Frequency-Aware Model Predictive Control

Transferring solutions found by trajectory optimization to robotic hardware remains a challenging task. When the optimization fully exploits the provided model to perform dynamic tasks, the presence of unmodeled dynamics renders the motion infeasible on the real system. Model errors can be a result of model simplifications, but also naturally arise when deploying the robot in unstructured and nondeterministic environments. Predominantly, compliant contacts and actuator dynamics lead to bandwidth limitations. While classical control methods provide tools to synthesize controllers that are robust to a class of model errors, such a notion is missing in modern trajectory optimization, which is solved in the time domain. We propose frequency-shaped cost functions to achieve robust solutions in the context of optimal control for legged robots. Through simulation and hardware experiments we show that motion plans can be made compatible with bandwidth limits set by actuators and contact dynamics. The smoothness of the model predictive solutions can be continuously tuned without compromising the feasibility of the problem. Experiments with the quadrupedal robot ANYmal, which is driven by highly-compliant series elastic actuators, showed significantly improved tracking performance of the planned motion, torque, and force trajectories and enabled the machine to walk robustly on terrain with unmodeled compliance

Cognitively Inspired Computational Memory Model with Applications in Robotics

У дисертацији је представљен нови рачунарски модел дуготрајне меморије, намењен за примене у конверзаци- оним роботским агентима. Предложени модел је симболи- чки, са методолошког аспекта, и инспирисан је изабраним когнитивним механизмима људског меморијског система, који укључују интеграцију менталних репрезентација, семантичку категоризацију, асоцијативно учење и контек- стно зависно селектовање информација. У основи модела се налази симболички приступ за аутоматско моделовање домена интеракције између човека и робота. Релевантни функциoнaлни aспeкт предложеног модела oднoси се нa прoблeме адекватног aктивирaњa делова дуготрајне мeмoриje, у складу са спољашњим стимулансима, истори- јом интеракције и тренутним контекстом интеракције. Ниво апстракције у спецификацији модела је довољан да омогући примену модела у широком спектру просторних, униформних домена који су карактеристични за интеракцију између човека и робота, а ниво детаља у спецификацији је довољан за рачунарску имплементацију модела.U disertaciji je predstavljen novi računarski model dugotrajne memorije, namenjen za primene u konverzaci- onim robotskim agentima. Predloženi model je simboli- čki, sa metodološkog aspekta, i inspirisan je izabranim kognitivnim mehanizmima ljudskog memorijskog sistema, koji uključuju integraciju mentalnih reprezentacija, semantičku kategorizaciju, asocijativno učenje i kontek- stno zavisno selektovanje informacija. U osnovi modela se nalazi simbolički pristup za automatsko modelovanje domena interakcije između čoveka i robota. Relevantni funkcionalni aspekt predloženog modela odnosi se na probleme adekvatnog aktiviranja delova dugotrajne memorije, u skladu sa spoljašnjim stimulansima, istori- jom interakcije i trenutnim kontekstom interakcije. Nivo apstrakcije u specifikaciji modela je dovoljan da omogući primenu modela u širokom spektru prostornih, uniformnih domena koji su karakteristični za interakciju između čoveka i robota, a nivo detalja u specifikaciji je dovoljan za računarsku implementaciju modela.This dissertation proposes a novel computational model of long-term memory intended for applications in conversational robotic agents. The proposed model is symbolic, from the methodological point of view, and cognitively-inspired by selected cognitive mechanisms of the human memory system, including integration of mental representations, semantic categorization, associative learning, and context-dependent information selection. In the core of the model there is a symbolic approach to automatic modeling of domains of human-robot interaction. The relevant functional aspect of the proposed model concerns the problems of context-dependent retrieval from long-term memory, in accordance with external stimuli, the interaction history, and the current context of interaction. The level of abstraction in the model is sufficient to enable generalization of the model over a range of spatial, uniform domains that are characterical for human-robot interaction, while the level of detail contained in the specification of the model is sufficient for a computational implementation

Legged locomotion over irregular terrains: State of the art of human and robot performance

Legged robotic technologies have moved out of the lab to operate in real environments, characterized by a wide variety of unpredictable irregularities and disturbances, all this in close proximity with humans. Demonstrating the ability of current robots to move robustly and reliably in these conditions is becoming essential to prove their safe operation. Here, we report an in-depth literature review aimed at verifying the existence of common or agreed protocols and metrics to test the performance of legged system in realistic environments. We primarily focused on three types of robotic technologies, i.e., hexapods, quadrupeds and bipeds. We also included a comprehensive overview on human locomotion studies, being it often considered the gold standard for performance, and one of the most important sources of bioinspiration for legged machines. We discovered that very few papers have rigorously studied robotic locomotion under irregular terrain conditions. On the contrary, numerous studies have addressed this problem on human gait, being nonetheless of highly heterogeneous nature in terms of experimental design. This lack of agreed methodology makes it challenging for the community to properly assess, compare and predict the performance of existing legged systems in real environments. On the one hand, this work provides a library of methods, metrics and experimental protocols, with a critical analysis on the limitations of the current approaches and future promising directions. On the other hand, it demonstrates the existence of an important lack of benchmarks in the literature, and the possibility of bridging different disciplines, e.g., the human and robotic, towards the definition of standardized procedure that will boost not only the scientific development of better bioinspired solutions, but also their market uptake

