Modeling, Control and Energy Efficiency of Underwater Snake Robots

This thesis is mainly motivated by the attribute of the snake robots that they are able to move over land as well as underwater while the physiology of the robot remains the same. This adaptability to different motion demands depending on the environment is one of the main characteristics of the snake robots. In particular, this thesis targets several interesting aspects regarding the modeling, control and energy efficiency of the underwater snake robots. This thesis addresses the problem of modeling the hydrodynamic effects with an analytical perspective and a primary objective to conclude in a closed-form solution for the dynamic model of an underwater snake robot. Two mathematical models of the kinematics and dynamics of underwater snake robots swimming in virtual horizontal and vertical planes aimed at control design are presented. The presented models are derived in a closed-form and can be utilized in modern modelbased control schemes. In addition, these proposed models comprise snake robots moving both on land and in water which makes the model applicable for unified control methods for amphibious snake robots moving both on land and in water. The third model presented in this thesis is based on simplifying assumptions in order to derive a control-oriented model of an underwater snake robot moving in a virtual horizontal plane that is well-suited for control design and stability analysis. The models are analysed using several techniques. An extensive analysis of the model of a fully immersed underwater snake robot moving in a virtual horizontal plane is conducted. Based on this analysis, a set of essential properties that characterize the overall motion of underwater snake robots is derived. An averaging analysis reveals new fundamental properties of underwater snake robot locomotion that are useful from a motion planning perspective. In this thesis, both the motion analysis and control strategies are conducted based on a general sinusoidal motion pattern which can be used for a broad class of motion patterns including lateral undulation and eel-like motion. This thesis proposes and experimentally validates solutions to the path following control problem for biologically inspired swimming snake robots. In particular, line-of-sight (LOS) and integral line-of-sight (I-LOS) guidance laws, which are combined with a sinusoidal gait pattern and a directional controller that steers the robot towards and along the desired path are proposed. An I-LOS path following controller for steering an underwater snake robot along a straight line path in the presence of ocean currents of unknown direction and magnitude is presented and by using a Poincaré map, it is shown that all state variables of an underwater snake robot, except for the position along the desired path, trace out an exponentially stable periodic orbit. Moreover, this thesis presents the combined use of an artificial potential fields-based path planner with a new waypoint guidance strategy for steering an underwater snake robot along a path defined by waypoints interconnected by straight lines. The waypoints are derived by using a path planner based on the artificial potential field method in order to also address the obstacle avoidance problem. Furthermore, this thesis considers the energy efficiency of underwater snake robots. In particular, the relationship between the parameters of the gait patterns, the forward velocity and the energy consumption for the different motion patterns for underwater snake robots is investigated. Based on simulation results, this thesis presents empirical rules to choose the values for the parameters of the motion gait pattern of underwater snake robots. The experimental results support the derived properties regarding the relationship between the gait parameters and the power consumption both for lateral undulation and eel-like motion patterns. Moreover, comparison results are obtained for the total energy consumption and the cost of transportation of underwater snake robots and remotely operated vehicles (ROVs). Furthermore, in this thesis a multi-objective optimization problem is developed with the aim of maximizing the achieved forward velocity of the robot and minimizing the corresponding average power consumption of the system

Bio-Inspired Robotics

Modern robotic technologies have enabled robots to operate in a variety of unstructured and dynamically-changing environments, in addition to traditional structured environments. Robots have, thus, become an important element in our everyday lives. One key approach to develop such intelligent and autonomous robots is to draw inspiration from biological systems. Biological structure, mechanisms, and underlying principles have the potential to provide new ideas to support the improvement of conventional robotic designs and control. Such biological principles usually originate from animal or even plant models, for robots, which can sense, think, walk, swim, crawl, jump or even fly. Thus, it is believed that these bio-inspired methods are becoming increasingly important in the face of complex applications. Bio-inspired robotics is leading to the study of innovative structures and computing with sensory–motor coordination and learning to achieve intelligence, flexibility, stability, and adaptation for emergent robotic applications, such as manipulation, learning, and control. This Special Issue invites original papers of innovative ideas and concepts, new discoveries and improvements, and novel applications and business models relevant to the selected topics of ``Bio-Inspired Robotics''. Bio-Inspired Robotics is a broad topic and an ongoing expanding field. This Special Issue collates 30 papers that address some of the important challenges and opportunities in this broad and expanding field

