Design Issues for Hexapod Walking Robots

Hexapod walking robots have attracted considerable attention for several decades. Many studies have been carried out in research centers, universities and industries. However, only in the recent past have efficient walking machines been conceived, designed and built with performances that can be suitable for practical applications. This paper gives an overview of the state of the art on hexapod walking robots by referring both to the early design solutions and the most recent achievements. Careful attention is given to the main design issues and constraints that influence the technical feasibility and operation performance. A design procedure is outlined in order to systematically design a hexapod walking robot. In particular, the proposed design procedure takes into account the main features, such as mechanical structure and leg configuration, actuating and driving systems, payload, motion conditions, and walking gait. A case study is described in order to show the effectiveness and feasibility of the proposed design procedure

Biomimetic oscillating foil propulsion to enhance underwater vehicle agility and maneuverability

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution June 2008Inspired by the swimming abilities of marine animals, this thesis presents "Finnegan the RoboTurtle", an autonomous underwater vehicle (AUV) powered entirely by four flapping foils. Biomimetic actuation is shown to produce dramatic improvements in AUV maneuvering at cruising speeds, while simultaneously allowing for agility at low speeds. Using control algorithms linear in the modified Rodrigues parameters to support large angle maneuvers, the vehicle is successfully controlled in banked and twisting turns, exceeding the best reported AUV turning performance by more than a factor of two; a minimum turning radius of 0.7BL, and the ability to avoid walls detected> 1.8BL ahead, are found for cruising speeds of 0.75BL/S, with a maximum heading rate of 400 / S recorded. Observations of "Myrtle", a 250kg Green sea turtle (Chelonia mydas) at the New England Aquarium, are detailed; along with steady swimming, Myrtle is observed performing 1800 level turns and rapidly actuating pitch to control depth and speed. Limb kinematics for the level turning maneuver are replicated by Finnegan, and turning rates comparable to those of the turtle are achieved. Foil kinematics which produce approximately sinusoidal nominal angle of attack trace are shown to improve turning performance by as much as 25%; the effect is achieved despite limited knowledge of the flow field. Finally, tests with a single foil are used to demonstrate that biomimetically inspired inline motion can allow oscillating foils utilizing a power/recovery style stroke to generate as much as 90% of the thrust from a power/power stroke style motion

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

Deep reinforcement learning for soft, flexible robots : brief review with impending challenges

The increasing trend of studying the innate softness of robotic structures and amalgamating it with the benefits of the extensive developments in the field of embodied intelligence has led to the sprouting of a relatively new yet rewarding sphere of technology in intelligent soft robotics. The fusion of deep reinforcement algorithms with soft bio-inspired structures positively directs to a fruitful prospect of designing completely self-sufficient agents that are capable of learning from observations collected from their environment. For soft robotic structures possessing countless degrees of freedom, it is at times not convenient to formulate mathematical models necessary for training a deep reinforcement learning (DRL) agent. Deploying current imitation learning algorithms on soft robotic systems has provided competent results. This review article posits an overview of various such algorithms along with instances of being applied to real-world scenarios, yielding frontier results. Brief descriptions highlight the various pristine branches of DRL research in soft robotics

Kinetic energy fluctuation-driven locomotor transitions on potential energy landscapes of beam obstacle traversal and self-righting

Despite contending with constraints imposed by the environment, morphology, and physiology, animals move well by physically interactingwith the environment to use and transition between modes such as running, climbing, and self-righting. By contrast, robots struggle to do so in real world. Understanding the principles of how locomotor transitions emerge from constrained physical interaction is necessary for robots to move robustly using similar strategies. Recent studies discovered that discoid cockroaches use and transition between diverse locomotor modes to traverse beams and self-right on ground. For both systems, animals probabilistically transitioned between modes via multiple pathways, while its self-propulsion created kinetic energy fluctuation. Here, we seek mechanistic explanations for these observations by adopting a physics-based approach that integrates biological and robotic studies. We discovered that animal and robot locomotor transitions during beam obstacle traversal and ground self-righting are barrier-crossing transitions on potential energy landscapes. Whereas animals and robot traversed stiff beams by rolling their body betweenbeam, they pushed across flimsy beams, suggesting a concept of terradynamic favorability where modes with easier physical interaction are more likely to occur. Robotic beam traversal revealed that, system state either remains in a favorable mode or transitions to one when energy fluctuation is comparable to the transition barrier. Robotic self-righting transitions occurred similarly and revealed that changing system parameters lowers barriers over which comparable fluctuation can induce transitions. Thetransitionsof animalsin both systems mostly occurred similarly, but sensory feedback may facilitate its beam traversal. Finally, we developed a method to measure animal movement across large spatiotemporal scales in a terrain treadmill.Comment: arXiv admin note: substantial text overlap with arXiv:2006.1271

