82 research outputs found
Learning Agility and Adaptive Legged Locomotion via Curricular Hindsight Reinforcement Learning
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
Genetically evolved dynamic control for quadruped walking
The aim of this dissertation is to show that dynamic control of quadruped locomotion is achievable through the use of genetically evolved central pattern generators. This strategy is tested both in simulation and on a walking robot. The design of the walker has been chosen to be statically unstable, so that during motion less than three supporting feet may be in contact with the ground.
The control strategy adopted is capable of propelling the artificial walker at a forward locomotion speed of ~1.5 Km/h on rugged terrain and provides for stability of motion. The learning of walking, based on simulated genetic evolution, is carried out in simulation to speed up the process and reduce the amount of damage to the hardware of the walking robot. For this reason a general-purpose fast dynamic simulator has been developed, able to efficiently compute the forward dynamics of tree-like robotic mechanisms.
An optimization process to select stable walking patterns is implemented through a purposely designed genetic algorithm, which implements stochastic mutation and cross-over operators. The algorithm has been tailored to address the high cost of evaluation of the optimization function, as well as the characteristics of the parameter space chosen to represent controllers.
Experiments carried out on different conditions give clear indications on the potential of the approach adopted. A proof of concept is achieved, that stable dynamic walking can be obtained through a search process which identifies attractors in the dynamics of the motor-control system of an artificial walker
Real-time Perceptive Motion Control using Control Barrier Functions with Analytical Smoothing for Six-Wheeled-Telescopic-Legged Robot Tachyon 3
To achieve safe legged locomotion, it is important to generate motion in
real-time considering various constraints in robots and environments. In this
study, we propose a lightweight real-time perspective motion control system for
the newly developed six-wheeled-telescopic-legged robot, Tachyon 3. In the
proposed method, analytically smoothed constraints including Smooth Separating
Axis Theorem (Smooth SAT) as a novel higher order differentiable collision
detection for 3D shapes is applied to the Control Barrier Function (CBF). The
proposed system integrating the CBF achieves online motion generation in a
short control cycle of 1 ms that satisfies joint limitations, environmental
collision avoidance and safe convex foothold constraints. The efficiency of
Smooth SAT is shown from the collision detection time of 1 us or less and the
CBF constraint computation time for Tachyon3 of several us. Furthermore, the
effectiveness of the proposed system is verified through the stair-climbing
motion, integrating online recognition in a simulation and a real machine.Comment: 8 pages, 8 figures, This work has been submitted to the IEEE for
possible publication. Copyright may be transferred without notice, after
which this version may no longer be accessibl
Legged Robots for Object Manipulation: A Review
Legged robots can have a unique role in manipulating objects in dynamic,
human-centric, or otherwise inaccessible environments. Although most legged
robotics research to date typically focuses on traversing these challenging
environments, many legged platform demonstrations have also included "moving an
object" as a way of doing tangible work. Legged robots can be designed to
manipulate a particular type of object (e.g., a cardboard box, a soccer ball,
or a larger piece of furniture), by themselves or collaboratively. The
objective of this review is to collect and learn from these examples, to both
organize the work done so far in the community and highlight interesting open
avenues for future work. This review categorizes existing works into four main
manipulation methods: object interactions without grasping, manipulation with
walking legs, dedicated non-locomotive arms, and legged teams. Each method has
different design and autonomy features, which are illustrated by available
examples in the literature. Based on a few simplifying assumptions, we further
provide quantitative comparisons for the range of possible relative sizes of
the manipulated object with respect to the robot. Taken together, these
examples suggest new directions for research in legged robot manipulation, such
as multifunctional limbs, terrain modeling, or learning-based control, to
support a number of new deployments in challenging indoor/outdoor scenarios in
warehouses/construction sites, preserved natural areas, and especially for home
robotics.Comment: Preprint of the paper submitted to Frontiers in Mechanical
Engineerin
Motion Planning and Control of Dynamic Humanoid Locomotion
Inspired by human, humanoid robots has the potential to become a general-purpose platform that lives along with human. Due to the technological advances in many field, such as actuation, sensing, control and intelligence, it finally enables humanoid robots to possess human comparable capabilities. However, humanoid locomotion is still a challenging research field. The large number of degree of freedom structure makes the system difficult to coordinate online. The presence of various contact constraints and the hybrid nature of locomotion tasks make the planning a harder problem to solve. Template model anchoring approach has been adopted to bridge the gap between simple model behavior and the whole-body motion of humanoid robot.
