7,345 research outputs found
Keep Rollin' - Whole-Body Motion Control and Planning for Wheeled Quadrupedal Robots
We show dynamic locomotion strategies for wheeled quadrupedal robots, which
combine the advantages of both walking and driving. The developed optimization
framework tightly integrates the additional degrees of freedom introduced by
the wheels. Our approach relies on a zero-moment point based motion
optimization which continuously updates reference trajectories. The reference
motions are tracked by a hierarchical whole-body controller which computes
optimal generalized accelerations and contact forces by solving a sequence of
prioritized tasks including the nonholonomic rolling constraints. Our approach
has been tested on ANYmal, a quadrupedal robot that is fully torque-controlled
including the non-steerable wheels attached to its legs. We conducted
experiments on flat and inclined terrains as well as over steps, whereby we
show that integrating the wheels into the motion control and planning framework
results in intuitive motion trajectories, which enable more robust and dynamic
locomotion compared to other wheeled-legged robots. Moreover, with a speed of 4
m/s and a reduction of the cost of transport by 83 % we prove the superiority
of wheeled-legged robots compared to their legged counterparts.Comment: IEEE Robotics and Automation Letter
Learning Image-Conditioned Dynamics Models for Control of Under-actuated Legged Millirobots
Millirobots are a promising robotic platform for many applications due to
their small size and low manufacturing costs. Legged millirobots, in
particular, can provide increased mobility in complex environments and improved
scaling of obstacles. However, controlling these small, highly dynamic, and
underactuated legged systems is difficult. Hand-engineered controllers can
sometimes control these legged millirobots, but they have difficulties with
dynamic maneuvers and complex terrains. We present an approach for controlling
a real-world legged millirobot that is based on learned neural network models.
Using less than 17 minutes of data, our method can learn a predictive model of
the robot's dynamics that can enable effective gaits to be synthesized on the
fly for following user-specified waypoints on a given terrain. Furthermore, by
leveraging expressive, high-capacity neural network models, our approach allows
for these predictions to be directly conditioned on camera images, endowing the
robot with the ability to predict how different terrains might affect its
dynamics. This enables sample-efficient and effective learning for locomotion
of a dynamic legged millirobot on various terrains, including gravel, turf,
carpet, and styrofoam. Experiment videos can be found at
https://sites.google.com/view/imageconddy
Review of Quadruped Robots for Dynamic Locomotion
This review introduces quadruped robots: MITCheetah, HyQ, ANYmal, BigDog, and
their mechanical structure, actuation, and control
Cable-Driven Actuation for Highly Dynamic Robotic Systems
This paper presents design and experimental evaluations of an articulated
robotic limb called Capler-Leg. The key element of Capler-Leg is its
single-stage cable-pulley transmission combined with a high-gap radius motor.
Our cable-pulley system is designed to be as light-weight as possible and to
additionally serve as the primary cooling element, thus significantly
increasing the power density and efficiency of the overall system. The total
weight of active elements on the leg, i.e. the stators and the rotors,
contribute more than 60% of the total leg weight, which is an order of
magnitude higher than most existing robots. The resulting robotic leg has low
inertia, high torque transparency, low manufacturing cost, no backlash, and a
low number of parts. Capler-Leg system itself, serves as an experimental setup
for evaluating the proposed cable- pulley design in terms of robustness and
efficiency. A continuous jump experiment shows a remarkable 96.5 % recuperation
rate, measured at the battery output. This means that almost all the mechanical
energy output used during push-off returned back to the battery during
touch-down
Body Lift and Drag for a Legged Millirobot in Compliant Beam Environment
Much current study of legged locomotion has rightly focused on foot traction
forces, including on granular media. Future legged millirobots will need to go
through terrain, such as brush or other vegetation, where the body contact
forces significantly affect locomotion. In this work, a (previously developed)
low-cost 6-axis force/torque sensing shell is used to measure the interaction
forces between a hexapedal millirobot and a set of compliant beams, which act
as a surrogate for a densely cluttered environment. Experiments with a
VelociRoACH robotic platform are used to measure lift and drag forces on the
tactile shell, where negative lift forces can increase traction, even while
drag forces increase. The drag energy and specific resistance required to pass
through dense terrains can be measured. Furthermore, some contact between the
robot and the compliant beams can lower specific resistance of locomotion. For
small, light-weight legged robots in the beam environment, the body motion
depends on both leg-ground and body-beam forces. A shell-shape which reduces
drag but increases negative lift, such as the half-ellipsoid used, is suggested
to be advantageous for robot locomotion in this type of environment.Comment: First three authors contributed equally. Accepted to ICRA 201
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