246 research outputs found

    Trends in the control of hexapod robots: a survey

    Get PDF
    The static stability of hexapods motivates their design for tasks in which stable locomotion is required, such as navigation across complex environments. This task is of high interest due to the possibility of replacing human beings in exploration, surveillance and rescue missions. For this application, the control system must adapt the actuation of the limbs according to their surroundings to ensure that the hexapod does not tumble during locomotion. The most traditional approach considers their limbs as robotic manipulators and relies on mechanical models to actuate them. However, the increasing interest in model-free models for the control of these systems has led to the design of novel solutions. Through a systematic literature review, this paper intends to overview the trends in this field of research and determine in which stage the design of autonomous and adaptable controllers for hexapods is.The first author received funding through a doctoral scholarship from the Portuguese Foundation for Science and Technology (FCT) (Grant No. SFRH/BD/145818/2019), with funds from the Portuguese Ministry of Science, Technology and Higher Education and the European Social Fund through the Programa Operacional Regional Norte. This work has been supported by the FCT national funds, under the national support to R&D units grant, through the reference project UIDB/04436/2020 and UIDP/04436/2020

    Synaptic plasticity in a recurrent neural network for versatile and adaptive behaviors of a walking robot

    Get PDF
    Walking animals, like insects, with little neural computing can effectively perform complex behaviors. They can walk around their environment, escape from corners/deadlocks, and avoid or climb over obstacles. While performing all these behaviors, they can also adapt their movements to deal with an unknown situation. As a consequence, they successfully navigate through their complex environment. The versatile and adaptive abilities are the result of an integration of several ingredients embedded in their sensorimotor loop. Biological studies reveal that the ingredients include neural dynamics, plasticity, sensory feedback, and biomechanics. Generating such versatile and adaptive behaviors for a walking robot is a challenging task. In this study, we present a bio-inspired approach to solve this task. Specifically, the approach combines neural mechanisms with plasticity, sensory feedback, and biomechanics. The neural mechanisms consist of adaptive neural sensory processing and modular neural locomotion control. The sensory processing is based on a small recurrent network consisting of two fully connected neurons. Online correlation-based learning with synaptic scaling is applied to adequately change the connections of the network. By doing so, we can effectively exploit neural dynamics (i.e., hysteresis effects and single attractors) in the network to generate different turning angles with short-term memory for a biomechanical walking robot. The turning information is transmitted as descending steering signals to the locomotion control which translates the signals into motor actions. As a result, the robot can walk around and adapt its turning angle for avoiding obstacles in different situations as well as escaping from sharp corners or deadlocks. Using backbone joint control embedded in the locomotion control allows the robot to climb over small obstacles. Consequently, it can successfully explore and navigate in complex environments

    Variable Configuration Planner for Legged-Rolling Obstacle Negotiation Locomotion: Application on the CENTAURO Robot

    Get PDF
    Hybrid legged-wheeled robots are able to adapt their leg configuration and height to vary their footprint polygons and go over obstacles or traverse narrow spaces. In this paper, we present a variable configuration wheeled motion planner based on the A* algorithm. It takes advantage of the agility of hybrid wheeled-legged robots and plans paths over low-lying obstacles and in narrow spaces. By imposing a symmetry on the robot polygon, the computed plans lie in a low-dimensional search space that provides the robot with configurations to safely negotiate obstacles by expanding or shrinking its footprint polygon. The introduced autonomous planner is demonstrated using simulations and real-world experiments with the CENTAURO robot

    Learning Agility and Adaptive Legged Locomotion via Curricular Hindsight Reinforcement Learning

    Full text link
    Agile and adaptive maneuvers such as fall recovery, high-speed turning, and sprinting in the wild are challenging for legged systems. We propose a Curricular Hindsight Reinforcement Learning (CHRL) that learns an end-to-end tracking controller that achieves powerful agility and adaptation for the legged robot. The two key components are (I) a novel automatic curriculum strategy on task difficulty and (ii) a Hindsight Experience Replay strategy adapted to legged locomotion tasks. We demonstrated successful agile and adaptive locomotion on a real quadruped robot that performed fall recovery autonomously, coherent trotting, sustained outdoor speeds up to 3.45 m/s, and tuning speeds up to 3.2 rad/s. This system produces adaptive behaviours responding to changing situations and unexpected disturbances on natural terrains like grass and dirt

