3,480 research outputs found
Robust Legged Robot State Estimation Using Factor Graph Optimization
Legged robots, specifically quadrupeds, are becoming increasingly attractive
for industrial applications such as inspection. However, to leave the
laboratory and to become useful to an end user requires reliability in harsh
conditions. From the perspective of state estimation, it is essential to be
able to accurately estimate the robot's state despite challenges such as uneven
or slippery terrain, textureless and reflective scenes, as well as dynamic
camera occlusions. We are motivated to reduce the dependency on foot contact
classifications, which fail when slipping, and to reduce position drift during
dynamic motions such as trotting. To this end, we present a factor graph
optimization method for state estimation which tightly fuses and smooths
inertial navigation, leg odometry and visual odometry. The effectiveness of the
approach is demonstrated using the ANYmal quadruped robot navigating in a
realistic outdoor industrial environment. This experiment included trotting,
walking, crossing obstacles and ascending a staircase. The proposed approach
decreased the relative position error by up to 55% and absolute position error
by 76% compared to kinematic-inertial odometry.Comment: 8 pages, 12 figures. Accepted to RA-L + IROS 2019, July 201
Virtual Structure Based Formation Tracking of Multiple Wheeled Mobile Robots: An Optimization Perspective
Today, with the increasing development of science and technology, many systems need to be optimized to find the optimal solution of the system. this kind of problem is also called optimization problem. Especially in the formation problem of multi-wheeled mobile robots, the optimization algorithm can help us to find the optimal solution of the formation problem. In this paper, the formation problem of multi-wheeled mobile robots is studied from the point of view of optimization. In order to reduce the complexity of the formation problem, we first put the robots with the same requirements into a group. Then, by using the virtual structure method, the formation problem is reduced to a virtual WMR trajectory tracking problem with placeholders, which describes the expected position of each WMR formation. By using placeholders, you can get the desired track for each WMR. In addition, in order to avoid the collision between multiple WMR in the group, we add an attraction to the trajectory tracking method. Because MWMR in the same team have different attractions, collisions can be easily avoided. Through simulation analysis, it is proved that the optimization model is reasonable and correct. In the last part, the limitations of this model and corresponding suggestions are given
Extending The Lossy Spring-Loaded Inverted Pendulum Model with a Slider-Crank Mechanism
Spring Loaded Inverted Pendulum (SLIP) model has a long history in describing
running behavior in animals and humans as well as has been used as a design
basis for robots capable of dynamic locomotion. Anchoring the SLIP for lossy
physical systems resulted in newer models which are extended versions of
original SLIP with viscous damping in the leg. However, such lossy models
require an additional mechanism for pumping energy to the system to control the
locomotion and to reach a limit-cycle. Some studies solved this problem by
adding an actively controllable torque actuation at the hip joint and this
actuation has been successively used in many robotic platforms, such as the
popular RHex robot. However, hip torque actuation produces forces on the COM
dominantly at forward direction with respect to ground, making height control
challenging especially at slow speeds. The situation becomes more severe when
the horizontal speed of the robot reaches zero, i.e. steady hoping without
moving in horizontal direction, and the system reaches to singularity in which
vertical degrees of freedom is completely lost. To this end, we propose an
extension of the lossy SLIP model with a slider-crank mechanism, SLIP- SCM,
that can generate a stable limit-cycle when the body is constrained to vertical
direction. We propose an approximate analytical solution to the nonlinear
system dynamics of SLIP- SCM model to characterize its behavior during the
locomotion. Finally, we perform a fixed-point stability analysis on SLIP-SCM
model using our approximate analytical solution and show that proposed model
exhibits stable behavior in our range of interest.Comment: To appear in The 17th International Conference on Advanced Robotic
Towards an Autonomous Walking Robot for Planetary Surfaces
In this paper, recent progress in the development of
the DLR Crawler - a six-legged, actively compliant walking
robot prototype - is presented. The robot implements
a walking layer with a simple tripod and a more complex
biologically inspired gait. Using a variety of proprioceptive
sensors, different reflexes for reactively crossing obstacles
within the walking height are realised. On top of
the walking layer, a navigation layer provides the ability
to autonomously navigate to a predefined goal point in
unknown rough terrain using a stereo camera. A model
of the environment is created, the terrain traversability is
estimated and an optimal path is planned. The difficulty
of the path can be influenced by behavioral parameters.
Motion commands are sent to the walking layer and the
gait pattern is switched according to the estimated terrain
difficulty. The interaction between walking layer and navigation
layer was tested in different experimental setups
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