In swarm robotics, developing algorithms for self-organizing minimalistic robots has become a popular research topic. Unlike others, minimalistic robots may not be able to self-localize themselves, making it very challenging to accomplish missions such as surrounding a target, whose position is typically unknown. In target surroundings, reaching a target and joining the swarm do not always lead to a satisfactory enclosure of the target. Furthermore, it is impossible for individual minimalistic robots to figure out what a global shape of the swarm should be without a collective decision making. In this article, we make use of diffusion and reaction of two morphogens for target surrounding and formation of a circular shape swarm. We show that the proposed method is able to adaptively form shapes surrounding multiple targets. Computer simulations and physical experiments using Kilobots are performed to assess the performance of the proposed algorithm.

Minimalist robots are functionally highly restricted but well suited for swarm robotic applications because of their low costs and small sizes. Connectivity maintenance and collision avoidance are challenging in minimalist swarm robotic systems due to a short communication range and the lack of positional and directional sensing. In this paper, we introduce a self-organizing control strategy for c...

Self-organised emergent patterns can be widely seen in natural and man-made complex systems generated by interactions among local components without external or global control. This paper presents a survey of recent research advances in self-organising pattern formation in mobile multi-robot (or swarm robotic) systems. Relevant pattern formation methods are reviewed with a special focus on biologically-inspired self-organising approaches inspired from macroscopic collective behaviours or microscopic multicellular developing mechanisms. As the ultimate goal of this review is to provide insight into pattern formation using real robots, limitations and considerations on dealing with a large number of robots are discussed. In addition, guided self-organisation is also discussed as a design strategy where the swarm robotic system may be endowed with local rules for generating desired global patterns.

In this paper, we present a morphogenetic approach to self-organized collective movement of a swarm. We assume that the robots (agents) do not have global knowledge of the environment and can communicate only locally with other robots. In addition, we assume that the robots are not able to perform directional sensing. To self-organize such systems, we adopt here a simplified diffusion mechanism inspired from biological morphogenesis. A guidance mechanism is proposed based on the history of morphogen concentrations. The division of labor is achieved by type differentiation to allocate different tasks to different type of robots. Simulations are run to show the efficiency of the proposed algorithm. The robustness of the algorithm is demonstrated by introducing an obstacle into the environment and removing a subset of robots from the swarm.

Many industrial applications need less than 6 degrees of freedom (DOF) to manipulate. On one hand, the parallel manipulators (PMs) with lower DOF have some advantages such as low manufacturing and control cost. On the other hand, they have more complicated kinematics. Among PMs with lower DOF, the 5-DOF PMs have particularly many industrial applications. Within the group of 5-DOF PMs, the three translational and two rotational (3T2R) type has more industrial applications than three rotational and two translational type. In this paper, we analyze and optimize the 5-RPUR PM which is a 3T2R type. The kinematic analysis is studied using the screw theory. The boundary and volume of the workspace is obtained using a geometrical method. In addition, singularity analysis is studied. Particle swarm optimization is utilized to optimize the workspace and the accuracy simultaneously, and achieve a roughly homogeneous accuracy index over the workspace. The boundary of the optimized workspace is depicted and we show that the optimized workspace is singularity free. The accuracy index of the manipulator is calculated and depicted in several cross-sections of the workspace.