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

Climbing and Walking Robots

With the advancement of technology, new exciting approaches enable us to render mobile robotic systems more versatile, robust and cost-efficient. Some researchers combine climbing and walking techniques with a modular approach, a reconfigurable approach, or a swarm approach to realize novel prototypes as flexible mobile robotic platforms featuring all necessary locomotion capabilities. The purpose of this book is to provide an overview of the latest wide-range achievements in climbing and walking robotic technology to researchers, scientists, and engineers throughout the world. Different aspects including control simulation, locomotion realization, methodology, and system integration are presented from the scientific and from the technical point of view. This book consists of two main parts, one dealing with walking robots, the second with climbing robots. The content is also grouped by theoretical research and applicative realization. Every chapter offers a considerable amount of interesting and useful information

A Design for Proprioceptive Force in 3D Agility Robot Through Use of AI

For robots to be considered effective, they should be able to maneuver through 3D environments. To achieve such mobility, robots needs to be designed in such a way that would span various topographies. So, artificial intelligence algorithms have been developed to ensure agility of the robots when walking on murky topographies. In the current state of the art legged robots, there is still much progress need to be made in research to turn them into automobiles with great agility to be used in the real world utility and provide mobility in rough. GOAT leg as a means of artificial intelligence is still a new phenomenon. There still exists a number of preliminary tests that need to be done in accessing and in the characterization of the leg’s current performance and its implications in the future. This study seeks to develop and agility model which would be useful in ensuring that the robots remain agile in such complex environments. To do this, a simulation has been through Matlab analysis. Results of the current study showed that, 3-RSR was designed to ensure that a high fidelity proprioceptive force control would enable legs with the mechanically spring stiffness. Implications and future recommendations also discussed

Adaptive, fast walking in a biped robot under neuronal control and learning

Human walking is a dynamic, partly self-stabilizing process relying on the interaction of the biomechanical design with its neuronal control. The coordination of this process is a very difficult problem, and it has been suggested that it involves a hierarchy of levels, where the lower ones, e.g., interactions between muscles and the spinal cord, are largely autonomous, and where higher level control (e.g., cortical) arises only pointwise, as needed. This requires an architecture of several nested, sensori–motor loops where the walking process provides feedback signals to the walker's sensory systems, which can be used to coordinate its movements. To complicate the situation, at a maximal walking speed of more than four leg-lengths per second, the cycle period available to coordinate all these loops is rather short. In this study we present a planar biped robot, which uses the design principle of nested loops to combine the self-stabilizing properties of its biomechanical design with several levels of neuronal control. Specifically, we show how to adapt control by including online learning mechanisms based on simulated synaptic plasticity. This robot can walk with a high speed (> 3.0 leg length/s), self-adapting to minor disturbances, and reacting in a robust way to abruptly induced gait changes. At the same time, it can learn walking on different terrains, requiring only few learning experiences. This study shows that the tight coupling of physical with neuronal control, guided by sensory feedback from the walking pattern itself, combined with synaptic learning may be a way forward to better understand and solve coordination problems in other complex motor tasks