Cooperation of Multiple Fish-like Microrobots Based on Reinforcement Learning

Abstract-This paper is concerned with cooperative control of a kind of multiple fish-like microrobots. Most of previous work on multi-robot cooperation is focused on the terrestrial robots and seldom deals with underwater applications. In fact, the tasks in hydro-environment is more challenging than those in ground circumstances and need the cooperation of robots much more. In this paper, we investigate this problem in the framework of an adversarial game with several underwater microrobots. A fuzzy reinforcement learning approach is adopted to acquire cooperative behavior and a behavioral hierarchical architecture is proposed. We conduct extensive experiments to verify the effectiveness of the proposed algorithms

Underwater Vehicles

For the latest twenty to thirty years, a significant number of AUVs has been created for the solving of wide spectrum of scientific and applied tasks of ocean development and research. For the short time period the AUVs have shown the efficiency at performance of complex search and inspection works and opened a number of new important applications. Initially the information about AUVs had mainly review-advertising character but now more attention is paid to practical achievements, problems and systems technologies. AUVs are losing their prototype status and have become a fully operational, reliable and effective tool and modern multi-purpose AUVs represent the new class of underwater robotic objects with inherent tasks and practical applications, particular features of technology, systems structure and functional properties

The Use of Flexible Biomimetic Fins in Propulsion

This thesis documents a series of investigations exploring the role of stiffness profile in propulsion using pitching flexible fins. Stiffness profile is defined as the variation in local bending stiffness along the chord of a fin, from leading to trailing edge. An unmanned robotic submarine was created, using simple pitching flexible fins for propulsion. Its design and performance prompted a review of literature covering many aspects of oscillating fin propulsion, paying special attention to the studies of pitching flexible fins, of the type used in the submarine. In the body of previous work, fin stiffness profile was a consequence of the external shape profile of a fin; fins had not thus far been designed with stiffness profile specifically in mind. A hypothesis was proposed: “Use of a biomimetic fin stiffness profile can improve the effectiveness of a flexible oscillating fin, over that of a standard NACA designated fin shape.” Rectangular planform flexible fins of standard NACA 0012 design and 1:1 aspect ratio were tested alongside similar fins with a stiffness profile mimicking that of a pumpkinseed sunfish (Lepomis gibbosus). The fins were oscillated with a pitching-only sinusoidal motion over a range of frequencies and amplitudes, while torque, lateral force and static thrust were measured. Over the range of oscillation parameters tested, it was shown that the fin with a biomimetic stiffness profile offered a significant improvement in static thrust over a fin of similar dimensions with a standard NACA 0012 aerofoil shape, and produced thrust more consistently over each oscillation cycle. A comparison of different moulding materials showed that the improvement was due to the stiffness profile itself, and was not simply an effect of altering the overall stiffness of the fin, or changing its natural frequency. Within the range of stiffnesses and oscillation conditions tested, fins of the same stiffness profile were found to follow similar thrust-power curves, independently of their moulding material. Biomimetic fins were shown to produce between 10% and 25% more thrust per watt of mechanical input power.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Estimation of objects’ inertial parameters, and their usage in robot grasping and manipulation

The subject of this thesis is the estimation of an object's inertial parameters by a robotic arm, and the exploitation of those parameters in the design of efficient manipulation criteria. The inertial parameters of objects describe the resistance of the object to an applied force, and dictate its motion. Research has shown that humans intuitively exploit them for their everyday manipulations. As humans are very capable of performing efficient manipulations, it is natural that robots should use the inertial parameters as well. Additionally, as the inertial parameters are not straightforward to calculate, there is the need for development of methods that can estimate them online. This thesis focuses on two directions, developing novel methods so that robots can accurately estimate the inertial parameters of an object, as well as developing manipulation criteria that can make robot task completion more efficient. The relevant literature is gathered, categorised and analytically described, and the innovation gaps are identified. The thesis offers novel research solutions on the problem of estimation of the inertial parameters with minimal robot interaction. The paradigm is shifted from the existing literature, and a data-driven estimation algorithm is introduced, that achieves accurate results with both simulated and real data. Additionally, the presented research is offering novel manipulation criteria that are affected by the object's inertial parameters. The results suggest that knowledge of the inertial parameters can make the robot tasks more power-efficient and safe to their surroundings. The core methodology is shown to be versatile to the robotic platform. Though most experiments are performed on a terrestrial robot, a numerical example is also shown for a space robot. The results of the thesis suggest that the developed methods can be used in various environments, with the most suitable being extreme environments where accuracy, efficiency and autonomy is required

