MOTION CONTROL SIMULATION OF A HEXAPOD ROBOT

This thesis addresses hexapod robot motion control. Insect morphology and locomotion patterns inform the design of a robotic model, and motion control is achieved via trajectory planning and bio-inspired principles. Additionally, deep learning and multi-agent reinforcement learning are employed to train the robot motion control strategy with leg coordination achieves using a multi-agent deep reinforcement learning framework. The thesis makes the following contributions: First, research on legged robots is synthesized, with a focus on hexapod robot motion control. Insect anatomy analysis informs the hexagonal robot body and three-joint single robotic leg design, which is assembled using SolidWorks. Different gaits are studied and compared, and robot leg kinematics are derived and experimentally verified, culminating in a three-legged gait for motion control. Second, an animal-inspired approach employs a central pattern generator (CPG) control unit based on the Hopf oscillator, facilitating robot motion control in complex environments such as stable walking and climbing. The robot\u27s motion process is quantitatively evaluated in terms of displacement change and body pitch angle. Third, a value function decomposition algorithm, QPLEX, is applied to hexapod robot motion control. The QPLEX architecture treats each leg as a separate agent with local control modules, that are trained using reinforcement learning. QPLEX outperforms decentralized approaches, achieving coordinated rhythmic gaits and increased robustness on uneven terrain. The significant of terrain curriculum learning is assessed, with QPLEX demonstrating superior stability and faster consequence. The foot-end trajectory planning method enables robot motion control through inverse kinematic solutions but has limited generalization capabilities for diverse terrains. The animal-inspired CPG-based method offers a versatile control strategy but is constrained to core aspects. In contrast, the multi-agent deep reinforcement learning-based approach affords adaptable motion strategy adjustments, rendering it a superior control policy. These methods can be combined to develop a customized robot motion control policy for specific scenarios

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

Bio-inspired Dynamic Control Systems with Time Delays

The world around us exhibits a rich and ever changing environment of startling, bewildering and fascinating complexity. Almost everything is never as simple as it seems, but through the chaos we may catch fleeting glimpses of the mechanisms within. Throughout the history of human endeavour we have mimicked nature to harness it for our own ends. Our attempts to develop truly autonomous and intelligent machines have however struggled with the limitations of our human ability. This has encouraged some to shirk this responsibility and instead model biological processes and systems to do it for us. This Thesis explores the introduction of continuous time delays into biologically inspired dynamic control systems. We seek to exploit rich temporal dynamics found in physical and biological systems for modelling complex or adaptive behaviour through the artificial evolution of networks to control robots. Throughout, arguments have been presented for the modelling of delays not only to better represent key facets of physical and biological systems, but to increase the computational potential of such systems for the synthesis of control. The thorough investigation of the dynamics of small delayed networks with a wide range of time delays has been undertaken, with a detailed mathematical description of the fixed points of the system and possible oscillatory modes developed to fully describe the behaviour of a single node. Exploration of the behaviour for even small delayed networks illustrates the range of complex behaviour possible and guides the development of interesting solutions. To further exploit the potential of the rich dynamics in such systems, a novel approach to the 3D simulation of locomotory robots has been developed focussing on minimising the computational cost. To verify this simulation tool a simple quadruped robot was developed and the motion of the robot when undergoing a manually designed gait evaluated. The results displayed a high degree of agreement between the simulation and laser tracker data, verifying the accuracy of the model developed. A new model of a dynamic system which includes continuous time delays has been introduced, and its utility demonstrated in the evolution of networks for the solution of simple learning behaviours. A range of methods has been developed for determining the time delays, including the novel concept of representing the time delays as related to the distance between nodes in a spatial representation of the network. The application of these tools to a range of examples has been explored, from Gene Regulatory Networks (GRNs) to robot control and neural networks. The performance of these systems has been compared and contrasted with the efficacy of evolutionary runs for the same task over the whole range of network and delay types. It has been shown that delayed dynamic neural systems are at least as capable as traditional Continuous Time Recurrent Neural Networks (CTRNNs) and show significant performance improvements in the control of robot gaits. Experiments in adaptive behaviour, where there is not such a direct link between the enhanced system dynamics and performance, showed no such discernible improvement. Whilst we hypothesise that the ability of such delayed networks to generate switched pattern generating nodes may be useful in Evolutionary Robotics (ER) this was not borne out here. The spatial representation of delays was shown to be more efficient for larger networks, however these techniques restricted the search to lower complexity solutions or led to a significant falloff as the network structure becomes more complex. This would suggest that for anything other than a simple genotype, the direct method for encoding delays is likely most appropriate. With proven benefits for robot locomotion and the open potential for adaptive behaviour delayed dynamic systems for evolved control remain an interesting and promising field in complex systems research