Control policies are first developed for simple template models like Linear Inverted Pendulum Model (LIPM) or Spring Loaded Inverted Pendulum(SLIP), the result controlled behaviors are then been mapped to the whole-body motion of humanoid robot through optimization-based task-space control strategies. Whole-body humanoid control framework has been verified on various contact situations such as unknown uneven terrain, multi-contact scenarios and moving platform and shows its generality and versatility. For walking motion, existing Model Predictive Control approach based on LIPM has been extended to enable the robot to walk without any reference foot placement anchoring. It is kind of discrete version of \u201cwalking without thinking\u201d.
As a result, the robot could achieve versatile locomotion modes such as automatic foot placement with single reference velocity command, reactive stepping under large external disturbances, guided walking with small constant external pushing forces, robust walking on unknown uneven terrain, reactive stepping in place when blocked by external barrier. As an extension of this proposed framework, also to increase the push recovery capability of the humanoid robot, two new configurations have been proposed to enable the robot to perform cross-step motions. For more dynamic hopping and running motion, SLIP model has been chosen as the template model. Different from traditional model-based analytical approach, a data-driven approach has been proposed to encode the dynamics of the this model. A deep neural network is trained offline with a large amount of simulation data based on the SLIP model to learn its dynamics.
The trained network is applied online to generate reference foot placements for the humanoid robot. Simulations have been performed to evaluate the effectiveness of the proposed approach in generating bio-inspired and robust running motions. The method proposed based on 2D SLIP model can be generalized to 3D SLIP model and the extension has been briefly mentioned at the end
Oncilla robot: a versatile open-source quadruped research robot with compliant pantograph legs
We present Oncilla robot, a novel mobile, quadruped legged locomotion
machine. This large-cat sized, 5.1 robot is one of a kind of a recent,
bioinspired legged robot class designed with the capability of model-free
locomotion control. Animal legged locomotion in rough terrain is clearly shaped
by sensor feedback systems. Results with Oncilla robot show that agile and
versatile locomotion is possible without sensory signals to some extend, and
tracking becomes robust when feedback control is added (Ajaoolleian 2015). By
incorporating mechanical and control blueprints inspired from animals, and by
observing the resulting robot locomotion characteristics, we aim to understand
the contribution of individual components. Legged robots have a wide mechanical
and control design parameter space, and a unique potential as research tools to
investigate principles of biomechanics and legged locomotion control. But the
hardware and controller design can be a steep initial hurdle for academic
research. To facilitate the easy start and development of legged robots,
Oncilla-robot's blueprints are available through open-source. [...
A Bio-inspired architecture for adaptive quadruped locomotion over irregular terrain
Tese de doutoramento
Programa Doutoral em Engenharia Electrónica e de ComputadoresThis thesis presents a tentative advancement on walking control of small quadruped and humanoid
position controlled robots, addressing the problem of walk generation by combining dynamical systems
approach to motor control, insights from neuroethology research on vertebrate motor control and
computational neuroscience.
Legged locomotion is a complex dynamical process, despite the seemingly easy and natural behavior
of the constantly present proficiency of legged animals. Research on locomotion and motor control
in vertebrate animals from the last decades has brought to the attention of roboticists, the potential of
the nature’s solutions to robot applications. Recent knowledge on the organization of complex motor
generation and on mechanics and dynamics of locomotion has been successfully exploited to pursue
agile robot locomotion.
The work presented on this manuscript is part of an effort on the pursuit in devising a general,
model free solution, for the generation of robust and adaptable walking behaviors. It strives to devise a
practical solution applicable to real robots, such as the Sony’s quadruped AIBO and Robotis’ DARwIn-
OP humanoid. The discussed solutions are inspired on the functional description of the vertebrate
neural systems, especially on the concept of Central Pattern Generators (CPGs), their structure and
organization, components and sensorimotor interactions. They use a dynamical systems approach for
the implementation of the controller, especially on the use of nonlinear oscillators and exploitation of
their properties.
The main topics of this thesis are divided into three parts.
