This paper presents a system that detects a path of moving obstacle that appear in the path of a navigating robot. The objective of the system is to avoid collision between mobile robot and moving obstacles. The system uses polar mapping to simplify the segmentation of the moving object from the background. In the transformed space qualitative extimation of moving obstacles is obtained by detec...

For service robots coexisting with humans, both safety and working efficiency are very important. In order for robots to avoid collisions with surrounding obstacles, the robots must recognize obstacles around them. In dynamic environments, not only currently moving obstacles but also movable obstacles should be recognized. In this paper, three types of obstacles, such as stationary, movable and...

We propose a sensor based navigation algorithm for a mobile robot that assures a convergence property when the robot is navigated from a given start position to a goal position while avoiding moving and fixed obstacles. This algorithm guides the robot toward the goal by using its sensor information in an unknown environment. Conventional sensor based navigation algorithms such as Bug algorithm ...

This paper proposes a potential filed immune network (PFIN) for dynamic navigation of mobile robots in an unknown environment with moving obstacles and fixed/moving targets. The Velocity Obstacle method is utilized to determine imminent obstacle collision of a robot moving in the timevarying environment. The response of the overall immune network is derived by the aid of fuzzy system. Simulatio...

This article proposes a new approach for centralized path planning of multiple aircraft in presence of the obstacle-laden environment under low flying rules. The problem considers as a unified nonlinear constraint optimization problem. The minimum time and control investigate as the cost functions and the maximum velocity and power consider as the constraints. The pseudospectral method applies ...

This paper presents a randomized motion planner for kinodynamic asteroid avoidanceproblems, in which a robot must avoid collision with moving obstacles under kinematic, dynamic constraints and reach a specified goal state. Inspired by probabilistic-roadmap (PRM) techniques, the planner samples the state time space of a robot by picking control inputs at random in order to compute a roadmap that...

A new methodology named Evolutionary Artificial Potential Field (EAPF) is proposed for real-time robot path planning. The artificial potential field method is combined with genetic algorithms, to derive optimal potential field functions. The proposed Evolutionary Artificial Potential Field approach is capable of navigating robot(s) situated among moving obstacles. Potential field functions for ...

This paper presents a novel randomized motion planner for robots that must achieve a specified goal under kinematic and/or dynamic motion constraints while avoiding collision with moving obstacles with known trajectories. The planner encodes the motion constraints on the robot with a control system and samples the robot’s state×time space by picking control inputs at random and integrating its ...

This paper addresses the problem of navigation of complex systems in dynamic environments under uncertainty. Such environments impose a hard real time constraint. However, computing a complete motion to the goal within a limited time is impossible to achieve in most real situations. The Partial Motion Planning (PMP) approach presented in [1] is used to address the planning problem. However, for...

A sensor based navigation algorithm for a mobile robot which assures a convergence property is proposed when the robot is navigated from a given start position to a goal position while avoiding moving and fixed obstacles. This algorithm guides the robot toward the goal by using its sensor information in an unknown environment. Conventional sensor based navigation algorithms such as Bug algorith...