Legged locomotion over irregular terrains: State of the art of human and robot performance

Legged robotic technologies have moved out of the lab to operate in real environments, characterized by a wide variety of unpredictable irregularities and disturbances, all this in close proximity with humans. Demonstrating the ability of current robots to move robustly and reliably in these conditions is becoming essential to prove their safe operation. Here, we report an in-depth literature review aimed at verifying the existence of common or agreed protocols and metrics to test the performance of legged system in realistic environments. We primarily focused on three types of robotic technologies, i.e., hexapods, quadrupeds and bipeds. We also included a comprehensive overview on human locomotion studies, being it often considered the gold standard for performance, and one of the most important sources of bioinspiration for legged machines. We discovered that very few papers have rigorously studied robotic locomotion under irregular terrain conditions. On the contrary, numerous studies have addressed this problem on human gait, being nonetheless of highly heterogeneous nature in terms of experimental design. This lack of agreed methodology makes it challenging for the community to properly assess, compare and predict the performance of existing legged systems in real environments. On the one hand, this work provides a library of methods, metrics and experimental protocols, with a critical analysis on the limitations of the current approaches and future promising directions. On the other hand, it demonstrates the existence of an important lack of benchmarks in the literature, and the possibility of bridging different disciplines, e.g., the human and robotic, towards the definition of standardized procedure that will boost not only the scientific development of better bioinspired solutions, but also their market uptake

Examples of Gibsonian Affordances in Legged Robotics Research Using an Empirical, Generative Framework

Evidence from empirical literature suggests that explainable complex behaviors can be built from structured compositions of explainable component behaviors with known properties. Such component behaviors can be built to directly perceive and exploit affordances. Using six examples of recent research in legged robot locomotion, we suggest that robots can be programmed to effectively exploit affordances without developing explicit internal models of them. We use a generative framework to discuss the examples, because it helps us to separate—and thus clarify the relationship between—description of affordance exploitation from description of the internal representations used by the robot in that exploitation. Under this framework, details of the architecture and environment are related to the emergent behavior of the system via a generative explanation. For example, the specific method of information processing a robot uses might be related to the affordance the robot is designed to exploit via a formal analysis of its control policy. By considering the mutuality of the agent-environment system during robot behavior design, roboticists can thus develop robust architectures which implicitly exploit affordances. The manner of this exploitation is made explicit by a well constructed generative explanation

Design and development of a hominid robot with local control in its adaptable feet to enhance locomotion capabilities

With increasing mechanization of our daily lives, the expectations and demands in robotic systems increase in the general public and in scientists alike. In recent events such as the Deepwater Horizon''-accident or the nuclear disaster at Fukushima, mobile robotic systems were used, e.g., to support local task forces by gaining visual material to allow an analysis of the situation. Especially the Fukushima example shows that the robotic systems not only have to face a variety of different tasks during operation but also have to deal with different demands regarding the robot's mobility characteristics. To be able to cope with future requirements, it seems necessary to develop kinematically complex systems that feature several different operating modes. That is where this thesis comes in: A robotic system is developed, whose morphology is oriented on chimpanzees and which has the possibility due to its electro-mechanical structure and the degrees of freedom in its arms and legs to walk with different gaits in different postures. For the proposed robot, the chimpanzee was chosen as a model, since these animals show a multitude of different gaits in nature. A quadrupedal gait like crawl allows the robot to traverse safely and stable over rough terrain. A change into the humanoid, bipedal posture enables the robot to move in man-made environments. The structures, which are necessary to ensure an effective and stable locomotion in these two poses, e.g., the feet, are presented in more detail within the thesis. This includes the biological model and an abstraction to allow a technical implementation. In addition, biological spines are analyzed and the development of an active, artificial spine for the robotic system is described. These additional degrees of freedom can increase the robot's locomotion and manipulation capabilities and even allow to show movements, which are not possible without a spine. Unfortunately, the benefits of using an artificial spine in robotic systems are nowadays still neglected, due to the increased complexity of system design and control. To be able to control such a kinematically complex system, a multitude of sensors is installed within the robot's structures. By placing evaluation electronics close by, a local and decentralized preprocessing is realized. Due to this preprocessing is it possible to realize behaviors on the lowest level of robot control: in this thesis it is exemplarily demonstrated by a local controller in the robot's lower leg. In addition to the development and evaluation of robot's structures, the functionality of the overall system is analyzed in different environments. This includes the presentation of detailed data to show the advantages and disadvantages of the local controller. The robot can change its posture independently from a quadrupedal into a bipedal stance and the other way around without external assistance. Once the robot stands upright, it is to investigate to what extent the quadrupedal walking pattern and control structures (like the local controller) have to be modified to contribute to the bipedal walking as well

