Controlling the Motion of an Autonomous Mobile Robot Using Various Techniques: a Review

Abstract

Autonomous navigation of mobile robots in an uncertain and complex environment is a broad and complicated issue due to a variety of obstacles that mobile robots have to detect and represent in their maps to navigate safely. The objective of the navigation-mobile robot is to obtain an optimum path, meaning that the robot should plan a reliable path between the source point and the target point without colliding with the static and dynamic obstacles found in an uncertain and complex environment. Several efficient techniques have been developed by researchers in the motion planning of mobile robots. This paper presents detailed analysis of various techniques used in the autonomous navigation of mobile robot.

A constrained A* approach towards optimal path planning for an unmanned surface vehicle in a maritime environment containing dynamic obstacles and ocean currents

“…A substantial amount of research has been conducted in the area of path planning of unmanned surface vehicles. Path planning for USVs can be classified into two categories, namely, reactive approaches (Khatib, 1986, Borenstein and Koren, 1991, Mohanty and Parhi, 2013, Fiorini and Shiller, 1998 where vehicles makes decision en route and deliberative approaches where vehicles follows a predetermined path (Hart et al, 1968, Holland, 1992, Kennedy, 2011. Several computational approaches comprising of evolutionary methods such as Genetic Algorithm (GAs) or Particle Swarm Optimisation (PSO) (Zeng et al, 2015, Aghababa, 2012, graph search techniques (Garau et al, 2005, Singh et al, 2017a, artificial potential field (APF) (Warren, 1990, Singh et al, 2017b and fast marching (FM) (Liu et al, 2017, Petres et al, 2007 have been applied in path planning of marine vehicles.…”

“…In order to save energy, avoid the collision and to increase the endurance of USVs enabled with limited computational resources, it is important to plan the USVs voyage in advance before the mission commences by considering environmental effects and dynamic obstacles in path planning of USVs. Traditionally, grid search techniques have been found most efficient in generating path in fastest computation time compared to other reactive approaches adopted in path planning of robots (Mohanty and Parhi, 2013).…”

Application of artificial neural network for control and navigation of humanoid robot

“…Deepak et al [26][27][28][29] used artificial immune based and other related approach in mobile robot navigation. Mohanty et al [30][31][32][33] developed different nature inspired algorithms for smooth planning of mobile robot navigation. Elliot et al [34] have conducted several experiments for the accomplishment of a new control architecture design for the mobile robots which help in the autonomy of disabled people.…”

A Comparative Study: Modified Particle Swarm Optimization and Modified Genetic Algorithm for Global Mobile Robot Navigation

“…Each method has its own strength over the others in certain aspects, researchers have been seeking for more efficient ways to solve this problem. In this section, the recent works on robot's navigation and path planning are reviewed [5]. (Dutta, 2010) deal with the obstacle avoidance of a wheeled mobile robot in structured environment by using PSO based neuro-fuzzy approach, and three layer neural networks with PSO were used as learning algorithm to determine the optimal collision-free path [6].…”