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Based on Robot's intelligent behavior of exploring the unknown environment, a fuzzy controller is built to complete the local path planning. Because of walking around swing and going into local minima problems, a method based on particle swarm optimization for fuzzy controller is proposed. The method utilizes the PSO algorithm to optimize the threshold of the fuzzy membership functions thus the parameters...
The planning method for robot arm probing is one of the key technologies in Chang'E-3 mission, which forms the basis of lunar scientific exploration. This paper presents a vision-based robotic planning method which is applied in the Chang'E-3 mission with two steps. First, the position information of the probing point in the working environment is obtained by matching the stereo images of the hazard...
Continuum robot has potential to run freely through a cluttered environment as aircraft fuel tank. To improve manual maintenance, we designed an aircraft fuel tank inspection robot which was composed of cable-driven sections. A suitable path is essential for the robot to reach the target zone while avoiding obstacles, but path planning for continuum robot is a challenge due to their complex kinematics...
In this paper, we proposed a 3D path planning method for a miniature robotic system, which can manipulate a beam of ultra-short pulse laser to cut a decayed tooth to formulate an expected 3D shape. Using high resolution STereo Lithography (STL) models of the original decayed tooth and the target preparing shape as the input, our method consists of a fast slicing algorithm and an optimized path generating...
This paper investigates the problem of finding shortest paths through 3-dimensional cluttered environments. In particular, an algorithm is presented that determines the shortest path between two points in an environment with obstacles which can be implemented on robots with capabilities of detecting obstacles in the environment. As knowledge of the environment is increasing while the vehicle moves...
In this paper we introduce a new language in which discrete path planning problems for mobile robots can be specified and solved. Given an environment represented as a graph and a Boolean variable for each vertex to represent its inclusion/exclusion on the path, we consider the problem of finding the shortest path (or tour) in the graph subject to a Boolean satisfiability (Sat) formula defined over...
Most path planning methods for mobile robots divide the environment in two areas - free and occupied - and restrict the path to lie entirely within the free space. However, the problem of path planning in rough terrain for a field robot, e.g. tracked wheel, is still a challenging problem, for which those methods cannot be directly applied. This paper addresses the problem of path planning on rough...
By developments of robotics and increments in utilizing this knowledge in different scientific and industrial branches, the issue of path planning, either in intelligent and online state, or by pre-determined algorithms has been arised as one of the discussion fields in control and specially robotics. In the path planning literature, several algorithms have been used repetitively, among which can...
Path planning investigates issues including the shortest path, obstacle avoidance, and computation efficiency, which can be regarded as an optimal problem. Taking advantage of the genetic algorithms to solve various optimal problems, this paper first proposes a Cooperative Genetic Optimization (CGO) Algorithm, including the establishment of an elite policy and larger selection region to minimize the...
Vision based observation of a moving target is one of the important problems and hot issues of mobile robot system. Dynamical vision sensors which is constituted with multiple robots to obtain improved observational results has been shown to be a good substitution of single vision sensors. Thus, a new active cooperative observation (ACO) method based on two dynamical vision sensors is proposed. The...
Neuromorphic Engineering is an interdisciplinary field which combines concepts from fields such as biology, neuroscience, computer science and engineering. The goal of this field is to design systems that are based on the principles of biological nervous systems. This paper presents hardware results for path planning using a neuron array integrated circuit. The algorithm is explained and experimental...
Online path planning for multi-robots in complicated and dynamic environments is a difficult and hot issue in the field of robotics. Many traditional path planning methods cannot meet the requirements of online and real-time processing. Neuro-dynamics-based method has an aptitude for online and real-time path planning in complicated and dynamic environments. However, this method still has shortcomings...
To better solve the optimization problem of fuzzy neural network (FNN), a kind of method based on artificial fish swarm algorithm (AFSA) is proposed in this paper. Aiming at the structure optimization problem of FNN, AFSA-FNN1 is established and realizes the simplification of fuzzy rules. Aiming at the parameter optimization problem of FNN, AFSA-FNN2 is built and realizes the acquisition of parameters...
This paper attempts to propose an efficient algorithm for global optimized path planning for autonomous robotics system, particularly land-based mobile robot. The presented approach relies on a modified visibility-graph, a classic roadmap of combinatorial planning in computer geometry which is able to retain the complete-feature as well as to reduce computation time, especially in the situation of...
This paper proposes a new adaptive Pareto-ranking for multiobjective genetic algorithms. The ranks are assigned after splitting the population in several groups, based on the current weak nadir point and the average objective values. This grouping supplements the sorting provided by the dominance analysis and gives the possibility to encourage certain valuable solutions recommended by the particular...
3D Terrain understanding and structure estimation is a crucial issue for robots navigating rescue scenarios. Large scale 3D point clouds, even if crisp and yielding a detailed representation of the scene, provide no information about what is ground, and what is top, what can be surmounted and what can be not, what can be crossed, and what is too deep to be traversed. In this work, we propose a new...
Unmanned autonomous systems offer safety benefits for potentially hazardous environments. The evaluation of the performance of such systems is challenging because hazardous environments, i.e. due to flood or fire, are constantly changing. In this paper we introduce a system for simulation-based risk assessment of a fleet of autonomous machines performing a rescue mission. The simulation is based on...
As a swarm intelligence, ant colony algorithm (ACA) is widely used to solve the path planning problem. But ACA applied to the path planning has some disadvantages such as fall into local optimization easily and low convergence. In order to overcome these defects, we improved the ant colony algorithm by changing heuristic factor. The experiment results indicate that the improved algorithm performs...
The artificial potential field is one of the most popular algorithms in the robot path planning. The algorithm's structure is simple and the algorithm implement quite easily. However, the traditional artificial potential field algorithm have a local minimum problem, which can trap mobile robots before reaching its goal. Meanwhile, as there are some obstacles near the goal point, the repulsive force...
Multi-agent systems and stereo vision navigation is a challenging area in Robotic research. The task can be widely scalable and optimized for a specific application. An efficient centralized heterogeneous swarm robotic system is proposed and implemented for digital elevation mapping of an unknown terrain using stereo vision. The utility of vision sensors compared to other sensor systems is shown in...
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