Pattern Generation for Rough Terrain Locomotion with Quadrupedal Robots:Morphed Oscillators & Sensory Feedback

Animals are able to locomote on rough terrain without any apparent difficulty, but this does not mean that the locomotor system is simple. The locomotor system is actually a complex multi-input multi-output closed-loop control system. This thesis is dedicated to the design of controllers for rough terrain locomotion, for animal-like quadrupedal robots. We choose the problem of blind rough terrain locomotion as the target of experiments. Blind rough terrain locomotion requires continuous and momentary corrections of leg movements and body posture, and provides a proper testbed to observe the interaction of different mod- ules involved in locomotion control. As for the specific case of this thesis, we have to design rough terrain locomotion controllers that do not depend on the torque-control capability, have limited sensing, and have to be computationally light, all due to the properties of the robotics platform that we use. We propose that a robust locomotion controller, taking into account the aforementioned constraints, is constructed from at least three modules: 1) pattern generators providing the nominal patterns of locomotion; 2) A posture controller continuously adjusting the attitude of the body and keeping the robot upright; and 3) quick reflexes to react to unwanted momentary events like stumbling or an external force impulse. We introduce the framework of morphed oscillators to systematize the design of pattern gen- erators realized as coupled nonlinear oscillators. Morphed oscillators are nonlinear oscillators that can encode arbitrary limit cycle shapes and simultaneously have infinitely large basins of attraction. More importantly, they provide dynamical systems that can assume the role of feedforward locomotion controllers known as Central Pattern Generators (CPGs), and accept discontinuous sensory feedback without the risk of producing discontinuous output. On top of the CPG module, we add a kinematic model-based posture controller inspired by virtual model control (VMC), to control the body attitude. Virtual model control produces forces, and through the application of the Jacobian transpose method, generates torques which are added to the CPG torques. However, because our robots do not have a torque- control capability, we adapt the posture controller by producing task-space velocities instead of forces, thus generating joint-space velocity feedback signals. Since the CPG model used for locomotion generates joint velocities and accepts feedback without the fear of instability or discontinuity, the posture control feedback is easily integrated into the CPG dynamics. More- over, we introduce feedback signals for adjusting the posture by shifting the trunk positions, which directly update the limit cycle shape of the morphed oscillator nodes of the CPG. Reflexes are added, with minimal complexity, to react to momentary events. We implement simple impulse-based feedback mechanisms inspired by animals and successful rough terrain robots to 1) flex the leg if the robot is stumbling (stumbling correction reflex); 2) extend the leg if an expected contact is missing (leg extension reflex); or 3) initiate a lateral stepping sequence in response to a lateral external perturbation. CPG, posture controller, and reflexes are put together in a modular control architecture alongside additional modules that estimate inclination, control speed and direction, maintain timing of feedback signals, etc. [...