Tarsal intersegmental reflex responses in the locust hind leg

Locomotion is vital for vertebrates and invertebrates to survive. However, the mechanisms for locomotion are partially unknown. Central Pattern Generators and reflex systems have been shown to be the basis of most movements performed by arthropods. Much has been investigated lately on Central Pattern Generators, but little work has been done in reflex systems. Locomotion and motor output in feet (or tarsus in arthropods) has also been disregarded in research. Despite that feet are responsible for stability and agility in most animals, research on feet movements is scarce.In this thesis the tarsal intersegmental reflex of the locust hind leg is investigated. The tarsal reflex consists of a response in the tarsus when there is a change in the femoro-tibial joint. The main objective of the thesis is to describe the system and to develop mathematical and experimental methods to study, model and analyse it. Through a set of experiments is shown that as the knee joint is extended, the tarsus is depressed, and as the knee joint flexes, the tarsus levates. The experiments demonstrated that there is a purely neuronal link between the femoro-tibial joint position and the tibio-tarsal joint position. Moreover, it also reveals the effect of neuromodulatory compounds, such as dopamine, serotonin or octopamine. The tarsal reflex responses are fairly consistent across individuals, although significant variability across animals was found.To model a system where variability is an issue, a mathematical model with strong generalisation abilities is used: Artificial Neural Networks (ANNs). To design the ANNs, a metaheuristic algorithm has been implemented. The resulting ANNs are shown to be as accurate as other mathematical models used in physiology when used in a well known reflex system, the FETi responses. This results showed that ANNs are as good as Wiener methods in predicting responses and they outperform them in prediction of Gaussian inputs. Furthermore, they are able to predict responses in different animals, independently of the variability, with a more limited performance.New experimental methods are also designed to obtain accurate recordings of tarsal movements in response to knee joint changes. These experimental methods facilitate the data acquisition and its accuracy, reducing measurement errors. Using the mathematical methods validated, these responses are modelled and studied, showing responses to Gaussian and sinusoidal inputs, variability across individuals and effects of neuromodulators.With the tarsal reflex described and modelled, it can be used as a tool for further research in disciplines such as medicine, in the diagnose and treatment of euromuscular dysfunction or design of prosthesis and orthoses. This model can also be implemented in robotics to aid in stability when walking on irregular terrain

Posture control of a low-cost commercially available hexapod robot for uneven terrain locomotion

