A Decentralized Control Framework for Energy-Optimal Goal Assignment and Trajectory Generation

This paper proposes a decentralized approach for solving the problem of moving a swarm of agents into a desired formation. We propose a decentralized assignment algorithm which prescribes goals to each agent using only local information. The assignment results are then used to generate energy-optimal trajectories for each agent which have guaranteed collision avoidance through safety constraints. We present the conditions for optimality and discuss the robustness of the solution. The efficacy of the proposed approach is validated through a numerical case study to characterize the framework's performance on a set of dynamic goals.Comment: 6 pages, 3 figures, to appear at the 2019 Conference on Decision and Control, Nice, F

Body Conjunction = Wavering Between Actual and Virtual Spaces

In the present digital age, the body tends to extend beyond it being flesh, it can be extended, it is a body without organs, and it might belong to more than your own-self. The “Body” as a living entity with its embedded sensory system, not only embodies who we are but also lets us understand and explore the sensitive, unpredictable but fascinating world. The body is an information receiver as well as information reactor. Through years of medical experiments and research on the body, medical devices and instruments are able to allow us to look into the deepest and the most mysterious spots in the human body. For instance, if seen through an HD monitor, while being probed by an endoscope, the body appears as an immersive and infinite landscape. By observing the smoothness and the folds of the surfaces encountered within the body, it is quite simple to project your individual self into this body-scape for a while to imagine and experience this immersive organic space. Various potential ideas of designing a body-like space have become the subject of design fantasies of a number of architects. The “Vitruvian Man”, which, Vitruvius described in the third book of De Architectura, and was later interpreted and illustrated by Leonardo DaVinci, has served as the human figure/body representation to be used as a measuring unit rather than being considered as a sensitive object. Unsurprisingly, it was a relatively long journey for architects to abandon this dogma. After the industrial revolution (during the modernist era), the concrete evidence of considering body proportions as potential measurements could still be seen in the projects of Le Corbusier, which accompanied his famous school of thought: “A house is a machine for living”. He developed the “Modular” in a mathematical proportion of space based on figures and intended to replace the old Vitruvian man with it as a new generation’s typical model. However, with the rapid development of electronic technology, the trend of realizing sensory environments akin to living bodies has no longer remained a thought but can be seen as an initial action to refuse to see the human body merely as a measuring unit. The turning point came about the time while the medium of news media, television, and social media became relatively mature, and thus started making people conduct critical reflections. Marshall McLuhan, a well-known pioneering media theorist, stated in his well-known publication, “Understanding Media: The Extension of Man” (McLuhan, Understanding Media: The Extensions of Man, 1964). This explicit shot made the researcher foresee the potential and intimate relationships between the body, technology, and space, and somehow have a rational explanation to extend the physical body to endless space, which is crucial in this chapter

Exogenous Fault Detection in Swarm Robotic Systems

Swarm robotic systems comprise many individual robots, and exhibit a degree of innate fault tolerance due to this built-in redundancy. They are robust in the sense that the complete failure of individual robots will have little detrimental effect on a swarm's overall collective behaviour. However, it has recently been shown that partially failed individuals may be harmful, and cause problems that cannot be solved by simply adding more robots to the swarm. Instead, an active approach to dealing with failed individuals is required for a swarm to continue operation in the face of partial failures. This thesis presents a novel method of exogenous fault detection that allows robots to detect the presence of faults in each other, via the comparison of expected and observed behaviour. Each robot predicts the expected behaviour of its neighbours by simulating them online in an internal replica of the real world. This expected behaviour is then compared against observations of their true behaviour, and any significant discrepancy is detected as a fault. This work represents the first step towards a distributed fault detection, diagnosis, and recovery process that would afford robot swarms a high degree of fault tolerance, and facilitate long-term autonomy

Unmanned Systems Sentinel / 6 March 2016

Approved for public release; distribution is unlimited

Multi-Agent Path Planning for Locating a Radiating Source in an Unknown Environment

A situation is addressed in which multiple autonomous agents are used to search an unknown environment for a target, the position and orientation of which is known with respect to each agent. A controlling framework is proposed to inform and coordinate the agents’ movements in order to reduce the time required to locate the target. Four primary variables are considered: the cost function used to select the agents’ paths, the number of agents in a given scenario, the distance over which the agents are assumed to communicate, and the size of the environment in which the agents are operating. It was found that a cost function that balances progress toward the target with exploration of the environment is generally most effective for all combinations of the other variables. More agents and greater communication are beneficial, to a point, in larger environments, although these may be less effective in smaller ones

A Novel Docking and Communications System for Heterogeneous Modular Robots

Modular robots are systems of many independent modules that can mechanically join and communicate with one another to form a robot morphology that can accomplish more than any of the modules could accomplish independently. Systems of modular robots that can dynamically reconfigure can form an ideal morphology for a given task, or repair the system if one or more modules fail. Such capabilities are useful for applications such as operating in harsh environments and exploration of extra-terrestrial planets. Previous work in the field has been focused on locomotion strategies, reconfiguration strategies and docking connector design. While these are all very important areas of research, if modular robots are to progress to the stage of being deployable systems, work needs to be done on developing a holistic platform that research can be built upon. This thesis describes the work that has been done to create a new heterogeneous cubic modular robot platform, Mo*, with particular focus on developing a system that can be used as a standard for modular robot development through a novel connection mechanism and communication strategy It is hoped that this can advance the field of research by allowing providing a platform that can be used for a wide range of future research The system is designed and built, with experiments being performed to test the performance of the docking mechanism and communication system between modules. The hardware system developed in this work could be used and built upon to further advance the capabilities modular robotic systems for real world applications

Methods for the Efficient Deployment and Coordination of Swarm Robotic Systems

Swarming has been observed in many animal species, including fish, birds, insects and mammals. These biological observations have inspired mathematical models of distributed coordination that have been applied to the development of multi-agent robotic systems, such as collections of unmanned autonomous vehicles (UAVs). The advantages of a swarming approach to distributed coordination are clear: each agent acts according to a simple set of rules that can be implemented on resource-constrained devices, and so it becomes feasible to replicate agents in order to build more resilient systems. However, there remain significant challenges in making the approach practicable. This thesis addresses two of the most significant: coordination and scalability. New coordination algorithms are proposed here, all of which manage the problem of scalability by requiring only local proximity sensing between agents, without the need for any other communications infrastructure. A major source of inefficiency in the deployment of a swarm is ‘oscillation’: small movements of agents that arise as a side effect of the application of their rules but which are not strictly necessary in order to satisfy the overall system function. The thesis introduces a new metric for ‘oscillation’ that allows it to be identified and measured in swarm control algorithms. A new perimeter detection mechanism is introduced and applied to the coordination of goal-based swarms. The mechanism is used to improve the internal coordination of agents whilst maintaining a directional focus to the swarm; this is then analysed using the new metric. A mechanism is proposed to allow a swarm to exhibit a ‘healing’ behaviour by identifying internal perimeter edges (doughnuts) and then altering the movement of agents, based upon a simple criterion, to remove the holes; this also has the emergent effect of smoothing the outer edges of a swarm and creating a more uniform swarm structure. Area coverage is an important requirement in many swarm applications. Two new, efficient area-filling techniques are introduced here and exit conditions are identified to determine when a swarm has filled an area. In summary, the thesis makes significant contributions to the analysis and design of efficient control algorithms for the coordination of large scale swarms