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. 2018 Oct 8:5:108.
doi: 10.3389/frobt.2018.00108. eCollection 2018.

A General Approach to Achieving Stability and Safe Behavior in Distributed Robotic Architectures

Stefan S Groothuis  1 , Gerrit A Folkertsma  1 , Stefano Stramigioli  1   2
Affiliations

A General Approach to Achieving Stability and Safe Behavior in Distributed Robotic Architectures

Stefan S Groothuis et al. Front Robot AI. .

Abstract

This paper proposes a unified energy-based modeling and energy-aware control paradigm for robotic systems. The paradigm is inspired by the layered and distributed control system of organisms, and uses the fundamental notion of energy in a system and the energy exchange between systems during interaction. A universal framework that models actuated and interacting robotic systems is proposed, which is used as the basis for energy-based and energy-limited control. The proposed controllers act on certain energy budgets to accomplish a desired task, and decrease performance if a budget has been depleted. These budgets ensure that a maximum amount of energy can be used, to ensure passivity and stability of the system. Experiments show the validity of the approach.

Keywords: energy budgeting; interaction; passivity-based control; robotics; safety.

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Figures

Figure 1
Figure 1
Impedance controlled robot interacting with an environment or a human.
Figure 2
Figure 2
Representation of a power port with a bond (half arrow) indicating a positive power flow from system Σ1 to system Σ2.
Figure 3
Figure 3
The human motor control system is highly suitable as model for robot modeling and control. The nervous system is responsible for cognition, planning, and controlling actions, while the musculatory system delivers power to generate movement supported by the skeletal system. This corresponds to a high-level and lower-level controller in a robotic system that control actuators to manipulate a mechanism.
Figure 4
Figure 4
Physical representation of an energy budgeted actuation controller.
Figure 5
Figure 5
Physical representation of the proposed distributed energy-aware system. The system is structured similarly as the generic model given in Figure 3.
Figure 6
Figure 6
Two coupled five-bar linkage systems are used as the experimentation setup. The smaller system on the left is termed the master while the larger system on the right is the slave.
Figure 7
Figure 7
Master end effector positions.
Figure 8
Figure 8
Slave end effector positions.
Figure 9
Figure 9
Slave energy levels.
Figure 10
Figure 10
Master end effector position; traditional 100 Hz supervisor.
Figure 11
Figure 11
Slave end effector position; traditional 100 Hz supervisor.
Figure 12
Figure 12
Slave end effector positions; traditional 100 Hz supervisor. Instability occurs at 75 s.
Figure 13
Figure 13
Master end effector position; energy-based 100 Hz supervisor.
Figure 14
Figure 14
Slave end effector position; energy-based 100 Hz supervisor.
Figure 15
Figure 15
Slave energy levels; energy-based 100 Hz supervisor. No instability occurs.
See this image and copyright information in PMC

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