32 research outputs found
Optimisation of Body-ground Contact for Augmenting Whole-Body Loco-manipulation of Quadruped Robots
Legged robots have great potential to perform loco-manipulation tasks, yet it
is challenging to keep the robot balanced while it interacts with the
environment. In this paper we study the use of additional contact points for
maximising the robustness of loco-manipulation motions. Specifically,
body-ground contact is studied for enhancing robustness and manipulation
capabilities of quadrupedal robots. We propose to equip the robot with prongs:
small legs rigidly attached to the body which ensure body-ground contact occurs
in controllable point-contacts. The effect of these prongs on robustness is
quantified by computing the Smallest Unrejectable Force (SUF), a measure of
robustness related to Feasible Wrench Polytopes. We apply the SUF to assess the
robustness of the system, and propose an effective approximation of the SUF
that can be computed at near-real-time speed. We design a hierarchical
quadratic programming based whole-body controller that controls stable
interaction when the prongs are in contact with the ground. This novel concept
of using prongs and the resulting control framework are all implemented on
hardware to validate the effectiveness of the increased robustness and newly
enabled loco-manipulation tasks, such as obstacle clearance and manipulation of
a large object
A Novel Design and Evaluation of a Dactylus-Equipped Quadruped Robot for Mobile Manipulation
Quadruped robots are usually equipped with additional arms for manipulation,
negatively impacting price and weight. On the other hand, the requirements of
legged locomotion mean that the legs of such robots often possess the needed
torque and precision to perform manipulation. In this paper, we present a novel
design for a small-scale quadruped robot equipped with two leg-mounted
manipulators inspired by crustacean chelipeds and knuckle-walker forelimbs. By
making use of the actuators already present in the legs, we can achieve
manipulation using only 3 additional motors per limb. The design enables the
use of small and inexpensive actuators relative to the leg motors, further
reducing cost and weight. The moment of inertia impact on the leg is small
thanks to an integrated cable/pulley system. As we show in a suite of
tele-operation experiments, the robot is capable of performing single- and
dual-limb manipulation, as well as transitioning between manipulation modes.
The proposed design performs similarly to an additional arm while weighing and
costing 5 times less per manipulator and enabling the completion of tasks
requiring 2 manipulators.Comment: 6 pages, 10 figures, updated layout to fit in margins and corrected
typos, accepted to the 2022 IEEE/RSJ International Conference on Intelligent
Robots and Systems (IROS 2022
RoLoMa: robust loco-manipulation for quadruped robots with arms
Deployment of robotic systems in the real world requires a certain level of
robustness in order to deal with uncertainty factors, such as mismatches in the
dynamics model, noise in sensor readings, and communication delays. Some
approaches tackle these issues reactively at the control stage. However,
regardless of the controller, online motion execution can only be as robust as
the system capabilities allow at any given state. This is why it is important
to have good motion plans to begin with, where robustness is considered
proactively. To this end, we propose a metric (derived from first principles)
for representing robustness against external disturbances. We then use this
metric within our trajectory optimization framework for solving complex
loco-manipulation tasks. Through our experiments, we show that trajectories
generated using our approach can resist a greater range of forces originating
from any possible direction. By using our method, we can compute trajectories
that solve tasks as effectively as before, with the added benefit of being able
to counteract stronger disturbances in worst-case scenarios.Comment: 15 pages, submitted to the IEEE Transactions on Robotics (T-RO) as an
evolved paper. For associated videos, see https://shorturl.at/oFJU
Variable autonomy of whole-body control for inspection and intervention in industrial environments using legged robots
The deployment of robots in industrial and civil scenarios is a viable solution to protect operators from danger and hazards. Shared autonomy is paramount to enable remote control of complex systems such as legged robots, allowing the operator to focus on the essential tasks instead of overly detailed execution. To realize this, we propose a comprehensive control framework for inspection and intervention using a legged robot and validate the integration of multiple loco-manipulation algorithms optimised for improving the remote operation. The proposed control offers 3 operation modes: fully automated, semi-autonomous, and the haptic interface receiving onsite physical interaction for assisting teleoperation. Our contribution is the design of a QP-based semi-analytical whole-body control, which is the key to the various task completion subject to internal and external constraints. We demonstrate the versatility of the whole-body control in terms of decoupling tasks, singularity tolerance and constraint satisfaction. We deploy our solution in field trials and evaluate in an emergency setting by an E-stop while the robot is clearing road barriers and traversing difficult terrains
Multicontact Motion Retargeting Using Whole-Body Optimization of Full Kinematics and Sequential Force Equilibrium
This article presents a multicontact motion adaptation framework that enables teleoperation of high degree-of-freedom robots, such as quadrupeds and humanoids, for loco-manipulation tasks in multicontact settings. Our proposed algorithms optimize whole-body configurations and formulate the retargeting of multicontact motions as sequential quadratic programming, which is robust and stable near the edges of feasibility constraints. Our framework allows real-time operation of the robot and reduces cognitive load for the operator because infeasible commands are automatically adapted into physically stable and viable motions on the robot. The results in simulations with full dynamics demonstrated the effectiveness of teleoperating different legged robots interactively and generating rich multicontact movements. We evaluated the computational efficiency of the proposed algorithms, and further validated and analyzed multicontact loco-manipulation tasks on humanoid and quadruped robots by reaching, active pushing, and various traversal on uneven terrains
Robustness to external disturbances for legged robots using dynamic trajectory optimisation
In robotics, robustness is an important and desirable attribute of any system, from
perception to planning and control. Robotic systems need to handle numerous factors
of uncertainty when they are deployed, and the more robust a method is, the fewer
chances there are of something going wrong. In planning and control, being robust
is crucial to deal with uncertain contact timings and positions, mismatches in the
dynamics model of the system, noise in the sensor readings and communication
delays. In this thesis, we focus on the problem of dealing with uncertainty and
external disturbances applied to the robot.
Reactive robustness can be achieved at the control stage using a variety of control
schemes. For example, model predictive control approaches are robust against external
disturbances thanks to the online high-frequency replanning of the motion being
executed. However, taking robustness into account in a proactive way, i.e., during the
planning stage itself, enables the adoption of kinematic configurations that allow the
system as a whole to better deal with uncertainty and disturbances.
To this end, we propose a novel trajectory optimisation framework for robotic
systems, ranging from fixed-base manipulators to legged robots, such as humanoids
or quadrupeds equipped with arms. We tackle the problem from a first-principles
perspective, and define a robustness metric based on the robot’s capabilities, such as
the torques available to the system (considering actuator torque limits) and contact
stability constraints. We compare our results with other existing approaches and,
through simulation and experiments on the real robot, we show that our method is
able to plan trajectories that are more robust against external disturbances
Optimizing Dynamic Trajectories for Robustness to Disturbances Using Polytopic Projections
This paper focuses on robustness to disturbance forces and uncertain
payloads. We present a novel formulation to optimize the robustness of dynamic
trajectories. A straightforward transcription of this formulation into a
nonlinear programming problem is not tractable for state-of-the-art solvers,
but it is possible to overcome this complication by exploiting the structure
induced by the kinematics of the robot. The non-trivial transcription proposed
allows trajectory optimization frameworks to converge to highly robust dynamic
solutions. We demonstrate the results of our approach using a quadruped robot
equipped with a manipulator.Comment: Final accepted version to the IEEE/RSJ International Conference on
Intelligent Robots and Systems (IROS) 2020. Supplementary video:
https://youtu.be/vDesP7IpTh