Advanced Mobile Robotics: Volume 3

Mobile robotics is a challenging field with great potential. It covers disciplines including electrical engineering, mechanical engineering, computer science, cognitive science, and social science. It is essential to the design of automated robots, in combination with artificial intelligence, vision, and sensor technologies. Mobile robots are widely used for surveillance, guidance, transportation and entertainment tasks, as well as medical applications. This Special Issue intends to concentrate on recent developments concerning mobile robots and the research surrounding them to enhance studies on the fundamental problems observed in the robots. Various multidisciplinary approaches and integrative contributions including navigation, learning and adaptation, networked system, biologically inspired robots and cognitive methods are welcome contributions to this Special Issue, both from a research and an application perspective

Innovative robot hand designs of reduced complexity for dexterous manipulation

This thesis investigates the mechanical design of robot hands to sensibly reduce the system complexity in terms of the number of actuators and sensors, and control needs for performing grasping and in-hand manipulations of unknown objects. Human hands are known to be the most complex, versatile, dexterous manipulators in nature, from being able to operate sophisticated surgery to carry out a wide variety of daily activity tasks (e.g. preparing food, changing cloths, playing instruments, to name some). However, the understanding of why human hands can perform such fascinating tasks still eludes complete comprehension. Since at least the end of the sixteenth century, scientists and engineers have tried to match the sensory and motor functions of the human hand. As a result, many contemporary humanoid and anthropomorphic robot hands have been developed to closely replicate the appearance and dexterity of human hands, in many cases using sophisticated designs that integrate multiple sensors and actuators---which make them prone to error and difficult to operate and control, particularly under uncertainty. In recent years, several simplification approaches and solutions have been proposed to develop more effective and reliable dexterous robot hands. These techniques, which have been based on using underactuated mechanical designs, kinematic synergies, or compliant materials, to name some, have opened up new ways to integrate hardware enhancements to facilitate grasping and dexterous manipulation control and improve reliability and robustness. Following this line of thought, this thesis studies four robot hand hardware aspects for enhancing grasping and manipulation, with a particular focus on dexterous in-hand manipulation. Namely: i) the use of passive soft fingertips; ii) the use of rigid and soft active surfaces in robot fingers; iii) the use of robot hand topologies to create particular in-hand manipulation trajectories; and iv) the decoupling of grasping and in-hand manipulation by introducing a reconfigurable palm. In summary, the findings from this thesis provide important notions for understanding the significance of mechanical and hardware elements in the performance and control of human manipulation. These findings show great potential in developing robust, easily programmable, and economically viable robot hands capable of performing dexterous manipulations under uncertainty, while exhibiting a valuable subset of functions of the human hand.Open Acces

Abstractions, Analysis Techniques, and Synthesis of Scalable Control Strategies for Robot Swarms

Tasks that require parallelism, redundancy, and adaptation to dynamic, possibly hazardous environments can potentially be performed very efficiently and robustly by a swarm robotic system. Such a system would consist of hundreds or thousands of anonymous, resource-constrained robots that operate autonomously, with little to no direct human supervision. The massive parallelism of a swarm would allow it to perform effectively in the event of robot failures, and the simplicity of individual robots facilitates a low unit cost. Key challenges in the development of swarm robotic systems include the accurate prediction of swarm behavior and the design of robot controllers that can be proven to produce a desired macroscopic outcome. The controllers should be scalable, meaning that they ensure system operation regardless of the swarm size. This thesis presents a comprehensive approach to modeling a swarm robotic system, analyzing its performance, and synthesizing scalable control policies that cause the populations of different swarm elements to evolve in a specified way that obeys time and efficiency constraints. The control policies are decentralized, computed a priori, implementable on robots with limited sensing and communication capabilities, and have theoretical guarantees on performance. To facilitate this framework of abstraction and top-down controller synthesis, the swarm is designed to emulate a system of chemically reacting molecules. The majority of this work considers well-mixed systems when there are interaction-dependent task transitions, with some modeling and analysis extensions to spatially inhomogeneous systems. The methodology is applied to the design of a swarm task allocation approach that does not rely on inter-robot communication, a reconfigurable manufacturing system, and a cooperative transport strategy for groups of robots. The third application incorporates observations from a novel experimental study of the mechanics of cooperative retrieval in Aphaenogaster cockerelli ants. The correctness of the abstractions and the correspondence of the evolution of the controlled system to the target behavior are validated with computer simulations. The investigated applications form the building blocks for a versatile swarm system with integrated capabilities that have performance guarantees