. With the help of the proposed fitness function, a mobile robot control system that satisfies the stated conditions is implemented. Based on the conducted model experiments, the desired values of the parameters of the PID controller are obtained.Co n c l u s i o n. A comparison of the effectiveness of various methods of tuning the PID controller is carried out. The developed software package is designed to solve the practical problem of moving a mobile robot along a color-contrast line at a speed of 1 m/s. The results obtained can be used to study methods of evolutionary tuning of stabilization systems for transport robots, ensuring their movement without overshoot.

Customizing skills for assistive robotic manipulators, an inverse reinforcement learning approach with error-related potentials

Robotic assistance via motorized robotic arm manipulators can be of valuable assistance to individuals with upper-limb motor disabilities. Brain-computer interfaces (BCI) offer an intuitive means to control such assistive robotic manipulators. However, BCI performance may vary due to the non-stationary nature of the electroencephalogram (EEG) signals. It, hence, cannot be used safely for controlling tasks where errors may be detrimental to the user. Avoiding obstacles is one such task. As there exist many techniques to avoid obstacles in robotics, we propose to give the control to the robot to avoid obstacles and to leave to the user the choice of the robot behavior to do so a matter of personal preference as some users may be more daring while others more careful. We enable the users to train the robot controller to adapt its way to approach obstacles relying on BCI that detects error-related potentials (ErrP), indicative of the user’s error expectation of the robot’s current strategy to meet their preferences. Gaussian process-based inverse reinforcement learning, in combination with the ErrP-BCI, infers the user’s preference and updates the obstacle avoidance controller so as to generate personalized robot trajectories. We validate the approach in experiments with thirteen able-bodied subjects using a robotic arm that picks up, places and avoids real-life objects. Results show that the algorithm can learn user’s preference and adapt the robot behavior rapidly using less than five demonstrations not necessarily optimal.

The model relates to an substation inspection robot carrying a Unmanned Aerial Vehicle

A kind of substation inspection robot carrying unmanned aerial vehicle(UAV) was studied to solve the problems of complex indoor environment of substation, high intensity of manual inspection and low efficiency of traditional inspection method. Using robot mobile platform connected to the robot controller of ontology, the robot controller of ontology through wireless router and background monitoring system for information transmission and according to the background monitoring system control command control robot mobile platform preset in the transformer substation inspection lines and parking. Walking on the robot mobile platform is equipped with the UAV. Wireless information transmission between the UAV and the robot body controller, take-off and landing controlled by the robot body controller and the camera component on the UAV takes pictures of the equipment and instruments of the substation so as to complete the substation inspection work safely and reliably.

Digital Twin for FANUC Robots: Industrial Robot Programming and Simulation Using Virtual Reality

A Digital Twin is the concept of creating a digital replica of physical models (such as a robot). This is similar to establishing a simulation using a robot operating system (ROS) or other industrial-owned platforms to simulate robot operations and sending the details to the robot controller. In this paper, we propose a Digital Twin model that assists in the online/remote programming of a robotic cell by creating a 3D digital environment of a real-world configuration. Our Digital Twin model consists of two components, (1) a physical model: FANUC robot (M-10iA/12), and (2) a digital model: Unity (a gaming platform) that comes with specialized plugins for virtual and augmented reality devices. One of the main challenges in the existing approach of robot programming is writing and modifying code for a robot trajectory that is eased in our framework using a Digital Twin. Using a Digital Twin setup along with Virtual Reality, we observe the trajectory replication between digital and physical robots. The simulation analysis provided a latency of approximately 40 ms with an error range of −0.28 to 0.28∘ across the robot joint movements in a simulation environment and −0.3 to 0.3∘ across the actual robot joint movements. Therefore, we can conclude that our developed model is suitable for industrial applications.

A Wearable IMU System for Flexible Teleoperation of a Collaborative Industrial Robot

Increasing the accessibility of collaborative robotics requires interfaces that support intuitive teleoperation. One possibility for an intuitive interface is offered by wearable systems that measure the operator’s movement and use the information for robot control. Such wearable systems should preserve the operator’s movement capabilities and, thus, their ability to flexibly operate in the workspace. This paper presents a novel wireless wearable system that uses only inertial measurement units (IMUs) to determine the orientation of the operator’s upper body parts. An algorithm was developed to transform the measured orientations to movement commands for an industrial collaborative robot. The algorithm includes a calibration procedure, which aligns the coordinate systems of all IMUs, the operator, and the robot, and the transformation of the operator’s relative hand motions to the movement of the robot’s end effector, which takes into account the operator’s orientation relative to the robot. The developed system is demonstrated with an example of an industrial application in which a workpiece needs to be inserted into a fixture. The robot’s motion is compared between the developed system and a standard robot controller. The results confirm that the developed system is intuitive, allows for flexible control, and is robust enough for use in industrial collaborative robotic applications.

Design of Fin-Curvature-Based Feedback Controller for Efficient Swimming

Over the past few decades, biologists and engineers have attempted to elucidate the swimming mechanism of fish and developed a fish-like robot to perform fast swimming in water. Such a robot will have wide applicability in investigations and exploration in the sea. There have been many studies on fish-type robots; however, the propulsion efficiency of the introduced robots is far from that of the actual fish. The main reason is that the robot controller for generating motions is conventionally designed by trial and error, and little attention has been placed on designing a motion controller that matches the body structure of a real fish. In this paper, we present an approach that uses fin-curvature-based feedback to design a motion controller. A swimming robot composed of a body with two actuated joints and a flexible tail fin is developed. After examining the relationship between the swimming speed and tail fin curvature in feedforward (open-loop) system experiments, we propose to reflect the tail fin curvature to the actuation inputs (phase difference between the two cyclic oscillations), which will perform the efficient swimming motion. Further, the results show that implementing the proposed feedback controller in a fish-type robot makes it swim similar to a real fish. In addition, the proposed controller functions to find inappropriate actuation according to the body structure.

Sit-To-Stand and Stand-To-Sit Energetics for Assistive Devices and Robotics Design

This research presents the development of a Sit-to-Stand and Stand-to-Sit model for regenerative energy recovery with applications in orthoses, protheses and humanoid robot design. Sit-to-Stand and Stand-to-Sit are routine activities and are crucial pre-requisites to walking and running. Determining design parameters for devices which can aid people to perform these activities in an effective manner is a key goal here. MapleSim was used to simulate a 1/10-scale multi-domain model and a nonlinear torque controller was used to control the trajectory profiles of the Sit-to-Stand-to-Sit gait. The model allows accurate simulation of hardware components for use in a future robot. This study addresses the usage in regenerative braking towards sit-to-stand-to-sit and the relationship between Coriolis/centrifugal torque components to inertial and gravitational torque components. This study examines the level of regeneration at ankle, knee and hip. Furthermore, it examines the significance of Coriolis and centrifugal versus inertial and gravitational components of a nonlinear controller in order to determine if these components would be needed in a real robot controller. By applying joint trajectories from human trials it was found that the regenerative effect in the robot model was most significant in the hip and least significant in the ankle. Furthermore, we determined that the Coriolis and centrifugal terms were approximately 1% of the inertial and gravitational terms in the applied nonlinear controller, making them insignificant. We also determined upper bounds for gearing in the joints such that battery autonomy is maximized without encountering motor saturation and inaccurate trajectory following. From these findings, we recommend that robot designs neglect the Coriolis and centrifugal terms and that regenerative hardware be prioritized at the hip.