Analysis of underwater snake robot locomotion based on a control-oriented model

This paper presents an analysis of planar underwater snake robot locomotion in the presence of ocean currents. The robot is assumed to be neutrally buoyant and move fully submerged with a planar sinusoidal gait and limited link angles. As a basis for the analysis, an existing, controloriented model is further simplified and extended to general sinusoidal gaits. Averaging theory is then employed to derive the averaged velocity dynamics of the underwater snake robot from that model. It is proven that the averaged velocity converges exponentially to an equilibrium, and an analytical expression for calculating the forward velocity of the robot in steady state is derived. A simulation study that validates both the proposed modelling approach and the theoretical results is presented.Prepint - (c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works

Formation Control of Underactuated Bio-inspired Snake Robots

This paper considers formation control of snake robots. In particular, based on a simplified locomotion model, and using the method of virtual holonomic constraints, we control the body shape of the robot to a desired gait pattern defined by some pre-specified constraint functions. These functions are dynamic in that they depend on the state variables of two compensators which are used to control the orientation and planar position of the robot, making this a dynamic maneuvering control strategy. Furthermore, using a formation control strategy we make the multi-agent system converge to and keep a desired geometric formation, and enforce the formation follow a desired straight line path with a given speed profile. Specifically, we use the proposed maneuvering controller to solve the formation control problem for a group of snake robots by synchronizing the commanded velocities of the robots. Simulation results are presented which illustrate the successful performance of the theoretical approach.© ISAROB 2016. This is the authors' accepted and refereed manuscript to the article. Locked until 2017-07-27

The Mechanics and Control of Undulatory Robotic Locomotion

In this dissertation, we examine a formulation of problems of undulatory robotic locomotion within the context of mechanical systems with nonholonomic constraints and symmetries. Using tools from geometric mechanics, we study the underlying structure found in general problems of locomotion. In doing so, we decompose locomotion into two basic components: internal shape changes and net changes in position and orientation. This decomposition has a natural mathematical interpretation in which the relationship between shape changes and locomotion can be described using a connection on a trivial principal fiber bundle. We begin by reviewing the processes of Lagrangian reduction and reconstruction for unconstrained mechanical systems with Lie group symmetries, and present new formulations of this process which are easily adapted to accommodate external constraints. Additionally, important physical quantities such as the mechanical connection and reduced mass-inertia matrix can be trivially determined using this formulation. The presence of symmetries then allows us to reduce the necessary calculations to simple matrix manipulations. The addition of constraints significantly complicates the reduction process; however, we show that for invariant constraints, a meaningful connection can be synthesized by defining a generalized momentum representing the momentum of the system in directions allowed by the constraints. We then prove that the generalized momentum and its governing equation possess certain invariances which allows for a reduction process similar to that found in the unconstrained case. The form of the reduced equations highlights the synthesized connection and the matrix quantities used to calculate these equations. The use of connections naturally leads to methods for testing controllability and aids in developing intuition regarding the generation of various locomotive gaits. We present accessibility and controllability tests based on taking derivatives of the connection, and relate these tests to taking Lie brackets of the input vector fields. The theory is illustrated using several examples, in particular the examples of the snakeboard and Hirose snake robot. We interpret each of these examples in light of the theory developed in this thesis, and examine the generation of locomotive gaits using sinusoidal inputs and their relationship to the controllability tests based on Lie brackets

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

In silico case studies of compliant robots: AMARSI deliverable 3.3

In the deliverable 3.2 we presented how the morphological computing ap- proach can significantly facilitate the control strategy in several scenarios, e.g. quadruped locomotion, bipedal locomotion and reaching. In particular, the Kitty experimental platform is an example of the use of morphological computation to allow quadruped locomotion. In this deliverable we continue with the simulation studies on the application of the different morphological computation strategies to control a robotic system

Information driven self-organization of complex robotic behaviors

Information theory is a powerful tool to express principles to drive autonomous systems because it is domain invariant and allows for an intuitive interpretation. This paper studies the use of the predictive information (PI), also called excess entropy or effective measure complexity, of the sensorimotor process as a driving force to generate behavior. We study nonlinear and nonstationary systems and introduce the time-local predicting information (TiPI) which allows us to derive exact results together with explicit update rules for the parameters of the controller in the dynamical systems framework. In this way the information principle, formulated at the level of behavior, is translated to the dynamics of the synapses. We underpin our results with a number of case studies with high-dimensional robotic systems. We show the spontaneous cooperativity in a complex physical system with decentralized control. Moreover, a jointly controlled humanoid robot develops a high behavioral variety depending on its physics and the environment it is dynamically embedded into. The behavior can be decomposed into a succession of low-dimensional modes that increasingly explore the behavior space. This is a promising way to avoid the curse of dimensionality which hinders learning systems to scale well.Comment: 29 pages, 12 figure

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