Um sistema de controle reativo para locomoção de robôs quadrúpedes

Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia de Automação e Sistemas, Florianópolis, 2013.A locomoção ágil de robôs com pernas em terrenos irregulares necessita que todas as tarefas - desde a geração/planejamento de trajetórias ao controle do movimento - interajam de maneira harmoniosa. As diferentes tarefas, por exemplo, a geração de trajetórias e as ações de controle, em geral, não podem gerar conflitos com relação ao movimento desejado. Nesta tese, propõe-se uma estrutura de controle reativa para locomoção de robôs quadrúpedes em terrenos irregulares. O objetivo de tal estrutura è fazer frente à problemas relacionados à locomoção em superfícies irregulares, ao erro de rastreamento de trajetória e a imprecisão da estimação de estados. A estrutura compreende a dois módulos principais: um relacionado a geração do movimento, e outro relacionado ao controle do movimento do robô. Para a geração do movimento propõe-se uma abordagem baseada em Geradores de Padrões Centrais, que geram referências no espaço da tarefa e podem ser modulados de acordo com a superfície do terreno. Para o controle do movimento propõe-se uma estratégia de controle baseado em projeção de espaço nulo e uma estratégia de controle para rejeição de distúrbios baseada no conceito de pontos de captura. As principais contribuições teóricas foram validadas em simulação e implementadas em um robô real. Ao final do documento, tais resultados são apresentados para demonstrar a efetividade da estrutura proposta.2014-08-06T17:47:31

Controle de força indireto para manipuladores com transmissões flexíveis empregados em tarefas de esmerilhamento

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-Graduação em Engenharia Elétrica.A flexibilidade ´e um efeito presente em muitos dos rob#os industriais provocando erros de posicionamento, aumento do tempo de estabiliza¸c#ao e at´e instabilidade. Neste trabalho, o problema do controle de for¸ca em rob#os manipuladores com transmiss#oes flex´ýveis (MTF#s) empregados em tarefas de esmerilhamento ´e estudado. Duas estrat´egias de controle de for¸ca indireto para manipuladores r´ýgidos s#ao estendidas para manipuladores com transmiss#oes flex´ýveis: o controle de rigidez e o controle de imped#ancia. Um modelo de for¸cas para a tarefa de esmerilhamento ´e proposto para o estudo da estabilidade e desempenho de ambas as estrat´egias. Buscando a implementa¸c#ao pr´atica destes controladores, dois observadores de estado - um observador de estados baseado na acelera¸c#ao e outro baseado em torques de dist´urbio - s#ao apresentados para estimar as vari´aveis dos elos e das for¸cas de contato com o objetivo de evitar a necessidade da instrumenta¸c#ao completa do manipulador. O desempenho das estrat´egias de controle e dos observadores ´e avaliado frente a tarefa de esmerilhamento pela an´alise dos resultados obtidos em simula¸c#ao. Esta disserta¸c#ao tamb´em apresenta o software de simula¸c#ao desenvolvido para facilitar a obten¸c#ao de resultados, o que engloba todo o conte´udo estudado. Flexibility is an effect present in many industrial robots causing positioning errors, increasing the stabilization time and even instability. In this paper, the force control problem of robot manipulators with flexible transmissions employed in milling tasks is studied. Two strategies of indirect force control for rigid manipulators are extended to manipulators with flexible transmissions: the compliance control and the impedance control. A model of forces for milling tasks is proposed to study the stability and performance of both strategies. Seeking a practical implementation of these controllers, two state observers - an state observer based on acceleration and another based on disturbance torques - are presented to estimate the variables of the links and the forces of contact with goal of avoid the need for full instrumentation of the manipulator. The performance of the control strategies and observers is evaluated against the milling task by analysis of results obtained in simulation. This document also presents the program of simulation developed and used, throughout this research, to facilitate the achievement of results. This software includes all the content studied

Fast and Continuous Foothold Adaptation for Dynamic Locomotion through CNNs

Legged robots can outperform wheeled machines for most navigation tasks across unknown and rough terrains. For such tasks, visual feedback is a fundamental asset to provide robots with terrain-awareness. However, robust dynamic locomotion on difficult terrains with real-time performance guarantees remains a challenge. We present here a real-time, dynamic foothold adaptation strategy based on visual feedback. Our method adjusts the landing position of the feet in a fully reactive manner, using only on-board computers and sensors. The correction is computed and executed continuously along the swing phase trajectory of each leg. To efficiently adapt the landing position, we implement a self-supervised foothold classifier based on a Convolutional Neural Network (CNN). Our method results in an up to 200 times faster computation with respect to the full-blown heuristics. Our goal is to react to visual stimuli from the environment, bridging the gap between blind reactive locomotion and purely vision-based planning strategies. We assess the performance of our method on the dynamic quadruped robot HyQ, executing static and dynamic gaits (at speeds up to 0.5 m/s) in both simulated and real scenarios; the benefit of safe foothold adaptation is clearly demonstrated by the overall robot behavior.Comment: 9 pages, 11 figures. Accepted to RA-L + ICRA 2019, January 201