The first part concerns quadruped locomotion, extending a previous CPG solution using nonlinear
oscillators, and discussing an organization on three hierarchical levels of abstraction, sharing the purpose
and knowledge of other works. It proposes a CPG solution which generates the walking motion
for the whole-leg, which is then organized in a network for the production of quadrupedal gaits. The
devised solution is able to produce goal-oriented locomotion and navigation as directed through highlevel
commands from local planning methods. In this part, active balance on a standing quadruped is
also addressed, proposing a method based on dynamical systems approach, exploring the integration of
parallel postural mechanisms from several sensory modalities. The solutions are all successfully tested on the quadruped AIBO robot.
In the second part, is addressed bipedal walking for humanoid robots. A CPG solution for biped
walking based on the concept of motion primitives is proposed, loosely based on the idea of synergistic
organization of vertebrate motor control. A set of motion primitives is shown to produce the basis
of simple biped walking, and generalizable to goal-oriented walking. Using the proposed CPG, the
inclusion of feedback mechanisms is investigated, for modulation and adaptation of walking, through
phase transition control according to foot load information. The proposed solution is validated on the
humanoid DARwIn-OP, and its application is evaluated within a whole-body control framework.
The third part sidesteps a little from the other two topics. It discusses the CPG as having an alternative
role to direct motor generation in locomotion, serving instead as a processor of sensory information
for a feedback based motor generation. In this work a reflex based walking controller is devised for the
compliant quadruped Oncilla robot, to serve as purely feedback based walking generation. The capabilities
of the reflex network are shown in simulations, followed by a brief discussion on its limitations,
and how they could be improved by the inclusion of a CPG.Esta tese apresenta uma tentativa de avanço no controlo de locomoção para pequenos robôs quadrúpedes
e bipedes controlados por posição, endereçando o problema de geração motora através da combinação
da abordagem de sistemas dinâmicos para o controlo motor, e perspectivas de investigação
neuroetologia no controlo motor vertebrado e neurociência computacional.
Andar é um processo dinâmico e complexo, apesar de parecer um comportamento fácil e natural
devido à presença constante de animais proficientes em locomoção terrestre. Investigação na área da locomoção
e controlo motor em animais vertebrados nas últimas decadas, trouxe à atenção dos roboticistas
o potencial das soluções encontradas pela natureza aplicadas a aplicações robóticas. Conhecimento
recente relativo à geração de comportamentos motores complexos e da mecânica da locomoção tem
sido explorada com sucesso na procura de locomoção ágil na robótica.
O trabalho apresentado neste documento é parte de um esforço no desenho de uma solução geral,
e independente de modelos, para a geração robusta e adaptável de comportamentos locomotores. O
foco é desenhar uma solução prática, aplicável a robôs reais, tal como o quadrúpede Sony AIBO e
o humanóide DARwIn-OP. As soluções discutidas são inspiradas na descrição funcional do sistema
nervoso vertebrado, especialmente no conceito de Central Pattern Generators (CPGs), a sua estrutura e
organização, componentes e interacção sensorimotora. Estas soluções são implementadas usando uma
abordagem em sistemas dinâmicos, focandos o uso de osciladores não lineares e a explorando as suas
propriedades.
Os tópicos principais desta tese estão divididos em três partes.
A primeira parte explora o tema de locomoção quadrúpede, expandindo soluções prévias de CPGs
usando osciladores não lineares, e discutindo uma organização em três níveis de abstracção, partilhando
as ideias de outros trabalhos. Propõe uma solução de CPG que gera os movimentos locomotores
para uma perna, que é depois organizado numa rede, para a produção de marcha quadrúpede. A
solução concebida é capaz de produzir locomoção e navegação, comandada através de comandos de alto
nível, produzidos por métodos de planeamento local. Nesta parte também endereçado o problema da
manutenção do equilíbrio num robô quadrúpede parado, propondo um método baseado na abordagem
em sistemas dinâmicos, explorando a integração de mecanismos posturais em paralelo, provenientes de várias modalidades sensoriais. As soluções são todas testadas com sucesso no robô quadrupede AIBO.
Na segunda parte é endereçado o problema de locomoção bípede. É proposto um CPG baseado
no conceito de motion primitives, baseadas na ideia de uma organização sinergética do controlo motor
vertebrado. Um conjunto de motion primitives é usado para produzir a base de uma locomoção bípede
simples e generalizável para navegação. Esta proposta de CPG é usada para de seguida se investigar
a inclusão de mecanismos de feedback para modulação e adaptação da marcha, através do controlo de
transições entre fases, de acordo com a informação de carga dos pés. A solução proposta é validada
no robô humanóide DARwIn-OP, e a sua aplicação no contexto do framework de whole-body control é
também avaliada.
