8 research outputs found
Wake-Based Locomotion Gait Design for Aerobat
Flying animals, such as bats, fly through their fluidic environment as they
create air jets and form wake structures downstream of their flight path. Bats,
in particular, dynamically morph their highly flexible and dexterous armwing to
manipulate their fluidic environment which is key to their agility and flight
efficiency. This paper presents the theoretical and numerical analysis of the
wake-structure-based gait design inspired by bat flight for flapping robots
using the notion of reduced-order models and unsteady aerodynamic model
incorporating Wagner function. The objective of this paper is to introduce the
notion of gait design for flapping robots by systematically searching the
design space in the context of optimization. The solution found using our gait
design framework was used to design and test a flapping robot
Aerobat, A Bioinspired Drone to Test High-DOF Actuation and Embodied Aerial Locomotion
This work presents an actuation framework for a bioinspired flapping drone
called Aerobat. This drone, capable of producing dynamically versatile wing
conformations, possesses 14 body joints and is tail-less. Therefore, in our
robot, unlike mainstream flapping wing designs that are open-loop stable and
have no pronounced morphing characteristics, the actuation, and closed-loop
feedback design can pose significant challenges. We propose a framework based
on integrating mechanical intelligence and control. In this design framework,
small adjustments led by several tiny low-power actuators called primers can
yield significant flight control roles owing to the robot's computational
structures. Since they are incredibly lightweight, the system can host the
primers in large numbers. In this work, we aim to show the feasibility of
joint's motion regulation in Aerobat's untethered flights
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
Mechanical Design, Dynamic Modeling, State Estimation, and Feedback Control of a Micro-Ball-Balancing Robot at High Yaw Rates
A ball-balancing robot (BBR) is a robot that balances itself on top of a ball, typically using three omni-directional wheels. This class of robot features a highly coupled 3D nonlinear dynamics that is capable of natural and holonomic motion. This dissertation presents a new mechanical design, a tractable dynamic model that is accurate at high yaw rates, and an effective estimation and control strategy for a micro ball-balancing robot (MBBR). The miniaturization and the low-cost components used in this design add significant control challenges, which manifest in the form of reduced durability and high amounts of noise, friction, and vibration, making the design of effective state estimation and control strategies for it very difficult, especially under high yaw rates. This motivates the design and use of a reduced nonlinear model which captures the important high yaw-rate dynamics well, and the design of an effective model-based observer and controller based on this reduced nonlinear model. The primary contributions of this dissertation in the general area of ball-balancing robotics include: (1) the novel (and, now, patented) midlatitude and orthogonal-omniwheel orientation of the design, (2) a reduced (minimum complexity) nonlinear BBR dynamic model which well captures its high yaw-rate behavior, and (3) the development of an effective model-based estimator (Extended Kalman Filter) and controller which are capable of achieving remarkable performance of this delicate system under high yaw rates.The novel omniwheel placement minimizes coupling and increases the normal force acting on the omniwheels, which helps to reduce the slipping caused by its very light body. Another contribution of this dissertation is: (4) the modeling and real-time implementation of drive/coast motor drivers, which is also used in the MBBR. Drive/coast motor drivers exhibit highly nonlinear behavior, which makes using them in a model-based controller difficult, but they allow for zero torque dynamics which can be quite useful for many wheeled robots. The drive/coast motor model has been implemented in our linear feedback controller, and has achieved remarkably good position tracking even under high yaw-rates. The performance of the observer and controller were verified with a motion capture system
Multi-Modal Mobility Morphobot (M4) with appendage repurposing for locomotion plasticity enhancement
Abstract 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 recruiting multi-functional appendages. For example, birds such as Chukars and Hoatzins can repurpose wings for quadrupedal walking and wing-assisted incline running. These animals showcase impressive dexterity in employing the same appendages in different ways and generating multiple modes of locomotion, resulting in highly plastic locomotion traits which enable them to interact and navigate various environments and expand their habitat range. The robotic biomimicry of animals’ appendage repurposing can yield mobile robots with unparalleled capabilities. Taking inspiration from animals, we have designed a robot capable of negotiating unstructured, multi-substrate environments, including land and air, by employing its components in different ways as wheels, thrusters, and legs. This robot is called the Multi-Modal Mobility Morphobot, or M4 in short. M4 can employ its multi-functional components composed of several actuator types to (1) fly, (2) roll, (3) crawl, (4) crouch, (5) balance, (6) tumble, (7) scout, and (8) loco-manipulate. M4 can traverse steep slopes of up to 45 deg. and rough terrains with large obstacles when in balancing mode. M4 possesses onboard computers and sensors and can autonomously employ its modes to negotiate an unstructured environment. We present the design of M4 and several experiments showcasing its multi-modal capabilities
Efficient Path Planning and Tracking for Multi-Modal Legged-Aerial Locomotion Using Integrated Probabilistic Road Maps (PRM) and Reference Governors (RG)
There have been several successful implementations of bio-inspired legged
robots that can trot, walk, and hop robustly even in the presence of
significant unplanned disturbances. Despite all of these accomplishments,
practical control and high-level decision-making algorithms in multi-modal
legged systems are overlooked. In nature, animals such as birds impressively
showcase multiple modes of mobility including legged and aerial locomotion.
They are capable of performing robust locomotion over large walls, tight
spaces, and can recover from unpredictable situations such as sudden gusts or
slippery surfaces. Inspired by these animals' versatility and ability to
combine legged and aerial mobility to negotiate their environment, our main
goal is to design and control legged robots that integrate two completely
different forms of locomotion, ground and aerial mobility, in a single
platform. Our robot, the Husky Carbon, is being developed to integrate aerial
and legged locomotion and to transform between legged and aerial mobility. This
work utilizes a Reference Governor (RG) based on low-level control of Husky's
dynamical model to maintain the efficiency of legged locomotion, uses
Probabilistic Road Maps (PRM) and 3D A* algorithms to generate an optimal path
based on the energetic cost of transport for legged and aerial mobilit
Bang-Bang Control Of A Tail-less Morphing Wing Flight
Bats' dynamic morphing wings are known to be extremely high-dimensional, and
they employ the combination of inertial dynamics and aerodynamics manipulations
to showcase extremely agile maneuvers. Bats heavily rely on their highly
flexible wings and are capable of dynamically morphing their wings to adjust
aerodynamic and inertial forces applied to their wing and perform sharp banking
turns. There are technical hardware and control challenges in copying the
morphing wing flight capabilities of flying animals. This work is majorly
focused on the modeling and control aspects of stable, tail-less, morphing wing
flight. A classical control approach using bang-bang control is proposed to
stabilize a bio-inspired morphing wing robot called Aerobat. Robot-environment
interactions based on horseshoe vortex shedding and Wagner functions is derived
to realistically evaluate the feasibility of the bang-bang control, which is
then implemented on the robot in experiments to demonstrate first-time
closed-loop stable flights of Aerobat