Stance Control Inspired by Cerebellum Stabilizes Reflex-Based Locomotion on HyQ Robot

Advances in legged robotics are strongly rooted in animal observations. A clear illustration of this claim is the generalization of Central Pattern Generators (CPG), first identified in the cat spinal cord, to generate cyclic motion in robotic locomotion. Despite a global endorsement of this model, physiological and functional experiments in mammals have also indicated the presence of descending signals from the cerebellum, and reflex feedback from the lower limb sensory cells, that closely interact with CPGs. To this day, these interactions are not fully understood. In some studies, it was demonstrated that pure reflex-based locomotion in the absence of oscillatory signals could be achieved in realistic musculoskeletal simulation models or small compliant quadruped robots. At the same time, biological evidence has attested the functional role of the cerebellum for predictive control of balance and stance within mammals. In this paper, we promote both approaches and successfully apply reflex-based dynamic locomotion, coupled with a balance and gravity compensation mechanism, on the state-of-art HyQ robot. We discuss the importance of this stability module to ensure a correct foot lift-off and maintain a reliable gait. The robotic platform is further used to test two different architectural hypotheses inspired by the cerebellum. An analysis of experimental results demonstrates that the most biologically plausible alternative also leads to better results for robust locomotion

SafeSteps: Learning Safer Footstep Planning Policies for Legged Robots via Model-Based Priors

We present a footstep planning policy for quadrupedal locomotion that is able to directly take into consideration a-priori safety information in its decisions. At its core, a learning process analyzes terrain patches, classifying each landing location by its kinematic feasibility, shin collision, and terrain roughness. This information is then encoded into a small vector representation and passed as an additional state to the footstep planning policy, which furthermore proposes only safe footstep location by applying a masked variant of the Proximal Policy Optimization (PPO) algorithm. The performance of the proposed approach is shown by comparative simulations on an electric quadruped robot walking in different rough terrain scenarios. We show that violations of the above safety conditions are greatly reduced both during training and the successive deployment of the policy, resulting in an inherently safer footstep planner. Furthermore, we show how, as a byproduct, fewer reward terms are needed to shape the behavior of the policy, which in return is able to achieve both better final performances and sample efficienc

Kinematically-Decoupled Impedance Control for Fast Object Visual Servoing and Grasping on Quadruped Manipulators

We propose a control pipeline for SAG (Searching, Approaching, and Grasping) of objects, based on a decoupled arm kinematic chain and impedance control, which integrates image-based visual servoing (IBVS). The kinematic decoupling allows for fast end-effector motions and recovery that leads to robust visual servoing. The whole approach and pipeline can be generalized for any mobile platform (wheeled or tracked vehicles), but is most suitable for dynamically moving quadruped manipulators thanks to their reactivity against disturbances. The compliance of the impedance controller makes the robot safer for interactions with humans and the environment. We demonstrate the performance and robustness of the proposed approach with various experiments on our 140 kg HyQReal quadruped robot equipped with a 7-DoF manipulator arm. The experiments consider dynamic locomotion, tracking under external disturbances, and fast motions of the target object.Comment: Accepted as contributed paper at 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2023

STANCE: Locomotion Adaptation over Soft Terrain

Whole-body Control (WBC) has emerged as an important framework in locomotion control for legged robots. However, most of WBC frameworks fail to generalize beyond rigid terrains. Legged locomotion over soft terrain is difficult due to the presence of unmodeled contact dynamics that WBCs do not account for. This introduces uncertainty in locomotion and affects the stability and performance of the system. In this paper, we propose a novel soft terrain adaptation algorithm called STANCE: Soft Terrain Adaptation and Compliance Estimation. STANCE consists of a WBC that exploits the knowledge of the terrain to generate an optimal solution that is contact consistent and an online terrain compliance estimator that provides the WBC with terrain knowledge. We validated STANCE both in simulation and experiment on the Hydraulically actuated Quadruped (HyQ) robot, and we compared it against the state of the art WBC. We demonstrated the capabilities of STANCE with multiple terrains of different compliances, aggressive maneuvers, different forward velocities, and external disturbances. STANCE allowed HyQ to adapt online to terrains with different compliances (rigid and soft) without pre-tuning. HyQ was able to successfully deal with the transition between different terrains and showed the ability to differentiate between compliances under each foot.Comment: 12 pages, 11 figure