    Reimagining Robotic Walkers For Real-World Outdoor Play Environments With Insights From Legged Robots: A Scoping Review

    Get PDF
    PURPOSE For children with mobility impairments, without cognitive delays, who want to participate in outdoor activities, existing assistive technology (AT) to support their needs is limited. In this review, we investigate the control and design of a selection of robotic walkers while exploring a selection of legged robots to develop solutions that address this gap in robotic AT. METHOD We performed a comprehensive literature search from four main databases: PubMed, Google Scholar, Scopus, and IEEE Xplore. The keywords used in the search were the following: “walker”, “rollator”, “smart walker”, “robotic walker”, “robotic rollator”. Studies were required to discuss the control or design of robotic walkers to be considered. A total of 159 papers were analyzed. RESULTS From the 159 papers, 127 were excluded since they failed to meet our inclusion criteria. The total number of papers analyzed included publications that utilized the same device, therefore we classified the remaining 32 studies into groups based on the type of robotic walker used. This paper reviewed 15 different types of robotic walkers. CONCLUSIONS The ability of many-legged robots to negotiate and transition between a range of unstructured substrates suggests several avenues of future consideration whose pursuit could benefit robotic AT, particularly regarding the present limitations of wheeled paediatric robotic walkers for children’s daily outside use. For more information: Kod*lab (link to kodlab.seas.upenn.edu

    Offline and Online Planning and Control Strategies for the Multi-Contact and Biped Locomotion of Humanoid Robots

    Get PDF
    In the past decades, the Research on humanoid robots made progress forward accomplishing exceptionally dynamic and agile motions. Starting from the DARPA Robotic Challenge in 2015, humanoid platforms have been successfully employed to perform more and more challenging tasks with the eventual aim of assisting or replacing humans in hazardous and stressful working situations. However, the deployment of these complex machines in realistic domestic and working environments still represents a high-level challenge for robotics. Such environments are characterized by unstructured and cluttered settings with continuously varying conditions due to the dynamic presence of humans and other mobile entities, which cannot only compromise the operation of the robotic system but can also pose severe risks both to the people and the robot itself due to unexpected interactions and impacts. The ability to react to these unexpected interactions is therefore a paramount requirement for enabling the robot to adapt its behavior to the task needs and the characteristics of the environment. Further, the capability to move in a complex and varying environment is an essential skill for a humanoid robot for the execution of any task. Indeed, human instructions may often require the robot to move and reach a desired location, e.g., for bringing an object or for inspecting a specific place of an infrastructure. In this context, a flexible and autonomous walking behavior is an essential skill, study of which represents one of the main topics of this Thesis, considering disturbances and unfeasibilities coming both from the environment and dynamic obstacles that populate realistic scenarios.  Locomotion planning strategies are still an open theme in the humanoids and legged robots research and can be classified in sample-based and optimization-based planning algorithms. The first, explore the configuration space, finding a feasible path between the start and goal robot’s configuration with different logic depending on the algorithm. They suffer of a high computational cost that often makes difficult, if not impossible, their online implementations but, compared to their counterparts, they do not need any environment or robot simplification to find a solution and they are probabilistic complete, meaning that a feasible solution can be certainly found if at least one exists. The goal of this thesis is to merge the two algorithms in a coupled offline-online planning framework to generate an offline global trajectory with a sample-based approach to cope with any kind of cluttered and complex environment, and online locally refine it during the execution, using a faster optimization-based algorithm that more suits an online implementation. The offline planner performances are improved by planning in the robot contact space instead of the whole-body robot configuration space, requiring an algorithm that maps the two state spaces.   The framework proposes a methodology to generate whole-body trajectories for the motion of humanoid and legged robots in realistic and dynamically changing environments.  This thesis focuses on the design and test of each component of this planning framework, whose validation is carried out on the real robotic platforms CENTAURO and COMAN+ in various loco-manipulation tasks scenarios. &nbsp
    • 

    corecore