Spacecraft formation-flying using potential functions

A group of small spacecraft able to change their relative position and attitude through the use of the potential function method is discussed. The spacecraft shapes, sizes and manoeuvring capabilities are not identical, although all are assumed to manoeuvre using continuous thrusters. A hyperbolic form of the attractive potential function is used to reduce actuator effort by using natural orbital motion to approaching the goal configuration. A superquadric repulsive potential with 3D a rigid object representation is then used to provide an accurate representation of the shape of spacecraft in the potential function. As the spacecraft start away from their goal, a parabolic attractive potential is inefficient as the control force increases with distance from the goal. Using a hyperbolic attractive potential, the control force is independent of the distance to goal, ensuring smooth manoeuvring towards the goal with a bound actuator effort

Realization of reactive control for multi purpose mobile agents

Mobile robots are built for different purposes, have different physical size, shape, mechanics and electronics. They are required to work in real-time, realize more than one goal simultaneously, hence to communicate and cooperate with other agents. The approach proposed in this paper for mobile robot control is reactive and has layered structure that supports multi sensor perception. Potential field method is implemented for both obstacle avoidance and goal tracking. However imaginary forces of the obstacles and of the goal point are separately treated, and then resulting behaviors are fused with the help of the geometry. Proposed control is tested on simulations where different scenarios are studied. Results have confirmed the high performance of the method

A Passivity-Based Distributed Reference Governor for Constrained Robotic Networks

This paper focuses on a passivity-based distributed reference governor (RG) applied to a pre-stabilized mobile robotic network. The novelty of this paper lies in the method used to solve the RG problem, where a passivity-based distributed optimization scheme is proposed. In particular, the gradient descent method minimizes the global objective function while the dual ascent method maximizes the Hamiltonian. To make the agents converge to the agreed optimal solution, a proportional-integral consensus estimator is used. This paper proves the convergence of the state estimates of the RG to the optimal solution through passivity arguments, considering the physical system static. Then, the effectiveness of the scheme considering the dynamics of the physical system is demonstrated through simulations and experiments.Comment: 8 pages, International Federation of Automatic Conference 2017, 8 figure

Potential Field Based Motion Planning with Steering Control and DYC for ADAS

In this study, the development of motion planning and control for collision avoidance driver assistance systems is presented. A potential field approach has been used in formulating the collision avoidance algorithm based on predicted vehicle motion. Then, to realize the advanced driver assistance systems (ADAS) for collision avoidance, steering control system and direct yaw moment control (DYC) is designed to follow the desired vehicle motion. Performance evaluation is conducted in simulation environment in term of its performance in avoiding the obstacles. Simulation results show that the vehicle collision avoidance assistance systems can successfully complete the avoidance behavior without colliding

Unaprijeđeni algoritam za praćenje putanje na neravnoj cesti

The path planning problem is an important problem in the research area of robot, games and group animation. This paper shows a 2.5-dimensional terrain grid which can reduce the amount of computation. By applying the fuzzy logic theory, the terrain trafficability of the rugged road can be evaluated based on different gradient, roughness, elevation difference; the trafficability factor can be achieved and applied to the heuristic function. The improved algorithm can solve the symmetry problem of path planning on uneven surfaces, reduce the search space.Problem planirana putanje je važan problem u istraživačkom području robotike, igara i grupne animacije. U ovom radu teren je predstavljen 2.5-dimenzionalnom mrežom što može smanjiti vrijeme računanja. Korištenjem teorije neizrazite logike prohodnost neravne ceste može se procijeniti na osnovu razlike gradijenata, nagiba i grbavosti, te se može odrediti faktor prohodnosti koji je primijenjiv na heurističku funkciju. Unaprijeđeni algoritam može riješiti problem simetrije kod planiranja putanje na neravnim površinama i smanjiti prostor pretraživanja

Robot localization and path planning based on potential field for map building in static environments

In static environments, and regarding the landmarks also as obstacles in the given situation, this paper suggests a map building algorithm of simultaneous localization and path planning based on the potential field. The robot can locate its movement control discipline with the help of a potential field theory and by conducting simultaneous localization and mapping; besides, the following prediction and state estimation will be done based on predicted control law. With the method of path planning in the potential field, the minimum influential range of  space obstacles with repulsive potential can be adjusted, which is in adaptation to the landmarks and environments in which the landmarks are simultaneously regarded as obstacles. The experiments show that the suggested algorithm, through which the robot  can conduct simultaneous localization and mapping in the localized landmarks, is also at the same time used as an obstacle in environments. After analyzing relevant performance indicators, the suggested algorithm has been verified as consistent estimation