This paper proposed a new methodology to solve collision free path planning problem for industrial robot using genetic algorithms. The method poses an optimization problem that aims to minimize the significant points traveling distance of the robot. The behaviour of more two operational parameters – the end effector traveling distance and computational time – is analysed. This algorithm is able...

The ultimate goal in robotics is to create machines which are more independent and rely less on humans to guide them in their operation. There are many sub-systems which may be present in such a robot, one of which is path planning — the ability to determine a sequence of positions or configurations between an initial and goal position within a particular obstacle cluttered workspace. Many clas...

We show that, for a class of systems described by a Lagrangian L(x, ˙ x, t) = 1 2 ˙ x 2 − V (x, t) the propagator K x ′′ , t ′′ ; x ′ , t ′ = e i ¯ h t ′′ t ′ dtL(x, ˙ x,t) D [x(t)] can be reduced via Noether's Theorem to a standard path integral multiplied by a phase factor. Using Henstock's integration technique, this path integral is given a firm mathematical basis. Finally, we recast the pr...

Computation of a collision-free path for a movable object among obstacles is an important problem in the fields of robotics. The simplest version of motion planning consists in generating a collisionfree path for a movable object among known and static obstacles. In this paper, we introduce a two stages evolutionary algorithm. The first stage is designed to compute a collission-free path in a k...

This paper describes a dynamic programming algorithm to solve a family of problems in the reconstruction of evolutionary trees from protein sequence data, that of constructing "minimal" colorings. This dynamic programming formulation can be modified to efficiently enumerate the number of minimal colorings and thereby be used to calculate the average cost of any given edge, where the average is ...

One of the main challenges when developing mobile robots is path planning. Efficient and robust algorithms are needed to produce plans for the movements of the robot. Many classical path planning algorithms depend on geometrically simple environments to achieve good performance, otherwise the paths produced tend to be far from ideal especially when the paths are to be optimized for multiple obj...

Evolutionary computation (EC) techniques have been successfully applied to compute near-optimal paths for unmanned aerial vehicles (UAVs). Premature convergence prevents evolutionary-based algorithms from reaching global optimal solutions. This often leads to unsatisfactory routes that are suboptimal to optimal path planning problems. To overcome this problem, this paper presents a framework of...