Synthesis and realization of biped walk using primitives

U tezi je prikazan novi metod za sintezu i realizaciju dvonožnog veštačkog hoda koji se zasniva na upotrebi jednostavnih pokreta čijim je kombinovanjem moguće realizovati kompleksne pokrete kao što je hod, a čiji se parametri mogu menjati tokom kretanja. Time je omogućeno da se na osnovu informacija o nameravanom kretanju i stanja okoline izvrši sinteza kretanja izborom i kombinacijom jednostavnih bazičnih pokreta koje se nazivaju primitivi. Takođe je omogućeno da se, tokom izvršavanja hoda bez njegovog prekida, menjaju parametri kretanja kao što su brzina hoda, dužina koraka, pravac kretanja i visina podizanja noge tokom prenosne faze. Potvrda je data kroz eksperimentalne rezultate koji su sprovedeni simulacijom na dinamičkom modelu humanoidnog robota.This dissertation presents new method for the synthesis and realization of biped artificial walk based on the use of simple movements that can be combined in order to achieve complex movements such as walk, whereas it is possible to change the motion parameters at any time. It means that, based on the information about intended movement and current state of the environment, it is possible to synthesize motion by selecting and tying simple movements, i.e. motion primitives. It also enables the robot to change walking parameters online such as walking speed, direction of walk, foot length during swing phase and step length. Proof of this method is given by experimental results obtained during the simulation on a dynamic model of humanoid robot

Control Implementation of Dynamic Locomotion on Compliant, Underactuated, Force-Controlled Legged Robots with Non-Anthropomorphic Design

The control of locomotion on legged robots traditionally involves a robot that takes a standard legged form, such as the anthropomorphic humanoid, the dog-like quadruped, or the bird-like biped. Additionally, these systems will often be actuated with position-controlled servos or series-elastic actuators that are connected through rigid links. This work investigates the control implementation of dynamic, force-controlled locomotion on a family of legged systems that significantly deviate from these classic paradigms by incorporating modern, state-of-the-art proprioceptive actuators on uniquely configured compliant legs that do not closely resemble those found in nature. The results of this work can be used to better inform how to implement controllers on legged systems without stiff, position-controlled actuators, and also provide insight on how intelligently designed mechanical features can potentially simplify the control of complex, nonlinear dynamical systems like legged robots. To this end, this work presents the approach to control for a family of non-anthropomorphic bipedal robotic systems which are developed both in simulation and with physical hardware. The first is the Non-Anthropomorphic Biped, Version 1 (NABi-1) that features position-controlled joints along with a compliant foot element on a minimally actuated leg, and is controlled using simple open-loop trajectories based on the Zero Moment Point. The second system is the second version of the non-anthropomorphic biped (NABi-2) which utilizes the proprioceptive Back-drivable Electromagnetic Actuator for Robotics (BEAR) modules for actuation and fully realizes feedback-based force controlled locomotion. These systems are used to highlight both the strengths and weaknesses of utilizing proprioceptive actuation in systems, and suggest the tradeoffs that are made when using force control for dynamic locomotion. These systems also present case studies for different approaches to system design when it comes to bipedal legged robots

A Stability-Estimator to Unify Humanoid Locomotion: Walking, Stair-Climbing and Ladder-Climbing

The field of Humanoid robotics research has often struggled to find a unique niche that is not better served by other forms of robot. Unlike more traditional industrials robots with a specific purpose, a humanoid robot is not necessarily optimized for any particular task, due to the complexity and balance issues of being bipedal. However, the versatility of a humanoid robot may be ideal for applications such as search and rescue. Disaster sites with chemical, biological, or radiation contamination mean that human rescue workers may face untenable risk. Using a humanoid robot in these dangerous circumstances could make emergency response faster and save human lives. Despite the many successes of existing mobile robots in search and rescue, stair and ladder climbing remains a challenging task due to their form. To execute ladder climbing motions effectively, a humanoid robot requires a reliable estimate of stability. Traditional methods such as Zero Moment Point are not applicable to vertical climbing, and do not account for force limits imposed on end-effectors. This dissertation implements a simple contact wrench space method using a linear combination of contact wrenches. Experiments in simulation showed ZMP equivalence on flat ground. Furthermore, the estimator was able to predict stability with four point contact on a vertical ladder. Finally, an extension of the presented method is proposed based on these findings to address the limitations of the linear combination.Ph.D., Mechanical Engineering and Mechanics -- Drexel University, 201

Reactive Gait Composition with Stability: Dynamic Walking amidst Static and Moving Obstacles

This paper presents a modular approach to motion planning with provable stability guarantees for robots that move through changing environments via periodic locomotion behaviors. We focus on dynamic walkers as a paradigm for such systems, although the tools developed in this paper can be used to support general compositional approaches to robot motion planning with Dynamic Movement Primitives (DMPs). Our approach ensures a priori that the suggested plan can be stably executed. This is achieved by formulating the planning process as a Switching System with Multiple Equilibria (SSME) and proving that the system's evolution remains within explicitly characterized trapping regions in the state space under suitable constraints on the frequency of switching among the DMPs. These conditions effectively encapsulate the low-level stability limitations in a form that can be easily communicated to the planner to guarantee that the suggested plan is compatible with the robot's dynamics. Furthermore, we show how the available primitives can be safely composed online in a receding horizon manner to enable the robot to react to moving obstacles. The proposed framework is applied on 3D bipedal walking models under common modeling assumptions, and offers a modular approach towards stably integrating readily available low-level locomotion control and high-level planning methods.Comment: 18 pages, 10 figure