Legged robots hold the advantage on uneven and irregular terrain, where they exhibit superior mobility over other terrestrial, mobile robots. One of the fundamental ingredients in achieving this exceptional mobility on uneven terrain is posture control, also referred to as attitude control. Many approaches to posture control for multi-legged robots have been taken in the literature; however, the majority of this research has been conducted on custom designed platforms, with sophisticated hardware and, often, fully custom software. Commercially available robots hardly feature in research on uneven terrain locomotion of legged robots, despite the significant advantages they pose over custom designed robots, including drastically lower costs, reusability of parts, and reduced development time, giving them the serious potential to be employed as low-cost research and development platforms. Hence, the aim of this study was to design and implement a posture control system on a low-cost, commercially available hexapod robot – the PhantomX MK-II – overcoming the limitations presented by the lower cost hardware and open source software, while still achieving performance comparable to that exhibited by custom designed robots. For the initial controller development, only the case of the robot standing on all six legs was considered, without accounting for walking motion. This Standing Posture Controller made use of the Virtual Model Control (VMC) strategy, along with a simple foot force distribution rule and a direct force control method for each of the legs, the joints of which can only be position controlled (i.e. they do not have torque control capabilities). The Standing Posture Controller was experimentally tested on level and uneven terrain, as well as on a dynamic balance board. Ground truth measurements of the posture during testing exhibited satisfactory performance, which compared favourably to results of similar tests performed on custom designed platforms. Thereafter, the control system was modified for the more general case of walking. The Walking Posture Controller still made use of VMC for the high-level posture control, but the foot force distribution was expanded to also account for a tripod of ground contact legs during walking. Additionally, the foot force control structure was modified to achieve compliance control of the legs during the swing phase, while still providing direct force control during the stance phase, using the same overall control structure, with a simple switching strategy, all without the need for torque control or modification of the motion control system of the legs, resulting in a novel foot force control system for low-cost, legged robots. Experimental testing of the Walking Posture Controller, with ground truth measurements, revealed that it improved the robot’s posture response by a small amount when walking on flat terrain, while on an uneven terrain setup the maximum roll and pitch angle deviations were reduced by up to 28.6% and 28.1%, respectively, as compared to the uncompensated case. In addition to reducing the maximum deviations on uneven terrain, the overall posture response was significantly improved, resulting in a response much closer to that observed on flat terrain, throughout much of the uneven terrain locomotion. Comparing these results to those obtained in similar tests performed with more sophisticated, custom designed robots, it is evident that the Walking Posture Controller exhibits favourable performance, thus fulfilling the aim of this study.Dissertation (MEng)--University of Pretoria, 2018.Mechanical and Aeronautical EngineeringMEngUnrestricte

An analysis of the locomotory behaviour and functional morphology of errant polychaetes

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp

Kinematická analýza rytmických pohybů: aplikace na třes rukou člověka a kmit křídel mušky octomilky.

Rytmický pohyb, pravidelný nebo nepravidelný, je nedílnou součástí motorického chování a to jak ve zdraví, tak v průběhu nemoci. Hlubší pochopení geneze rytmického pohybu je důležité pro porozumění patofyziologii onemocnění, mezi jejichž projevy rytmický pohyb patří. V disertační práci jsem studovala dva konkrétní aspekty rytmického pohybu: bilaterální koordinaci a modulární řízení. První z nich jsem analyzovala na třesu lidských rukou, druhý na pohybu křídel u modelového organismu Drosophila melanogaster (octomilka obecná). Mnoho typů třesu, včetně fyziologického třesu (PT) a esenciálního tremoru (ET), se vyskytuje v končetinách po obou stranách těla, s podobnou základní frekvencí kmitání. To naznačuje, že kontralaterální třesy mohou mít společný zdroj nebo jsou jinak spojené. Ve své studii jsem prozkoumala vazbu mezi třesem levé a pravé ruky. Pomocí 3D- akcelerometrů jsem změřila časový průběh třesu, a použila stacionární i nestacionární (waveletové) výpočetní metody k vyhodnocení bilaterální koherence. Měření na všech třech prostorových osách umožnilo prozkoumat ucelenější sadu kinematických proměnných, než ve většině předešlých studií. Nestacionární analýza usnadnila identifikaci časově transientní koherence, což je scénář, který se v analýze třesu dříve nebral v úvahu. U většiny subjektů s PT...Rhythmic motions, regular or irregular, are an integral part of motor behavior both in health and in disease. Better understanding of its neural control mechanisms helps in developing methods for controlling the progression of diseases manifesting as rhythmic motions. I studied two specific aspects of rhythmic motions: bilateral coordination of hand tremors in human subjects and modular control of locomotion in invertebrates. Many types of tremors, including the physiological tremor (PT) and the essential tremor (ET) occur in limbs on both the sides of the body, with similar fundamental frequency of the oscillation. This raises the possibility that the contralateral tremors may have a common source or are otherwise coupled. However, while significant contralateral interaction is seen in these two types of tremors, only limited evidence of bilateral coherence has been shown in the previous literature. Therefore, in my study I explored the existence of a weak coupling between the left and right oscillators the may lead to intermittent bilateral coherence. I measured triaxial acceleration of the two hands and systematically assessed their bilateral coherence, using both stationary and non-stationary (wavelet-based) analyses methods. Measuring all three axes allowed examination of a more complete set...Institute of Biophysics and Informatics First Faculty of Medicine Charles University in PragueÚstav biofyziky a informatiky 1. LF UK v PrazeFirst Faculty of Medicine1. lékařská fakult