Immune Navigation Control for Stigmergy Based Foraging Behaviour of Autonomous Mobile Robots

Abstract

The paper presents a series of experiments in a simulated environment where two autonomous mobile robots gather randomly distributed objects and cluster them into one pile. The coordination of the robots' movements is achieved through stigmergy (an indirect form of communication through the environment). In order to avoid the drawback of the random moves, necessary for stigmergy based foraging behaviour, the perceptive capabilities of the robots are enhanced by detectors for concentration of objects. An artificial immune network carries out the collision free goal following behaviour. Simulations confirm the improved performance of the foraging behaviour under the proposed immune navigation control. Copyright  2005 IFAC

Emotional Intervention on Stigmergy Based Foraging Behaviour of Immune Network Driven Mobile Robots

“…The problem to solve here is to find a way of speeding up the foraging process, because random movements make the process of formation of the final pile time consuming. Placing simulated detectors for object concentration in order to enhance the perceptive capabilities of the robots is a way of avoiding the loss of time due to wondering in an area without objects, as suggested in the literature (Tsankova et al, 2005;Tsankova et al, 2007). The detectors determine the directions with the maximum and minimum (non-zero) concentrations of pucks (with respect to the robot).…”

“…The robot is equipped with a simple threshold mechanism -a gripper, able to pick up one puck. An additional detector for puck concentration is used to determine the directions (with respect to the robot) with maximum and minimum (non-zero) concentrations of pucks (Tsankova et al, 2005). This information is www.intechopen.com…”

“…The first method relies on random walks and codes the stigmergic principles in simple rules with fixed priorities (Beckers et al, 1994;Tsankova & Georgieva, 2004). The other four methods are characterized with enhanced sensing of puck concentration and include (respectively): (1) simple rules with fixed priorities (Tsankova et al, 2005), (2) an immune network for navigation control (Tsankova et al, 2005;Tsankova et al, 2007), (3) emotionally influenced immune network based navigation, and (4) emotional intervention on an immune navigator and on the picking up/dropping behaviour mechanism. The aim is to evaluate the performance of the robots equipped with the above mechanisms and controls in simulations.…”

“…The following set of rules describes the robot's behaviours, when the puck concentration is taken into account (Tsankova et al, 2005): (Fig.1b) corresponding to the place with the maximum or minimum concentration of pucks, depending on the presence or absence of a puck in the gripper, respectively. The puck concentration detectors determine the direction of the artificial goal.…”

“…In conformity with the immune navigation control, the set of rules of Algorithm II (from rule (1) to rule (5)) is modified so that the first two rules remain unchanged, and the other three are substituted by the following rule (3a) (Tsankova et al, 2005;Tsankova et al, 2007): (3a) If (there are no pucks ahead) OR (there is an obstacle ahead) then turn on the collision free goal following behaviour, realized by an artificial immune network. If there is one puck in the gripper, the direction of the goal G is the direction corresponding to the sector with the maximum number of pucks, and if there is no puck in the gripper -the direction with the minimum puck concentration.…”