Navigation and Control of Mobile Robots

The rapid development of robotics has benefited by more and more people putting their attention to it. In the 1920s, ‘Robota’, a similar concept, was first known to the world. It is proposed in Karel Capek’ s drama, Rossum’ s Universal Robots (RUR). From then on, numbers of automatic machines were created all over the world, which are known as the robots of the early periods. Gradually, the demand for robots is growing for the purpose of fulfilling tasks instead of humans. From industrial uses, to the military, to education and entertainment, di↵erent kinds of robots began to serve humans in various scenarios. Based on this, how to control the robot better is becoming a hot topic. For the topic of navigating and controlling mobile robots, number of related problems have been carried out. Obstacle avoidance, path planning, cooperative work of multi-robots. In this thesis, we focus on the first two problems, and mention the last one as a future direction in the last part. For obstacle avoidance, we proposed algorithms for both 2D planar environ- ments and 3D space environments. The example cases we raise are those that need to be addressed but have always been ignored. To be specific, the motion of the obstacles are not fixed, the shape of the obstacles are changeable, and the sensors that could be deployed for underwater environments are limited. We even put those problems together to solve them. The methods we proposed are based on the biologically inspired algorithm and Back Propagation Neural network (BPNN). In addition, we put e↵orts into trajectory planning for robots. The two scenarios we set are self-driving cars on the road and reconnaissance and surveillance of drones. The methods we deployed are the Convolutional Neural Network (CNN) method and the two-phase strategy, respectively. When we proposed the strategies, we gave a detailed description of the robot systems, the proposed algorithms. We showed the performance with simulation results to demonstrate the solutions proposed are feasible. For future expectations, there are some possible directions. When applying traditional navigation algorithms, for example, biologically inspired algorithms, we have to pay attention to the limitations of the environment. However, high-tech algorithms sometimes are not computationally friendly. How to combine them together so as to fulfill the tasks perfectly while the computational e ciency is not too high is a worthy topic. In addition, extending the obstacle avoidance al- gorithms to more competitive situations, such as applying to autonomous UAVs, is also being considered. Moreover, for cooperation among multi robots, which could be regarded as Network Control System (NCS), the issues, such as how to complete their respective tasks, how to choose the optimal routes for them are worth attention by researchers. All in all, there is still a long way to go for the development of navigation and control of mobile robots. Despite this, we believe we do not need to wait for too long time to see the revolution of robots

Automatic Control and Routing of Marine Vessels

Due to the intensive development of the global economy, many problems are constantly emerging connected to the safety of ships’ motion in the context of increasing marine traffic. These problems seem to be especially significant for the further development of marine transportation services, with the need to considerably increase their efficiency and reliability. One of the most commonly used approaches to ensuring safety and efficiency is the wide implementation of various automated systems for guidance and control, including such popular systems as marine autopilots, dynamic positioning systems, speed control systems, automatic routing installations, etc. This Special Issue focuses on various problems related to the analysis, design, modelling, and operation of the aforementioned systems. It covers such actual problems as tracking control, path following control, ship weather routing, course keeping control, control of autonomous underwater vehicles, ship collision avoidance. These problems are investigated using methods such as neural networks, sliding mode control, genetic algorithms, L2-gain approach, optimal damping concept, fuzzy logic and others. This Special Issue is intended to present and discuss significant contemporary problems in the areas of automatic control and the routing of marine vessels

Risk-aware Path and Motion Planning for a Tethered Aerial Visual Assistant in Unstructured or Confined Environments

