Gait Generation for Damaged Hexapods using Genetic Algorithm

This paper discusses the design and implementation of a Genetic Algorithm for the generation of gaits compensating for system damage on the joint level of a hexapod system. The hexapod base used for this algorithm consists of six three degree of freedom legs on a rectangular body. The purpose of this algorithm is to generate a gait such that when N motors become inoperable, as detected by the robot’s internal software, the system is able to continue moving about its environment. While algorithms like this have been implemented before, the generated gaits are a sequence of discrete foot positions. This work aims to generate continuous motions profiles for each joint of the leg rather than discrete foot positions. Previous works commonly disable an entire leg when damage occurs, instead this work aims to disable only individual joint motors

Design of a Biomimetic Mechanical Leg and Accompanying Sensor System for Terrain Detection

Autonomous robots are useful in a wide range of applications. However, finding a balance between speed and stability in an autonomous robot can be difficult. The goal of this project was to design a biomimetically-inspired robotic leg and accompanying sensor system for detecting terrain; the mechanical leg and sensor system designs in combination are intended to enable a quadruped robot to move quickly while maintaining its stability. In order to accomplish this goal, a leg was designed based on the leg of a cheetah and the team performed a variety of mechanical analyses on it. Additionally, the output from a force sensor landing on hard and muddy surfaces was collected and algorithms for determining which of the two surfaces the robot was walking on were developed

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

New Joint Design to Create a More Natural and Efficient Biped

This paper presents a human-oriented approach to design the mechanical architecture and the joint controller for a biped robot. Starting from the analysis of the human lower limbs, we figured out which features of the human legs are fundamental for a correct walking motion, and can be adopted in the mechanical design of a humanoid robot. We focus here on the knee, designed as a compliant human-like knee instead of a classical pin-joint, and on the foot, characterised by the mobility and lightness of the human foot. We implemented an elastic actuator, with a simple position control paradigm that sets the joint stiffness in real time, and developed the basic controller. Results in simulation are discussed. In our approach the robot gains in adaptability and energetic efficiency, which are the most challenging issues for a biped robot

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

Evaluation Of Impedance Control On A Powered Hip Exoskeleton

This thesis presents an impedance control strategy for a novel powered hip exoskeleton designed to provide partial assistance and leverage the dynamics of human gait. The control strategy is based on impedance control and provides the user assistance as needed which is determined by the user’s interaction with the exoskeleton. A series elastic element is used to drive the exoskeleton and measures the interaction torque between the user and the device. The device operates in two modes. Free mode is a low impedance state that attempts to provide no assistance. Assist mode increases the gains of the controller to provide assistance as needed. The device was tested on five healthy subjects, and the resulting assistive hip torque was evaluated to determine the ability of the controller to provide gait assistance. The device was evaluated at different speeds to assess the gait speed adaptation performance of the controller. Results show that hip torque assistance range was between 0.3 to 0.5 Nm/kg across the subjects, corresponding to 24% to 40% of the maximum hip torque requirements of healthy adults during walking. The peak power provided by the system is 35 W on average and a peak power of up to 45 W

Evolving Predator Control Programs for an Actual Hexapod Robot Predator

In the development of autonomous robots, control program learning systems are important since they allow the robots to adapt to changes in their surroundings. Evolutionary Computation (EC) is a method that is used widely in learning systems. In previous research, we used a Cyclic Genetic Algorithm (CGA), a form of EC, to evolve a simulated predator robot to test the effectiveness of a learning system in the predator/prey problem. The learned control program performed search, chase, and capture behavior using 64 sensor states relative to the nearest obstacle and the target, a simulated prey robot. In this paper, we present the results of a new set of trials, which were tested on the actual robots. The actual robots successfully performed desired behaviors, showing the effectiveness of the CGA learning system

Locomotion performance of hexapod robots on rough substrates and the influence of leg compliance

ABSTRACT OF THE THESISLocomotion performance of hexapod robots on rough substrates and the influence of leg compliancebyAmartya Bhattacharyya Master of Science in Engineering Sciences (Mechanical Engineering)University of California San Diego, 2019Professor Nicholas Gravish, ChairHexapod Robots are a complex system where six legs are connected to the main body which acts as a support frame. A lot of research has been performed in this field from the study of six legged insects to present day implementations where the robot uses its own decision making network. The motivation for this field are the various advantages that hexapedal robots provide like; Obstacle climbing capability, omnidirectional motion, variable geometry, stability, access to uneven terrain etc. At the same time they also have many disadvantages like low energy efficiency, low speeds, complexity of operation and design and especially a lot of attention has to be given to path and gait planning. Therefore, in this paper wexiiuse an open loop platform for our robot and test the performance on simulated rough substrates. Using the results we propose a compliant leg design which will improve the performance while maintaining the stability. We compare the new design with solid legs to quantify the gain. And also test for the shear force limits to make sure the design is ready to be tested on a robot for full length runs. With a goal to utilize the new design and simplify the requirements of complicated neural networks for gait planning