Enhancement of Motionability Based on Segregation of States for Holonomic Soccer Robot

One of the critical issues when navigating wheeled robot is the ability to move effectively. Omnidirectional robots might overcome these nonholonomic constraints. However, the motion planning and travel speed of the movement has been in continuous research. This study proposed segregation of states to improve the holonomic motion system with omnidirectional wheels, which is specially designed for soccer robots. The system used five separate defined states in order to move toward all directions by means of speed variations of each wheel, yielding both linear and curved trajectories. The controller received some parameter values from the main controller to generate robot motion according to the game algorithm. The results show that the robot is able to move in an omnidirectional way with the maximum linear speed of 3.2 m/s. The average error of movement direction is 4.3°, and the average error of facing direction is 4.8°. The shortest average time for a robot to make a rotational motion is 2.84 seconds without any displacement from the pivot point. Also, the robot can dribble the ball forward and backward successfully. In addition, the robot can change its facing direction while carrying the ball with a ball shift of less than 15 cm for 5 seconds. The results shows that state segregations improve the robots capability to conduct many variations of motions, while the ball-handling system is helpful to prevent the ball gets disengaged from the robot grip so the robot can dribble accordingly

Gyroscopic Precession In Motion Modelling Of Ball-Shaped Robots

This study discusses kinematic and dynamic precession models for a rolling ball with a finite contact area and a point contact respectively. In literature, both conventions have been applied. In this paper, we discuss in detail the kinematic and dynamic models to describe the ball precession and the radius of a circular rolling path. The kinematic model can be used if the contact area and friction coefficient are sufficient to prevent slippage. The dynamic precession model has significance in multi-body simulation environments handling rolling balls with ideal point contacts. We have applied both the kinematic and dynamic precession model to evaluate the no-slip condition of the existing GimBall-robot. According to the result, the necessity of an external precession torque may cause slipping at lower velocities than expected if ignoring this torque.Peer reviewe

Graph-Based Classification of Omnidirectional Images

Omnidirectional cameras are widely used in such areas as robotics and virtual reality as they provide a wide field of view. Their images are often processed with classical methods, which might unfortunately lead to non-optimal solutions as these methods are designed for planar images that have different geometrical properties than omnidirectional ones. In this paper we study image classification task by taking into account the specific geometry of omnidirectional cameras with graph-based representations. In particular, we extend deep learning architectures to data on graphs; we propose a principled way of graph construction such that convolutional filters respond similarly for the same pattern on different positions of the image regardless of lens distortions. Our experiments show that the proposed method outperforms current techniques for the omnidirectional image classification problem

Human-powered vehicle capable of movement in the longitudinal and lateral directions

Human-powered vehicles, especially conventional wheelchairs, are essential tools for people with lower body disability. But their movement in a lateral direction is limited or impossible, which burdens users who want to change directions, especially in a narrow space. Thus, a human-powered vehicle that can move in a lateral direction is required. To move in any direction, many motor-driven omnidirectional vehicles have been proposed, but humans cannot manually power their mechanisms. To solve this problem, we are developing a human-powered vehicle, that is, driven by hands of the rider, that can move in both the longitudinal and lateral directions. This paper proposes such a vehicle, which has a mechanism to move in the lateral direction like people can do while walking. We designed it so that riders can operate its mechanism by analyzing the space reachable by the rider’s palms where they can effectively exert power. We constructed a prototype and conducted experiments to confirm that the vehicle moves as expected with relatively low effort. In the experiments, we confirmed the validity of vehicle operation by comparing the moving time of the vehicle with and without the lateral translation function for different travel distances and passage widths. Our results showed that the proposed vehicle moves more quickly or requires shorter moving distance in comparison with a conventional wheelchair because of the lateral movement function. In addition, we found that the threshold for utility of the function is whether the passage width is larger than the vehicle diagonal length