Virtual spring damper method for nonholonomic robotic swarm self-organization and leader following

In this paper, we demonstrate a method for self-organization and leader following of nonholonomic robotic swarm based on spring damper mesh. By self-organization of swarm robots we mean the emergence of order in a swarm as the result of interactions among the single robots. In other words the self-organization of swarm robots mimics some natural behavior of social animals like ants among others. The dynamics of two-wheel robot is derived, and a relation between virtual forces and robot control inputs is defined in order to establish stable swarm formation. Two cases of swarm control are analyzed. In the first case the swarm cohesion is achieved by virtual spring damper mesh connecting nearest neighboring robots without designated leader. In the second case we introduce a swarm leader interacting with nearest and second neighbors allowing the swarm to follow the leader. The paper ends with numeric simulation for performance evaluation of the proposed control method

Virtual spring damper method for nonholonomic robotic swarm self-organization and leader following

In this paper, we demonstrate a method for self-organization and leader following of nonholonomic robotic swarm based on spring damper mesh. By self-organization of swarm robots we mean the emergence of order in a swarm as the result of interactions among the single robots. In other words the self-organization of swarm robots mimics some natural behavior of social animals like ants among others. The dynamics of two-wheel robot is derived, and a relation between virtual forces and robot control inputs is defined in order to establish stable swarm formation. Two cases of swarm control are analyzed. In the first case the swarm cohesion is achieved by virtual spring damper mesh connecting nearest neighboring robots without designated leader. In the second case we introduce a swarm leader interacting with nearest and second neighbors allowing the swarm to follow the leader. The paper ends with numeric simulation for performance evaluation of the proposed control method

A survey of modern exogenous fault detection and diagnosis methods for swarm robotics

Swarm robotic systems are heavily inspired by observations of social insects. This often leads to robust-ness being viewed as an inherent property of them. However, this has been shown to not always be thecase. Because of this, fault detection and diagnosis in swarm robotic systems is of the utmost importancefor ensuring the continued operation and success of the swarm. This paper provides an overview of recentwork in the field of exogenous fault detection and diagnosis in swarm robotics, focusing on the four areaswhere research is concentrated: immune system, data modelling, and blockchain-based fault detectionmethods and local-sensing based fault diagnosis methods. Each of these areas have significant advan-tages and disadvantages which are explored in detail. Though the work presented here represents a sig-nificant advancement in the field, there are still large areas that require further research. Specifically,further research is required in testing these methods on real robotic swarms, fault diagnosis methods,and integrating fault detection, diagnosis and recovery methods in order to create robust swarms thatcan be used for non-trivial tasks

A survey of modern exogenous fault detection and diagnosis methods for swarm robotics

Swarm robotic systems are heavily inspired by observations of social insects. This often leads to robust-ness being viewed as an inherent property of them. However, this has been shown to not always be thecase. Because of this, fault detection and diagnosis in swarm robotic systems is of the utmost importancefor ensuring the continued operation and success of the swarm. This paper provides an overview of recentwork in the field of exogenous fault detection and diagnosis in swarm robotics, focusing on the four areaswhere research is concentrated: immune system, data modelling, and blockchain-based fault detectionmethods and local-sensing based fault diagnosis methods. Each of these areas have significant advan-tages and disadvantages which are explored in detail. Though the work presented here represents a sig-nificant advancement in the field, there are still large areas that require further research. Specifically,further research is required in testing these methods on real robotic swarms, fault diagnosis methods,and integrating fault detection, diagnosis and recovery methods in order to create robust swarms thatcan be used for non-trivial tasks

Particle Swarm Optimization—An Adaptation for the Control of Robotic Swarms

Particle Swarm Optimization (PSO) is a numerical optimization technique based on the motion of virtual particles within a multidimensional space. The particles explore the space in an attempt to find minima or maxima to the optimization problem. The motion of the particles is linked, and the overall behavior of the particle swarm is controlled by several parameters. PSO has been proposed as a control strategy for physical swarms of robots that are localizing a source; the robots are analogous to the virtual particles. However, previous attempts to achieve this have shown that there are inherent problems. This paper addresses these problems by introducing a modified version of PSO, as well as introducing new guidelines for parameter selection. The proposed algorithm links the parameters to the velocity and acceleration of each robot, and demonstrates obstacle avoidance. Simulation results from both MATLAB and Gazebo show close agreement and demonstrate that the proposed algorithm is capable of effective control of a robotic swarm and obstacle avoidance

Acoustic Communication for Medical Nanorobots

Communication among microscopic robots (nanorobots) can coordinate their activities for biomedical tasks. The feasibility of in vivo ultrasonic communication is evaluated for micron-size robots broadcasting into various types of tissues. Frequencies between 10MHz and 300MHz give the best tradeoff between efficient acoustic generation and attenuation for communication over distances of about 100 microns. Based on these results, we find power available from ambient oxygen and glucose in the bloodstream can readily support communication rates of about 10,000 bits/second between micron-sized robots. We discuss techniques, such as directional acoustic beams, that can increase this rate. The acoustic pressure fields enabling this communication are unlikely to damage nearby tissue, and short bursts at considerably higher power could be of therapeutic use.Comment: added discussion of communication channel capacity in section

Characterisation of a nuclear cave environment utilising an autonomous swarm of heterogeneous robots

As nuclear facilities come to the end of their operational lifetime, safe decommissioning becomes a more prevalent issue. In many such facilities there exist ‘nuclear caves’. These caves constitute areas that may have been entered infrequently, or even not at all, since the construction of the facility. Due to this, the topography and nature of the contents of these nuclear caves may be unknown in a number of critical aspects, such as the location of dangerous substances or significant physical blockages to movement around the cave. In order to aid safe decommissioning, autonomous robotic systems capable of characterising nuclear cave environments are desired. The research put forward in this thesis seeks to answer the question: is it possible to utilise a heterogeneous swarm of autonomous robots for the remote characterisation of a nuclear cave environment? This is achieved through examination of the three key components comprising a heterogeneous swarm: sensing, locomotion and control. It will be shown that a heterogeneous swarm is not only capable of performing this task, it is preferable to a homogeneous swarm. This is due to the increased sensory and locomotive capabilities, coupled with more efficient explorational prowess when compared to a homogeneous swarm

Acoustic Communication for Medical Nanorobots

Communication among microscopic robots (nanorobots) can coordinate their activities for biomedical tasks. The feasibility of in vivo ultrasonic communication is evaluated for micron-size robots broadcasting into various types of tissues. Frequencies between 10MHz and 300MHz give the best tradeoff between efficient acoustic generation and attenuation for communication over distances of about 100 microns. Based on these results, we find power available from ambient oxygen and glucose in the bloodstream can readily support communication rates of about 10,000 bits/second between micron-sized robots. We discuss techniques, such as directional acoustic beams, that can increase this rate. The acoustic pressure fields enabling this communication are unlikely to damage nearby tissue, and short bursts at considerably higher power could be of therapeutic use.Comment: added discussion of communication channel capacity in section