arXiv subjects

Alireza Ramezani

Publications and source records attributed to Alireza Ramezani.

At least 37 records · Page 2Linked to original sources

arXiv2024

Validation of Tumbling Robot Dynamics with Posture Manipulation for Closed-Loop Heading Angle Control

Navigating rugged terrain and steep slopes is a challenge for mobile robots. Conventional legged and wheeled systems struggle with these environments due to limited traction and stability. Northeastern University's COBRA (Crater Observing Bio-inspired Rolling Articulator), a novel multi-modal snake-like robot, addresses these issues by combining traditional snake gaits for locomotion on flat and inclined surfaces with a tumbling mode for controlled descent on steep slopes. Through dynamic posture manipulation, COBRA can modulate its heading angle and velocity during tumbling. This paper presents a reduced-order cascade model for COBRA's tumbling locomotion and validates it against a high-fidelity rigid-body simulation, presenting simulation results that show that the model captures key system dynamics.

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arXiv2024

Reinforcement Learning-Based Model Matching to Reduce the Sim-Real Gap in COBRA

This paper employs a reinforcement learning-based model identification method aimed at enhancing the accuracy of the dynamics for our snake robot, called COBRA. Leveraging gradient information and iterative optimization, the proposed approach refines the parameters of COBRA's dynamical model such as coefficient of friction and actuator parameters using experimental and simulated data. Experimental validation on the hardware platform demonstrates the efficacy of the proposed approach, highlighting its potential to address sim-to-real gap in robot implementation.

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arXiv2024

Optimization free control and ground force estimation with momentum observer for a multimodal legged aerial robot

Legged-aerial multimodal robots can make the most of both legged and aerial systems. In this paper, we propose a control framework that bypasses heavy onboard computers by using an optimization-free Explicit Reference Governor that incorporates external thruster forces from an attitude controller. Ground reaction forces are maintained within friction cone constraints using costly optimization solvers, but the ERG framework filters applied velocity references that ensure no slippage at the foot end. We also propose a Conjugate momentum observer, that is widely used in Disturbance Observation to estimate ground reaction forces and compare its efficacy against a constrained model in estimating ground reaction forces in a reduced-order simulation of Husky.

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arXiv2024

Conjugate Momentum-Based Estimation of External Forces for Bio-Inspired Morphing Wing Flight

Dynamic morphing wing flights present significant challenges in accurately estimating external forces due to complex interactions between aerodynamics, rapid wing movements, and external disturbances. Traditional force estimation methods often struggle with unpredictable disturbances like wind gusts or unmodeled impacts that can destabilize flight in real-world scenarios. This paper addresses these challenges by implementing a Conjugate Momentum-based Observer, which effectively estimates and manages unknown external forces acting on the Aerobat, a bio-inspired robotic platform with dynamically morphing wings. Through simulations, the observer demonstrates its capability to accurately detect and quantify external forces, even in the presence of Gaussian noise and abrupt impulse inputs. The results validate the robustness of the method, showing improved stability and control of the Aerobat in dynamic environments. This research contributes to advancements in bio-inspired robotics by enhancing force estimation for flapping-wing systems, with potential applications in autonomous aerial navigation and robust flight control.

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arXiv2024

Enabling steep slope walking on Husky using reduced order modeling and quadratic programming

Wing-assisted inclined running (WAIR) observed in some young birds, is an attractive maneuver that can be extended to legged aerial systems. This study proposes a control method using a modified Variable Length Inverted Pendulum (VLIP) by assuming a fixed zero moment point and thruster forces collocated at the center of mass of the pendulum. A QP MPC is used to find the optimal ground reaction forces and thruster forces to track a reference position and velocity trajectory. Simulation results of this VLIP model on a slope of 40 degrees is maintained and shows thruster forces that can be obtained through posture manipulation. The simulation also provides insight to how the combined efforts of the thrusters and the tractive forces from the legs make WAIR possible in thruster-assisted legged systems.

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arXiv2024

Capture Point Control in Thruster-Assisted Bipedal Locomotion

Despite major advancements in control design that are robust to unplanned disturbances, bipedal robots are still susceptible to falling over and struggle to negotiate rough terrains. By utilizing thrusters in our bipedal robot, we can perform additional posture manipulation and expand the modes of locomotion to enhance the robot's stability and ability to negotiate rough and difficult-to-navigate terrains. In this paper, we present our efforts in designing a controller based on capture point control for our thruster-assisted walking model named Harpy and explore its control design possibilities. While capture point control based on centroidal models for bipedal systems has been extensively studied, the incorporation of external forces that can influence the dynamics of linear inverted pendulum models, often used in capture point-based works, has not been explored before. The inclusion of these external forces can lead to interesting interpretations of locomotion, such as virtual buoyancy studied in aquatic-legged locomotion. This paper outlines the dynamical model of our robot, the capture point method we use to assist the upper body stabilization, and the simulation work done to show the controller's feasibility.