A terceira parte desvia um pouco dos outros dois tópicos. Discute o CPG como tendo um papel
alternativo ao controlo motor directo, servindo em vez como um processador de informação sensorial
para um mecanismo de locomoção puramente em feedback. Neste trabalho é desenhado um controlador
baseado em reflexos para a geração da marcha de um quadrúpede compliant. As suas capacidades são
demonstradas em simulação, seguidas por uma breve discussão nas suas limitações, e como estas podem
ser ultrapassadas pela inclusão de um CPG.The presented work was possible thanks to the support by the Portuguese Science and Technology Foundation through the PhD grant SFRH/BD/62047/2009
Online Optimization-based Gait Adaptation of Quadruped Robot Locomotion
Quadruped robots demonstrated extensive capabilities of traversing complex and unstructured
environments. Optimization-based techniques gave a relevant impulse to the research on legged
locomotion. Indeed, by designing the cost function and the constraints, we can guarantee the
feasibility of a motion and impose high-level locomotion tasks, e.g., tracking of a reference
velocity. This allows one to have a generic planning approach without the need to tailor a
specific motion for each terrain, as in the heuristic case. In this context, Model Predictive
Control (MPC) can compensate for model inaccuracies and external disturbances, thanks to
the high-frequency replanning.
The main objective of this dissertation is to develop a Nonlinear MPC (NMPC)-based
locomotion framework for quadruped robots. The aim is to obtain an algorithm which can
be extended to different robots and gaits; in addition, I sought to remove some assumptions
generally done in the literature, e.g., heuristic reference generator and user-defined gait
sequence.
The starting point of my work is the definition of the Optimal Control Problem to generate
feasible trajectories for the Center of Mass. It is descriptive enough to capture the linear and
angular dynamics of the robot as a whole. A simplified model (Single Rigid Body Dynamics
model) is used for the system dynamics, while a novel cost term maximizes leg mobility
to improve robustness in the presence of nonflat terrain. In addition, to test the approach
on the real robot, I dedicated particular effort to implementing both a heuristic reference
generator and an interface for the controller, and integrating them into the controller framework
developed previously by other team members.
As a second contribution of my work, I extended the locomotion framework to deal with a
trot gait. In particular, I generalized the reference generator to be based on optimization.
Exploiting the Linear Inverted Pendulum model, this new module can deal with the underactuation of the trot when only two legs are in contact with the ground, endowing the NMPC
with physically informed reference trajectories to be tracked. In addition, the reference velocities are used to correct the heuristic footholds, obtaining contact locations coherent with
the motion of the base, even though they are not directly optimized.
The model used by the NMPC receives as input the gait sequence, thus with the last part
of my work I developed an online multi-contact planner and integrated it into the MPC
framework. Using a machine learning approach, the planner computes the best feasible option,
even in complex environments, in a few milliseconds, by ranking online a set of discrete options
for footholds, i.e., which leg to move and where to step. To train the network, I designed
a novel function, evaluated offline, which considers the value of the cost of the NMPC and
robustness/stability metrics for each option.
These methods have been validated with simulations and experiments over the three years. I
tested the NMPC on the Hydraulically actuated Quadruped robot (HyQ) of the IIT’s Dynamic
Legged Systems lab, performing omni-directional motions on flat terrain and stepping on
a pallet (both static and relocated during the motion) with a crawl gait. The trajectory
replanning is performed at high-frequency, and visual information of the terrain is included to
traverse uneven terrain. A Unitree Aliengo quadruped robot is used to execute experiments
with the trot gait. The optimization-based reference generator allows the robot to reach a
fixed goal and recover from external pushes without modifying the structure of the NMPC.
Finally, simulations with the Solo robot are performed to validate the neural network-based
contact planning. The robot successfully traverses complex scenarios, e.g., stepping stones,
with both walk and trot gaits, choosing the footholds online.
The achieved results improved the robustness and the performance of the quadruped locomotion.
High-frequency replanning, dealing with a fixed goal, recovering after a push, and the automatic
selection of footholds could help the robots to accomplish important tasks for the humans,
for example, providing support in a disaster response scenario or inspecting an unknown
environment.
