1,035 research outputs found
The Penn Jerboa: A Platform for Exploring Parallel Composition of Templates
We have built a 12DOF, passive-compliant legged, tailed biped actuated by
four brushless DC motors. We anticipate that this machine will achieve varied
modes of quasistatic and dynamic balance, enabling a broad range of locomotion
tasks including sitting, standing, walking, hopping, running, turning, leaping,
and more. Achieving this diversity of behavior with a single under-actuated
body, requires a correspondingly diverse array of controllers, motivating our
interest in compositional techniques that promote mixing and reuse of a
relatively few base constituents to achieve a combinatorially growing array of
available choices. Here we report on the development of one important example
of such a behavioral programming method, the construction of a novel monopedal
sagittal plane hopping gait through parallel composition of four decoupled 1DOF
base controllers.
For this example behavior, the legs are locked in phase and the body is
fastened to a boom to restrict motion to the sagittal plane. The platform's
locomotion is powered by the hip motor that adjusts leg touchdown angle in
flight and balance in stance, along with a tail motor that adjusts body shape
in flight and drives energy into the passive leg shank spring during stance.
The motor control signals arise from the application in parallel of four
simple, completely decoupled 1DOF feedback laws that provably stabilize in
isolation four corresponding 1DOF abstract reference plants. Each of these
abstract 1DOF closed loop dynamics represents some simple but crucial specific
component of the locomotion task at hand. We present a partial proof of
correctness for this parallel composition of template reference systems along
with data from the physical platform suggesting these templates are anchored as
evidenced by the correspondence of their characteristic motions with a suitably
transformed image of traces from the physical platform.Comment: Technical Report to Accompany: A. De and D. Koditschek, "Parallel
composition of templates for tail-energized planar hopping," in 2015 IEEE
International Conference on Robotics and Automation (ICRA), May 2015. v2:
Used plain latex article, correct gap radius and specific force/torque
number
Shaping in Practice: Training Wheels to Learn Fast Hopping Directly in Hardware
Learning instead of designing robot controllers can greatly reduce
engineering effort required, while also emphasizing robustness. Despite
considerable progress in simulation, applying learning directly in hardware is
still challenging, in part due to the necessity to explore potentially unstable
parameters. We explore the concept of shaping the reward landscape with
training wheels: temporary modifications of the physical hardware that
facilitate learning. We demonstrate the concept with a robot leg mounted on a
boom learning to hop fast. This proof of concept embodies typical challenges
such as instability and contact, while being simple enough to empirically map
out and visualize the reward landscape. Based on our results we propose three
criteria for designing effective training wheels for learning in robotics. A
video synopsis can be found at https://youtu.be/6iH5E3LrYh8.Comment: Accepted to the IEEE International Conference on Robotics and
Automation (ICRA) 2018, 6 pages, 6 figure
Effectiveness of Central Pattern Generator Model on Developed One Legged Hopping Robot
The paper presents the validity of using Central
Pattern Generator (CPG) model to develop one leg hopping robot
which hops higher and rhythmically. Infrared Ranging (IR)
sensor is mounted on a platform to measure the distance of
hopping performance. The distances of IR sensor from the
platform to the floor in both static and vertical jumping motion
are measured. MATLAB & Simulink model including CPG
model is designed to evaluate the performance of IR sensor by
converting the measurement data from IR sensor from voltage to
distance by using function blocks. The result shows that the one
leg hopping robot with CPG model is able to achieve maximum
hopping height at 4cm
Review of Quadruped Robots for Dynamic Locomotion
This review introduces quadruped robots: MITCheetah, HyQ, ANYmal, BigDog, and
their mechanical structure, actuation, and control
The implications of embodiment for behavior and cognition: animal and robotic case studies
In this paper, we will argue that if we want to understand the function of
the brain (or the control in the case of robots), we must understand how the
brain is embedded into the physical system, and how the organism interacts with
the real world. While embodiment has often been used in its trivial meaning,
i.e. 'intelligence requires a body', the concept has deeper and more important
implications, concerned with the relation between physical and information
(neural, control) processes. A number of case studies are presented to
illustrate the concept. These involve animals and robots and are concentrated
around locomotion, grasping, and visual perception. A theoretical scheme that
can be used to embed the diverse case studies will be presented. Finally, we
will establish a link between the low-level sensory-motor processes and
cognition. We will present an embodied view on categorization, and propose the
concepts of 'body schema' and 'forward models' as a natural extension of the
embodied approach toward first representations.Comment: Book chapter in W. Tschacher & C. Bergomi, ed., 'The Implications of
Embodiment: Cognition and Communication', Exeter: Imprint Academic, pp. 31-5
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