This research aims at developing path and motion planning algorithms for a tethered Unmanned Aerial Vehicle (UAV) to visually assist a teleoperated primary robot in unstructured or confined environments. The emerging state of the practice for nuclear operations, bomb squad, disaster robots, and other domains with novel tasks or highly occluded environments is to use two robots, a primary and a secondary that acts as a visual assistant to overcome the perceptual limitations of the sensors by providing an external viewpoint. However, the benefits of using an assistant have been limited for at least three reasons: (1) users tend to choose suboptimal viewpoints, (2) only ground robot assistants are considered, ignoring the rapid evolution of small unmanned aerial systems for indoor flying, (3) introducing a whole crew for the second teleoperated robot is not cost effective, may introduce further teamwork demands, and therefore could lead to miscommunication. This dissertation proposes to use an autonomous tethered aerial visual assistant to replace the secondary robot and its operating crew. Along with a pre-established theory of viewpoint quality based on affordances, this dissertation aims at defining and representing robot motion risk in unstructured or confined environments. Based on those theories, a novel high level path planning algorithm is developed to enable risk-aware planning, which balances the tradeoff between viewpoint quality and motion risk in order to provide safe and trustworthy visual assistance flight. The planned flight trajectory is then realized on a tethered UAV platform. The perception and actuation are tailored to fit the tethered agent in the form of a low level motion suite, including a novel tether-based localization model with negligible computational overhead, motion primitives for the tethered airframe based on position and velocity control, and two differentComment: Ph.D Dissertatio

Risk-aware Path and Motion Planning for a Tethered Aerial Visual Assistant in Unstructured or Confined Environments

This research aims at developing path and motion planning algorithms for a tethered Unmanned Aerial Vehicle (UAV) to visually assist a teleoperated primary robot in unstructured or confined environments. The emerging state of the practice for nuclear operations, bomb squad, disaster robots, and other domains with novel tasks or highly occluded environments is to use two robots, a primary and a secondary that acts as a visual assistant to overcome the perceptual limitations of the sensors by providing an external viewpoint. However, the benefits of using an assistant have been limited for at least three reasons: (1) users tend to choose suboptimal viewpoints, (2) only ground robot assistants are considered, ignoring the rapid evolution of small unmanned aerial systems for indoor flying, (3) introducing a whole crew for the second teleoperated robot is not cost effective, may introduce further teamwork demands, and therefore could lead to miscommunication. This dissertation proposes to use an autonomous tethered aerial visual assistant to replace the secondary robot and its operating crew. Along with a pre-established theory of viewpoint quality based on affordances, this dissertation aims at defining and representing robot motion risk in unstructured or confined environments. Based on those theories, a novel high level path planning algorithm is developed to enable risk-aware planning, which balances the tradeoff between viewpoint quality and motion risk in order to provide safe and trustworthy visual assistance flight. The planned flight trajectory is then realized on a tethered UAV platform. The perception and actuation are tailored to fit the tethered agent in the form of a low level motion suite, including a novel tether-based localization model with negligible computational overhead, motion primitives for the tethered airframe based on position and velocity control, and two different approaches to negotiate tether with complex obstacle-occupied environments. The proposed research provides a formal reasoning of motion risk in unstructured or confined spaces, contributes to the field of risk-aware planning with a versatile planner, and opens up a new regime of indoor UAV navigation: tethered indoor flight to ensure battery duration and failsafe in case of vehicle malfunction. It is expected to increase teleoperation productivity and reduce costly errors in scenarios such as safe decommissioning and nuclear operations in the Fukushima Daiichi facility

Boundary tracking and source seeking of oceanic features using autonomous vehicles