In the future, the contact planning will be transferred to the real hardware. Possible developments foresee the optimization of the gait timings, i.e., stance and swing duration, and a
framework which allows the automatic transition between gaits
Locomotion system for ground mobile robots in uneven and unstructured environments
One of the technology domains with the greatest growth rates nowadays is service robots. The extensive use of ground mobile robots in environments that are unstructured or structured for humans is a promising challenge for the coming years, even though Automated Guided Vehicles (AGV) moving on flat and compact grounds are already commercially available and widely utilized to move components and products inside indoor industrial buildings. Agriculture, planetary exploration, military operations, demining, intervention in case of terrorist attacks, surveillance, and reconnaissance in hazardous conditions are important application domains.
Due to the fact that it integrates the disciplines of locomotion, vision, cognition, and navigation, the design of a ground mobile robot is extremely interdisciplinary. In terms of mechanics, ground mobile robots, with the exception of those designed for particular surroundings and surfaces (such as slithering or sticky robots), can move on wheels (W), legs (L), tracks (T), or hybrids of these concepts (LW, LT, WT, LWT). In terms of maximum speed, obstacle crossing ability, step/stair climbing ability, slope climbing ability, walking capability on soft terrain, walking capability on uneven terrain, energy efficiency, mechanical complexity, control complexity, and technology readiness, a systematic comparison of these locomotion systems is provided in [1].
Based on the above-mentioned classification, in this thesis, we first introduce a small-scale hybrid locomotion robot for surveillance and inspection, WheTLHLoc, with two tracks, two revolving legs, two active wheels, and two passive omni wheels. The robot can move in several different ways, including using wheels on the flat, compact ground,[1] tracks on soft, yielding terrain, and a combination of tracks, legs, and wheels to navigate obstacles. In particular, static stability and non-slipping characteristics are considered while analyzing the process of climbing steps and stairs. The experimental test on the first prototype has proven the planned climbing maneuver’s efficacy and the WheTLHLoc robot's operational flexibility. Later we present another development of WheTLHLoc and introduce WheTLHLoc 2.0 with newly designed legs, enabling the robot to deal with bigger obstacles.
Subsequently, a single-track bio-inspired ground mobile robot's conceptual and embodiment designs are presented. This robot is called SnakeTrack. It is designed for surveillance and inspection activities in unstructured environments with constrained areas. The vertebral column has two end modules and a variable number of vertebrae linked by compliant joints, and the surrounding track is its essential component. Four motors drive the robot: two control the track motion and two regulate the lateral flexion of the vertebral column for steering. The compliant joints enable limited passive torsion and retroflection of the vertebral column, which the robot can use to adapt to uneven terrain and increase traction. Eventually, the new version of SnakeTrack, called 'Porcospino', is introduced with the aim of allowing the robot to move in a wider variety of terrains.
The novelty of this thesis lies in the development and presentation of three novel designs of small-scale mobile robots for surveillance and inspection in unstructured environments, and they employ hybrid locomotion systems that allow them to traverse a variety of terrains, including soft, yielding terrain and high obstacles.
This thesis contributes to the field of mobile robotics by introducing new design concepts for hybrid locomotion systems that enable robots to navigate challenging environments. The robots presented in this thesis employ modular designs that allow their lengths to be adapted to suit specific tasks, and they are capable of restoring their correct position after falling over, making them highly adaptable and versatile.
Furthermore, this thesis presents a detailed analysis of the robots' capabilities, including their step-climbing and motion planning abilities. In this thesis we also discuss possible refinements for the robots' designs to improve their performance and reliability.
Overall, this thesis's contributions lie in the design and development of innovative mobile robots that address the challenges of surveillance and inspection in unstructured environments, and the analysis and evaluation of these robots' capabilities. The research presented in this thesis provides a foundation for further work in this field, and it may be of interest to researchers and practitioners in the areas of robotics, automation, and inspection.
As a general note, the first robot, WheTLHLoc, is a hybrid locomotion robot capable of combining tracked locomotion on soft terrains, wheeled locomotion on flat and compact grounds, and high obstacle crossing capability. The second robot, SnakeTrack, is a small-size mono-track robot with a modular structure composed of a vertebral column and a single peripherical track revolving around it. The third robot, Porcospino, is an evolution of SnakeTrack and includes flexible spines on the track modules for improved traction on uneven but firm terrains, and refinements of the shape of the track guidance system. This thesis provides detailed descriptions of the design and prototyping of these robots and presents analytical and experimental results to verify their capabilities
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