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arXiv2024

Thruster-Assisted Incline Walking

In this study, our aim is to evaluate the effectiveness of thruster-assisted steep slope walking for the Husky Carbon, a quadrupedal robot equipped with custom-designed actuators and plural electric ducted fans, through simulation prior to conducting experimental trials. Thruster-assisted steep slope walking draws inspiration from wing-assisted incline running (WAIR) observed in birds, and intriguingly incorporates posture manipulation and thrust vectoring, a locomotion technique not previously explored in the animal kingdom. Our approach involves developing a reduced-order model of the Husky robot, followed by the application of an optimization-based controller utilizing collocation methods and dynamics interpolation to determine control actions. Through simulation testing, we demonstrate the feasibility of hardware implementation of our controller.

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arXiv2024

Modeling and Controls of Fluid-Structure Interactions (FSI) in Dynamic Morphing Flight

The primary aim of this study is to enhance the accuracy of our aerodynamic Fluid-Structure Interaction (FSI) model to support the controlled tracking of 3D flight trajectories by Aerobat, which is a dynamic morphing winged drone. Building upon our previously documented Unsteady Aerodynamic model rooted in horseshoe vortices, we introduce a new iteration of Aerobat, labeled as version beta, which is designed for attachment to a Kinova arm. Through a series of experiments, we gather force-moment data from the robotic arm attachment and utilize it to fine-tune our unsteady model for banking turn maneuvers. Subsequently, we employ the tuned FSI model alongside a collocation control strategy to accomplish 3D banking turns of Aerobat within simulation environments. The primary contribution lies in presenting a methodical approach to calibrate our FSI model to predict complex 3D maneuvers and successfully assessing the model's potential for closed-loop flight control of Aerobat using an optimization-based collocation method.

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arXiv2024

Banking Turn of High-DOF Dynamic Morphing Wing Flight by Shifting Structure Response Using Optimization

The 3D flight control of a flapping wing robot is a very challenging problem. The robot stabilizes and controls its pose through the aerodynamic forces acting on the wing membrane which has complex dynamics and it is difficult to develop a control method to interact with such a complex system. Bats, in particular, are capable of performing highly agile aerial maneuvers such as tight banking and bounding flight solely using their highly flexible wings. In this work, we develop a control method for a bio-inspired bat robot, the Aerobat, using small low-powered actuators to manipulate the flapping gait and the resulting aerodynamic forces. We implemented a controller based on collocation approach to track a desired roll and perform a banking maneuver to be used in a trajectory tracking controller. This controller is implemented in a simulation to show its performance and feasibility.

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arXiv2024

Narrow-Path, Dynamic Walking Using Integrated Posture Manipulation and Thrust Vectoring

This research concentrates on enhancing the navigational capabilities of Northeastern Universitys Husky, a multi-modal quadrupedal robot, that can integrate posture manipulation and thrust vectoring, to traverse through narrow pathways such as walking over pipes and slacklining. The Husky is outfitted with thrusters designed to stabilize its body during dynamic walking over these narrow paths. The project involves modeling the robot using the HROM (Husky Reduced Order Model) and developing an optimal control framework. This framework is based on polynomial approximation of the HROM and a collocation approach to derive optimal thruster commands necessary for achieving dynamic walking on narrow paths. The effectiveness of the modeling and control design approach is validated through simulations conducted using Matlab.

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arXiv2024

Dynamic Posture Manipulation During Tumbling for Closed-Loop Heading Angle Control

Passive tumbling uses natural forces like gravity for efficient travel. But without an active means of control, passive tumblers must rely entirely on external forces. Northeastern University's COBRA is a snake robot that can morph into a ring, which employs passive tumbling to traverse down slopes. However, due to its articulated joints, it is also capable of dynamically altering its posture to manipulate the dynamics of the tumbling locomotion for active steering. This paper presents a modelling and control strategy based on collocation optimization for real-time steering of COBRA's tumbling locomotion. We validate our approach using Matlab simulations.

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arXiv2024

Loco-Manipulation with Nonimpulsive Contact-Implicit Planning in a Slithering Robot

Object manipulation has been extensively studied in the context of fixed base and mobile manipulators. However, the overactuated locomotion modality employed by snake robots allows for a unique blend of object manipulation through locomotion, referred to as loco-manipulation. The following work presents an optimization approach to solving the loco-manipulation problem based on non-impulsive implicit contact path planning for our snake robot COBRA. We present the mathematical framework and show high-fidelity simulation results and experiments to demonstrate the effectiveness of our approach.