Design and Real Time Control of a Versatile Scansorial Robot

This thesis presents investigations into the development of a versatile scansorial mobile robot and real-time realisation of a control system for different configurations of the robot namely climbing mode, walking mode and steering mode. The mobile robot comprises of a hybrid leg and wheel mechanism with innovative design that enables it to interchange its configuration to perform the specific tasks of pole climbing in climbing mode, walking and step climbing in walking mode, and skid steering and inclined slope climbing in steering mode. The motivation of this research is due to the surrounding environment which is not always structured for exploration or navigation missions, and thus poses significant difficulty for the robot to manoeuvre and accomplish the intended task. Hence, the development of versatile scansorial robot with a flexible and interchangeable configuration can provide a broad range of applications and locomotion system and to achieve the mission objective successfully. The robot design consists of four arms/legs with wheel attached at each end-effector and has two link manipulation capability. In climbing mode, the arms are configured as grippers to grip the pole and wheels accelerate to ascend or descend. The climbing angle is monitored to retain the level of the robot while climbing. However, in walking mode, the arms are configured as legs and the wheels are disabled. By implementing a periodic walking gait, the robot is capable of performing stable walking and step climbing. In steering mode, the arms are configured as suspension and the wheels are used for manoeuvring. In this mode, the skid steering system is used to enable the robot perform the turn. The versatile scansorial robot’s configurations and locomotion capabilities are assessed experimentally in real time implementation using the physical prototype. The experiments provided demonstrate the versatility of the robot and successfully fulfill the aims and objectives of the research

Locomoção de humanoides robusta e versátil baseada em controlo analítico e física residual

Humanoid robots are made to resemble humans but their locomotion abilities are far from ours in terms of agility and versatility. When humans walk on complex terrains or face external disturbances, they combine a set of strategies, unconsciously and efficiently, to regain stability. This thesis tackles the problem of developing a robust omnidirectional walking framework, which is able to generate versatile and agile locomotion on complex terrains. We designed and developed model-based and model-free walk engines and formulated the controllers using different approaches including classical and optimal control schemes and validated their performance through simulations and experiments. These frameworks have hierarchical structures that are composed of several layers. These layers are composed of several modules that are connected together to fade the complexity and increase the flexibility of the proposed frameworks. Additionally, they can be easily and quickly deployed on different platforms. Besides, we believe that using machine learning on top of analytical approaches is a key to open doors for humanoid robots to step out of laboratories. We proposed a tight coupling between analytical control and deep reinforcement learning. We augmented our analytical controller with reinforcement learning modules to learn how to regulate the walk engine parameters (planners and controllers) adaptively and generate residuals to adjust the robot’s target joint positions (residual physics). The effectiveness of the proposed frameworks was demonstrated and evaluated across a set of challenging simulation scenarios. The robot was able to generalize what it learned in one scenario, by displaying human-like locomotion skills in unforeseen circumstances, even in the presence of noise and external pushes.Os robôs humanoides são feitos para se parecerem com humanos, mas suas habilidades de locomoção estão longe das nossas em termos de agilidade e versatilidade. Quando os humanos caminham em terrenos complexos ou enfrentam distúrbios externos combinam diferentes estratégias, de forma inconsciente e eficiente, para recuperar a estabilidade. Esta tese aborda o problema de desenvolver um sistema robusto para andar de forma omnidirecional, capaz de gerar uma locomoção para robôs humanoides versátil e ágil em terrenos complexos. Projetámos e desenvolvemos motores de locomoção sem modelos e baseados em modelos. Formulámos os controladores usando diferentes abordagens, incluindo esquemas de controlo clássicos e ideais, e validámos o seu desempenho por meio de simulações e experiências reais. Estes frameworks têm estruturas hierárquicas compostas por várias camadas. Essas camadas são compostas por vários módulos que são conectados entre si para diminuir a complexidade e aumentar a flexibilidade dos frameworks propostos. Adicionalmente, o sistema pode ser implementado em diferentes plataformas de forma fácil. Acreditamos que o uso de aprendizagem automática sobre abordagens analíticas é a chave para abrir as portas para robôs humanoides saírem dos laboratórios. Propusemos um forte acoplamento entre controlo analítico e aprendizagem profunda por reforço. Expandimos o nosso controlador analítico com módulos de aprendizagem por reforço para aprender como regular os parâmetros do motor de caminhada (planeadores e controladores) de forma adaptativa e gerar resíduos para ajustar as posições das juntas alvo do robô (física residual). A eficácia das estruturas propostas foi demonstrada e avaliada em um conjunto de cenários de simulação desafiadores. O robô foi capaz de generalizar o que aprendeu em um cenário, exibindo habilidades de locomoção humanas em circunstâncias imprevistas, mesmo na presença de ruído e impulsos externos.Programa Doutoral em Informátic