Proceedings of the Post-Graduate Conference on Robotics and Development of Cognition, 10-12 September 2012, Lausanne, Switzerland

The aim of the Postgraduate Conference on Robotics and Development of Cognition (RobotDoC-PhD) is to bring together young scientists working on developmental cognitive robotics and its core disciplines. The conference aims to provide both feedback and greater visibility to their research as lively and stimulating discussion can be held amongst participating PhD students and senior researchers. The conference is open to all PhD students and post-doctoral researchers in the field. RobotDoC-PhD conference is an initiative as a part of Marie-Curie Actions ITN RobotDoC and will be organized as a satellite event of the 22nd International Conference on Artificial Neural Networks ICANN 2012

Proceedings of the Post-Graduate Conference on Robotics and Development of Cognition, 10-12 September 2012, Lausanne, Switzerland

The aim of the Postgraduate Conference on Robotics and Development of Cognition (RobotDoC-PhD) is to bring together young scientists working on developmental cognitive robotics and its core disciplines. The conference aims to provide both feedback and greater visibility to their research as lively and stimulating discussion can be held amongst participating PhD students and senior researchers. The conference is open to all PhD students and post-doctoral researchers in the field. RobotDoC-PhD conference is an initiative as a part of Marie-Curie Actions ITN RobotDoC and will be organized as a satellite event of the 22nd International Conference on Artificial Neural Networks ICANN 2012

A Perspective on Cephalopods Mimicry and Bioinspired Technologies toward Proprioceptive Autonomous Soft Robots

Octopus skin is an amazing source of inspiration for bioinspired sensors, actuators and control solutions in soft robotics. Soft organic materials, biomacromolecules and protein ingredients in octopus skin combined with a distributed intelligence, result in adaptive displays that can control emerging optical behavior, and 3D surface textures with rough geometries, with a remarkably high control speed (≈ms). To be able to replicate deformable and compliant materials capable of translating mechanical perturbations in molecular and structural chromogenic outputs, could be a glorious achievement in materials science and in the technological field. Soft robots are suitable platforms for soft multi-responsive materials, which can provide them with improved mechanical proprioception and related smarter behaviors. Indeed, a system provided with a “learning and recognition” functions, and a constitutive “mechanical” and “material intelligence” can result in an improved morphological adaptation in multi-variate environments responding to external and internal stimuli. This review aims to explore challenges and opportunities related to smart and chromogenic responsive materials for adaptive displays, reconfigurable and programmable soft skin, proprioceptive sensing system, and synthetic nervous control units for data processing, toward autonomous soft robots able to communicate and interact with users in open-world scenarios

Control of Bio-Inspired Sprawling Posture Quadruped Robots with an Actuated Spine

Sprawling posture robots are characterized by upper limb segments protruding horizontally from the body, resulting in lower body height and wider support on the ground. Combined with an actuated segmented spine and tail, such morphology resembles that of salamanders or crocodiles. Although bio-inspired salamander-like robots with simple rotational limbs have been created, not much research has been done on kinematically redundant bio-mimetic robots that can closely replicate kinematics of sprawling animal gaits. Being bio-mimetic could allow a robot to have some of the locomotion skills observed in those animals, expanding its potential applications in challenging scenarios. At the same time, the robot could be used to answer questions about the animal's locomotion. This thesis is focused on developing locomotion controllers for such robots. Due to their high number of degrees of freedom (DoF), the control is based on solving the limb and spine inverse kinematics to properly coordinate different body parts. It is demonstrated how active use of a spine improves the robot's walking and turning performance. Further performance improvement across a variety of gaits is achieved by using model predictive control (MPC) methods to dictate the motion of the robot's center of mass (CoM). The locomotion controller is reused on an another robot (OroBOT) with similar morphology, designed to mimic the kinematics of a fossil belonging to Orobates, an extinct early tetrapod. Being capable of generating different gaits and quantitatively measuring their characteristics, OroBOT was used to find the most probable way the animal moved. This is useful because understanding locomotion of extinct vertebrates helps to conceptualize major transitions in their evolution. To tackle field applications, e.g. in disaster response missions, a new generation of field-oriented sprawling posture robots was built. The robustness of their initial crocodile-inspired design was tested in the animal's natural habitat (Uganda, Africa) and subsequently enhanced with additional sensors, cameras and computer. The improvements to the software framework involved a smartphone user interface visualizing the robot's state and camera feed to improve the ease of use for the operator. Using force sensors, the locomotion controller is expanded with a set of reflex control modules. It is demonstrated how these modules improve the robot's performance on rough and unstructured terrain. The robot's design and its low profile allow it to traverse low passages. To also tackle narrow passages like pipes, an unconventional crawling gait is explored. While using it, the robot lies on the ground and pushes against the pipe walls to move the body. To achieve such a task, several new control and estimation modules were developed. By exploring these problems, this thesis illustrates fruitful interactions that can take place between robotics, biology and paleontology