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arXiv2024

Non-impulsive Contact-Implicit Motion Planning for Morpho-functional Loco-manipulation

Object manipulation has been extensively studied in the context of fixed base and mobile manipulators. However, the overactuated locomotion modality employed by snake robots allows for a unique blend of object manipulation through locomotion, referred to as loco-manipulation. The following work presents an optimization approach to solving the loco-manipulation problem based on non-impulsive implicit contact path planning for our snake robot COBRA. We present the mathematical framework and show high fidelity simulation results for fixed-shape lateral rolling trajectories that demonstrate the object manipulation.

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arXiv2023

Quadrupedal Locomotion Control On Inclined Surfaces Using Collocation Method

Inspired by Chukars wing-assisted incline running (WAIR), in this work, we employ a high-fidelity model of our Husky Carbon quadrupedal-legged robot to walk over steep slopes of up to 45 degrees. Chukars use the aerodynamic forces generated by their flapping wings to manipulate ground contact forces and traverse steep slopes and even overhangs. By exploiting the thrusters on Husky, we employed a collocation approach to rapidly resolving the joint and thruster actions. Our approach uses a polynomial approximation of the reduced-order dynamics of Husky, called HROM, to quickly and efficiently find optimal control actions that permit high-slope walking without violating friction cone conditions.

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arXiv2023

Hierarchical RL-Guided Large-scale Navigation of a Snake Robot

Classical snake robot control leverages mimicking snake-like gaits tuned for specific environments. However, to operate adaptively in unstructured environments, gait generation must be dynamically scheduled. In this work, we present a four-layer hierarchical control scheme to enable the snake robot to navigate freely in large-scale environments. The proposed model decomposes navigation into global planning, local planning, gait generation, and gait tracking. Using reinforcement learning (RL) and a central pattern generator (CPG), our method learns to navigate in complex mazes within hours and can be directly deployed to arbitrary new environments in a zero-shot fashion. We use the high-fidelity model of Northeastern's slithering robot COBRA to test the effectiveness of the proposed hierarchical control approach.

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arXiv2023

Snake Robot with Tactile Perception Navigates on Large-scale Challenging Terrain

Along with the advancement of robot skin technology, there has been notable progress in the development of snake robots featuring body-surface tactile perception. In this study, we proposed a locomotion control framework for snake robots that integrates tactile perception to augment their adaptability to various terrains. Our approach embraces a hierarchical reinforcement learning (HRL) architecture, wherein the high-level orchestrates global navigation strategies while the low-level uses curriculum learning for local navigation maneuvers. Due to the significant computational demands of collision detection in whole-body tactile sensing, the efficiency of the simulator is severely compromised. Thus a distributed training pattern to mitigate the efficiency reduction was adopted. We evaluated the navigation performance of the snake robot in complex large-scale cave exploration with challenging terrains to exhibit improvements in motion efficiency, evidencing the efficacy of tactile perception in terrain-adaptive locomotion of snake robots.

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arXiv2023

How Strong a Kick Should be to Topple Northeastern's Tumbling Robot?

Rough terrain locomotion has remained one of the most challenging mobility questions. In 2022, NASA's Innovative Advanced Concepts (NIAC) Program invited US academic institutions to participate NASA's Breakthrough, Innovative \& Game-changing (BIG) Idea competition by proposing novel mobility systems that can negotiate extremely rough terrain, lunar bumpy craters. In this competition, Northeastern University won NASA's top Artemis Award award by proposing an articulated robot tumbler called COBRA (Crater Observing Bio-inspired Rolling Articulator). This report briefly explains the underlying principles that made COBRA successful in competing with other concepts ranging from cable-driven to multi-legged designs from six other participating US institutions.

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arXiv2023

Dynamic modeling of wing-assisted inclined running with a morphing multi-modal robot

Robot designs can take many inspirations from nature, where there are many examples of highly resilient and fault-tolerant locomotion strategies to navigate complex terrains by using multi-functional appendages. For example, Chukar and Hoatzin birds can repurpose their wings for quadrupedal walking and wing-assisted incline running (WAIR) to climb steep surfaces. We took inspiration from nature and designed a morphing robot with multi-functional thruster-wheel appendages that allows the robot to change its mode of locomotion by transforming into a rover, quad-rotor, mobile inverted pendulum (MIP), and other modes. In this work, we derive a dynamic model and formulate a nonlinear model predictive controller to perform WAIR to showcase the unique capabilities of our robot. We implemented the model and controller in a numerical simulation and experiments to show their feasibility and the capabilities of our transforming multi-modal robot.

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