Climbing and Walking Robots

Nowadays robotics is one of the most dynamic fields of scientific researches. The shift of robotics researches from manufacturing to services applications is clear. During the last decades interest in studying climbing and walking robots has been increased. This increasing interest has been in many areas that most important ones of them are: mechanics, electronics, medical engineering, cybernetics, controls, and computers. Today’s climbing and walking robots are a combination of manipulative, perceptive, communicative, and cognitive abilities and they are capable of performing many tasks in industrial and non- industrial environments. Surveillance, planetary exploration, emergence rescue operations, reconnaissance, petrochemical applications, construction, entertainment, personal services, intervention in severe environments, transportation, medical and etc are some applications from a very diverse application fields of climbing and walking robots. By great progress in this area of robotics it is anticipated that next generation climbing and walking robots will enhance lives and will change the way the human works, thinks and makes decisions. This book presents the state of the art achievments, recent developments, applications and future challenges of climbing and walking robots. These are presented in 24 chapters by authors throughtot the world The book serves as a reference especially for the researchers who are interested in mobile robots. It also is useful for industrial engineers and graduate students in advanced study

Consider the robot - Abstraction of bioinspired leg coordination and its application to a hexapod robot under consideration of technical constraints

Paskarbeit J. Consider the robot - Abstraction of bioinspired leg coordination and its application to a hexapod robot under consideration of technical constraints. Bielefeld: Universität Bielefeld; 2017.To emulate the movement agility and adaptiveness of stick insects in technical systems such as piezo actuators (Szufnarowski et al. 2014) or hexapod robots (Schneider, Cruse et al. 2006), a direct adaptation of bioinspired walking controllers like WALKNET has often been suggested. However, stick insects have very specific features such as adhesive foot pads that allow them to cling to the ground. Typically, robots do not possess such features. Besides, robots tend to be bigger and heavier than their biological models, usually possessing a different mass distribution as well. This leads to different mechanical and functional properties that need to be addressed in control. Based on the model of the stick insect *Carausius morosus*, the six-legged robot HECTOR was developed in this work to test and evaluate bioinspired controllers. The robot's geometrical layout corresponds to that of the stick insect, scaled up by a factor of 20. Moreover, like the stick insect, the robot features an inherent compliance in its joints. This compliance facilitates walking in uneven terrain since small irregularities can be compensated passively without controller intervention. However, the robot differs from the biological model, e.g., in terms of its size, mass, and mass distribution. Also, it does not possess any means to cling to the ground and therefore must maintain static stability to avoid tilting. To evaluate the ability of stick insects to maintain static stability, experimental data (published by Theunissen et al. (2014)) was examined. It can be shown that stick insects do not maintain static stability at all times. Still, due to their adhesive foot pads, they do not tumble. Therefore, a direct replication of the biological walking controller would not be suitable for the control of HECTOR. In a next step, the bioinspired walking controller WALKNET (Cruse, Kindermann, et al. 1998) was evaluated regarding its applicability for the control of HECTOR. For this purpose, different parametrizations of WALKNET were tested in a simulation environment. For forward walking, parameter sets were found that achieve a high, although not permanent stability. Thus, for the control of HECTOR, which requires continuous stability, a more abstract adaption of the bioinspired coordination had to be found. Based on the original coordination concepts of WALKNET, new coordination mechanisms were developed that incorporate the technical requirements (static stability, angular joint limits, torque constraints, etc.). The ability of the resulting controller to generate insect-like gaits is demonstrated for different walking scenarios in simulation. Moreover, locomotion that is unlikely for insects such as backwards and sidewards walking is shown to be feasible using the novel control approach. At the end of this work the applicability of the approach for the control of the real robot is proved in experiments on visual collision avoidance and basic climbing ability