International Journal of Robotics
Volume:7 Issue: 1, Spring 2021

The positioning of robots, relative to the origin of coordinates, is a crucial issue for autonomous robots. The purpose of the positioning is to find Cartesian coordinates and to position the robot body in a global coordinate system. In this paper, an image-based approach is proposed to robots positioning. In this approach, the pixels for the lines in the ground are specified in the original image. These pixels are replaced by a numerical value of zero and other pixels with a numerical value of one. The image obtained from these points is converted to an image taken from the top view using a reverse perspective transform. Then using the Hough line, the angle of the longest sequence is obtained from the zero values. This angle is used to correct changes resulting from the rotation of the image. In the next step, the information obtained is processed as a matrix containing zero and one using the Particle Swarm Optimization (PSO) algorithm and the coordinates of the location of the robot are determined from the origin. In this paper, an efficient target function is proposed for use in the PSO algorithm. The most important feature of this approach is the use of an Inverse Perspective Map (IPM) transformation to eliminate perspective effects. This method is resistant to changing the size and shape of various forms within the ground. To test the proposed method, positioning for soccer robots is used. The experiments show that the proposed approach has high accuracy in detecting the robot position. The main application of this algorithm is the positioning of airplanes and military missiles based on aerial imagery without the need for a global positioning system (GPS). It can also be used to increase the accuracy of the global positioning system.

Spherical robots provide a mean for extensively mobile robot research and studies. Due to their special attributes such as compact structure, omnidirectional and flexible movement, They have been successfully exploited in robotic and control discipline rather than conventional robots which consume much more energy. Even though numerous methods have been adopted to design the Inside Drive Unit (IDU), pendulum structure has been widely employed, given that it might alleviate the complexity either in the process of implementing the mechanical structure and designing the control scheme. The mathematical equations of ball-shaped robots are extremely nonlinear, and they are regarded as highly under-actuated and non-holonomic systems so that there are some relative complexities for dynamic equations to be calculated by the conservative knock on methods. Hence, the main focus of this paper is to experimentally determine the dynamic model of the robot by adopting offline approximation approaches. In this paper, a spherical robot equipped with a pendulum - driven is designed and constructed. The robot is programmed in which it is able to be maneuvered around manually by a remote control device. In the automatic control process, two control schemes are designed to guarantee the trajectory tracking and stability of the robot. The discrepancy between the first and second strategies is that in the former scheme, the dynamics model of the robot based on the Lagrangian method is proposed but in the later scheme, the transform functions between the driving motors and angular velocities are derived experimentally. For both control systems, however, the PID controller provides a mean to ensure the trajectory tracking of the robot. Experimental results depict compared with the control scheme in which the dynamic model is calculated by the Lagrangian method, the trajectory tracking generated by the transform function is more effective and it performs sufficiently more accurate.

Designing a walking gait for biped robots, that can preserve stability against a known range of disturbances, is very important in real applications. In the area of biped robots with point-feet, designing an exponentially stable walking gait with desired features has been recently done by an online reinforcement learning method called PI^2-WG. However, the designed gait might not be robust enough against disturbances. Therefore, we extend a robust version of PI^2-WG to design an exponentially stable walking gait which is robust against modeling errors/disturbances and we call it R-SPI^2-WG. It is done by minimizing the costs of worst rollouts which are generated in presence of different modeling errors/disturbances. We study the ability of the proposed method to adapt the controller of RABBIT, which is a planar biped robot with point-feet, for some robust applications. The simulation results show that the designed gaits are exponentially stable and robust against modeling errors/disturbances in a feasible range.

In this paper, an algorithm is presented for a swarm motion stability based on Lagrange equations. Having virtual energy sources, the mentioned algorithm is designed and applying energy values to Lagrange equations the swarm members move toward the desired target point. Moreover, the presented stability algorithm has been generalized to prevent collision between members of the swarm as well as avoid collision with obstacles and two repulsive operators have been designed to guaranty the safety of the swarm members along the path. Arriving of all members at the target point, an aggregation switch is designed for members’ aggregation. Prioritizing on experimental works, this feature enables the swarm members move more freely and cover a greater area along the path. It is also possible to define and arrange virtual obstacles in any desired layouts (e.g., narrow corridor) in order to achieve different goals such as avoiding an area, guiding the swarm in the desired direction, etc. the presented algorithm is suitable for identification, navigation, search and rescue, protection, etc. Using MATLAB software this algorithm is simulated and validated for the movement of swarm robots in both two- and three-dimensional spaces covering different conditions. The simulation results demonstrate the capabilities and efficiency of the presented algorithm for application in swarm motion.

A haptic simulation of the corneal incision is implemented based on a validated mathematical model of the corneal cutting process. The experimental setup measures force in three phases of pre-cutting, cutting, and relaxation. The mechanical behavior of the corneal incision is modeled mathematically from the experiments. The haptic model is characterized by the behavior of the ovine corneal tissue in sequential phases. In the pre-cutting phase, the force increases until the instrument tip penetrates into the cornea. Then, a reduction in the force indicates the onset of the cutting phase after which the force remains constant. At the relaxation phase, the force returns to zero. The numerical results of the haptic simulation show that the maximum force error predicted by the model is 0.016 N for the keratome velocity of 2 mm/s and the root mean square of the error is 0.004 N.

A new framework of synchronized adaptive fuzzy sliding mode control (AFSMC) approach for a network of under-actuated systems (UASs) under communication time delay is presented here. The basic equations of motion of each agent for controller design and information exchange paradigm among them are considered as cascaded normal form and master/slave, respectively. A fuzzy system is applied to determine the equivalent part of the controller which is based on classical sliding mode control (SMC). Then, its robust part is improved in comparison with the conventional AFSMC so as to synchronize the agents to the leader’s state. In addition to synchronization, the proposed AFSMC improves some properties associated with the transient part of the response, especially rise-time, significantly. The proposed scheme is robust against uncertainties and unknown communication time delay, as well. Also, its implementation is so simple that different UASs can be replaced, easily. Moreover, the presented controller is completely model-free for UASs with strict feedback form dynamics and less-dependent on the dynamics of UASs with cascaded normal form.