The thesis concerns the study and the development of boundary tracking and source seeking approaches for autonomous vehicles, specifically for marine autonomous systems. The underlying idea is that the characterization of most environmental features can be posed from either a boundary tracking or a source seeking perspective. The suboptimal sliding mode boundary tracking approach is considered and, as a first contribution, it is extended to the study of three dimensional features. The approach is aimed at controlling the movement of an underwater glider tracking a three-dimensional underwater feature and it is validated in a simulated environment. Subsequently, a source seeking approach based on sliding mode extremum seeking ideas is proposed. This approach is developed for the application to a single surface autonomous vehicle, seeking the source of a static or dynamic two dimensional spatial field. A sufficient condition which guarantees the finite time convergence to a neighbourhood of the source is introduced. Furthermore, a probabilistic learning boundary tracking approach is proposed, aimed at exploiting the available preliminary information relating to the spatial phenomenon of interest in the control strategy. As an additional contribution, the sliding mode boundary tracking approach is experimentally validated in a set of sea-trials with the deployment of a surface autonomous vehicle. Finally, an embedded system implementing the proposed boundary tracking strategy is developed for future installation on board of the autonomous vehicle. This work demonstrates the possibility to perform boundary tracking with a fully autonomous vehicle and to operate marine autonomous systems without remote control or pre-planning. Conclusions are drawn from the results of the research presented in this thesis and directions for future work are identified

Dynamic virtual reality user interface for teleoperation of heterogeneous robot teams

This research investigates the possibility to improve current teleoperation control for heterogeneous robot teams using modern Human-Computer Interaction (HCI) techniques such as Virtual Reality. It proposes a dynamic teleoperation Virtual Reality User Interface (VRUI) framework to improve the current approach to teleoperating heterogeneous robot teams

Development of a formation control algorithm to coordinate multiple biomimetic AUVs in the presence of realistic environmental constraints

Biomimetic Autonomous Underwater Vehicles (BAUVs) are a class of Uncrewed Underwater Vehicle (UUV) that mimic the propulsive and steering mechanisms of real fish. However, as with all UUVs, the range and endurance of these vehicles remains limited by the finite energy source housed on board the vehicle. Unsurprisingly, a consequence of this finite energy source is that BAUVs/UUVs are incapable of completing the large-scale oceanographic sampling missions required to drastically improve our understanding of the Earth’s oceans and its processes. To overcome this limitation, this thesis aims to investigate the feasibility of deploying a self-coordinating group of BAUVs capable of completing the aforementioned oceanic surveying missions despite the constraints of the local operating environment. To achieve this, the work presented in this thesis can be separated into four distinct parts. The first of which is the development of a suitable mathematical model that accurately models the dynamics of the RoboSalmon BAUV designed and built at the University of Glasgow. As well as ensuring the models validity, its ability to efficiently simulate multiple vehicles simultaneously is also demonstrated. The design and implementation of the formation control algorithm used to coordinate the vehicles is then presented. This process describes the alterations made to a biologically-inspired algorithm to ensure the required parallel line formation required for efficient oceanic sampling can be generated. Thereafter, the implementation of a realistic representation of the underwater communication channel and its debilitating effect on the algorithms ability to coordinate the vehicles as required is presented. The thesis then describes the incorporation of two methodologies designed specifically to overcome the limitations associated with the underwater communication channel. The first of which involves the implementation of tracking/predictive functionality while the second is a consensus based algorithm that aims to reduce the algorithms reliance on the communication channel. The robustness of these two methodologies to overcoming not only the problematic communication channel but also the inclusion of additional external disturbances is then presented. The results demonstrate that while the tracking/predictive functionality can overcome the problems associated with the communication channel, its efficiency significantly reduces when the external disturbances are taken into consideration. The consensus based methodology meanwhile generates the required formation regardless of the constraints imposed by both the communication channel and the additional external disturbances and therefore provides the more robust solution

Comprehensive review on controller for leader-follower robotic system

985-1007This paper presents a comprehensive review of the leader-follower robotics system. The aim of this paper is to find and elaborate on the current trends in the swarm robotic system, leader-follower, and multi-agent system. Another part of this review will focus on finding the trend of controller utilized by previous researchers in the leader-follower system. The controller that is commonly applied by the researchers is mostly adaptive and non-linear controllers. The paper also explores the subject of study or system used during the research which normally employs multi-robot, multi-agent, space flying, reconfigurable system, multi-legs system or unmanned system. Another aspect of this paper concentrates on the topology employed by the researchers when they conducted simulation or experimental studies