4 research outputs found
A Model-based Hierarchical Controller for Legged Systems subject to External Disturbances
Xin G, Lin H-C, Smith J, Cebe O, Mistry M. A Model-based Hierarchical Controller for Legged Systems subject to External Disturbances. In: IEEE/RSJ Int. Conf. on Robotics and Automation. 2018.Legged robots have many potential applications
in real-world scenarios where the tasks are too dangerous for
humans, and compliance is needed to protect the system against
external disturbances and impacts. In this paper, we propose a
model-based controller for hierarchical tasks of legged systems
subject to external disturbance. The control framework is
based on projected inverse dynamics controller, such that the
control law is decomposed into two orthogonal subspaces,
i.e., the constrained and the unconstrained subspaces. The
unconstrained component controls multiple desired tasks with
impedance responses. The constrained space controller maintains
the contact subject to unknown external disturbances,
without the use of any force/torque sensing at the contact
points. By explicitly modelling the external force, our controller
is robust to external disturbances and errors arising from
incorrect dynamic model information. The main contributions
of this paper include (1) incorporating an impedance controller
to control external disturbances and allow impedance shaping
to adjust the behaviour of the motion under external disturbances,
(2) optimising contact forces within the constrained
subspace that also takes into account the external disturbances
without using force/torque sensors at the contact locations. The
techniques are evaluated on the ANYmal quadruped platform
under a variety of scenarios
Robust Footstep Planning and LQR Control for Dynamic Quadrupedal Locomotion
In this paper, we aim to improve the robustness of dynamic quadrupedal
locomotion through two aspects: 1) fast model predictive foothold planning, and
2) applying LQR to projected inverse dynamic control for robust motion
tracking. In our proposed planning and control framework, foothold plans are
updated at 400 Hz considering the current robot state and an LQR controller
generates optimal feedback gains for motion tracking. The LQR optimal gain
matrix with non-zero off-diagonal elements leverages the coupling of dynamics
to compensate for system underactuation. Meanwhile, the projected inverse
dynamic control complements the LQR to satisfy inequality constraints. In
addition to these contributions, we show robustness of our control framework to
unmodeled adaptive feet. Experiments on the quadruped ANYmal demonstrate the
effectiveness of the proposed method for robust dynamic locomotion given
external disturbances and environmental uncertainties
Online dynamic trajectory optimization and control for a quadruped robot
Legged robot locomotion requires the planning of stable reference trajectories, especially while traversing uneven terrain. The proposed trajectory optimization framework is capable of generating dynamically stable base and footstep trajectories for multiple steps. The locomotion task can be defined with contact locations, base motion or both, making the algorithm suitable for multiple scenarios (e.g., presence of moving obstacles). The planner uses a simplified momentum based task space model for the robot dynamics, allowing computation times that are fast enough for online replanning. This fast planning capability also enables the quadruped to accommodate for drift and environmental changes. The algorithm is tested on simulation and a real robot across multiple scenarios, which includes uneven terrain, stairs and moving obstacles. The results show that the planner is capable of generating stable trajectories in the real robot even when a box of 15 cm height is placed in front of its path at the last moment
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