Negotiation of goal direction for cooperative transport

In this paper, we study the cooperative transport of a heavy object by a group of robots towards a goal. We investigate the case in which robots have partial and noisy knowledge of the goal direction and can not perceive the goal itself. The robots have to coordinate their motion to apply enough force on the object to move it. Furthermore, the robots should share knowledge in order to collectively improve their estimate of the goal direction and transport the object as fast and as accurately as possible towards the goal. We propose a bio-inspired mechanism of negotiation of direction that is fully distributed. Four different strategies are implemented and their performances are compared on a group of four real robots, varying the goal direction and the level of noise. We identify a strategy that enables effcient coordination of motion of the robots. Moreover, this strategy lets the robots improve their knowledge of the goal direction. Despite significant noise in the robots' communication, we achieve effective cooperative transport towards the goal and observe that the negotiation of direction entails interesting properties of robustness

Artificial Pheromone for Path Selection by a Foraging Swarm of Robots

Foraging robots involved in a search and retrieval task may create paths to navigate faster in their environment. In this context, a swarm of robots that has found several resources and created different paths may benefit strongly from path selection. Path selection enhances the foraging behavior by allowing the swarm to focus on the most profitable resource with the possibility for unused robots to stop participating in the path maintenance and to switch to another task. In order to achieve path selection, we implement virtual ants that lay artificial pheromone inside a network of robots. Virtual ants are local messages transmitted by robots; they travel along chains of robots and deposit artificial pheromone on the robots that are literally forming the chain and indicating the path. The concentration of artificial pheromone on the robots allows them to decide whether they are part of a selected path. We parameterize the mechanism with a mathematical model and provide an experimental validation using a swarm of 20 real robots. We show that our mechanism favors the selection of the closest resource is able to select a new path if a selected resource becomes unavailable and selects a newly detected and better resource when possible. As robots use very simple messages and behaviors, the system would be particularly well suited for swarms of microrobots with minimal abilitie

A Social Approach for Target Localization: Simulation and Implementation in the marXbot Robot

Foraging is a common benchmark problem in collective robotics in which a robot (the forager) explores a given environment while collecting items for further deposition at specific locations. A typical real-world application of foraging is garbage collection where robots collect garbage for further disposal in pre-defined locations. This work proposes a method to cooperatively perform the task of finding such locations: instead of using local or global localization strategies relying on pre-installed infrastructure, the proposed approach takes advantage of the knowledge gathered by a population about the localization of the targets. In our approach, robots communicate in an intrinsic way the estimation about how near they are from a target; these estimations are used by neighbour robots for estimating their proximity, and for guiding the navigation of the whole population when looking for these specific areas. We performed several tests in a simulator, and we validated our approach on a population of real robots. For the validation tests we used a mobile robot called marXbot. In both cases (i.e., simulation and implementation on real robots), we found that the proposed approach efficiently guides the robots towards the pre-specified targets while allowing the modulation of their speed

Group Transport Along a Robot Chain in a Self-Organised Robot Colony

info:eu-repo/semantics/publishe

Group Transport Along a Robot Chain in a Self-Organised Robot Colony

Abstract. We study groups of autonomous robots engaged in a foraging task as typically found in some ant colonies. The task is to find a prey object and a nest object, establish a path between the two, and transport the prey to the nest. Once a path is established

Robotique collective et auto-assemblage:une étude mécatronique

We present a study of collective robotics by including a mechatronics point of view. In the field it is usually claimed that collective robots are simple and relatively cheap because they are produced in large quantities. Instead in our study we show that collective robots are not simple because they need sensors and actuators for additional work. Our experience in designing robots and producing them allows us to analyze the manufacturing costs of different collective robots . We present in this work four robots developed prior and during to this thesis. Chapter 2 concerns the e-puck robot. This is a robot designed for education, however, it is used in research to experiment collective behaviors. The s-bot robot is presented in Chapter 3. This is a robot that has the collective ability to self-assemble to form larger structures and increase its performance. In Chapter 4 we present the marXbot robot. It is a modular robot developed in the laboratory to meet the needs of different research hubs. One of its modules allows it to self-assemble with its teammates and with the robot handbot presented in Chapter 5. The handbot is a robot that can climb and handle objects. It can climb for example a shelf to grasp a book. On the ground it is transported by marXbot. In Chapter 6 the performance of robots are presented. We expose a study of their performance gain when the robots are self-assembled. Finally we compare in Chapter 7 the four robots from the mechatronics point of view and in respect to their cost

Entwicklungsumgebung für Roboterschwärme

In der vorliegenden Arbeit werden der systematische Entwurf und die Entwicklung einer Entwicklungsumgebung für Roboterschwärme beschrieben, die auf die spezifischen Eigenarten solcher Multi-Roboter-Systeme (MRS) eingeht. Kernstück der Entwicklungsumgebung sind eine interpretierte Steuersprache sowie eine dynamische interaktive Arena für Experimente. Die Entwicklungsumgebung vereinfacht den Entwurf von MRS, was in mehreren Experimenten mit verschiedenen Robotern anschaulich dargelegt wird