10 research outputs found
Towards Connecting Control to Perception: High-Performance Whole-Body Collision Avoidance Using Control-Compatible Obstacles
One of the most important aspects of autonomous systems is safety. This
includes ensuring safe human-robot and safe robot-environment interaction when
autonomously performing complex tasks or in collaborative scenarios. Although
several methods have been introduced to tackle this, most are unsuitable for
real-time applications and require carefully hand-crafted obstacle
descriptions. In this work, we propose a method combining high-frequency and
real-time self and environment collision avoidance of a robotic manipulator
with low-frequency, multimodal, and high-resolution environmental perceptions
accumulated in a digital twin system. Our method is based on geometric
primitives, so-called primitive skeletons. These, in turn, are
information-compressed and real-time compatible digital representations of the
robot's body and environment, automatically generated from ultra-realistic
virtual replicas of the real world provided by the digital twin. Our approach
is a key enabler for closing the loop between environment perception and robot
control by providing the millisecond real-time control stage with a current and
accurate world description, empowering it to react to environmental changes. We
evaluate our whole-body collision avoidance on a 9-DOFs robot system through
five experiments, demonstrating the functionality and efficiency of our
framework.Comment: Accepted for publication at 2023 IEEE/RSJ International Conference on
Intelligent Robots and Systems (IROS 2023
Optimally Controlling the Timing of Energy Transfer in Elastic Joints: Experimental Validation of the Bi-Stiffness Actuation Concept
Elastic actuation taps into elastic elements' energy storage for dynamic
motions beyond rigid actuation. While Series Elastic Actuators (SEA) and
Variable Stiffness Actuators (VSA) are highly sophisticated, they do not fully
provide control over energy transfer timing. To overcome this problem on the
basic system level, the Bi-Stiffness Actuation (BSA) concept was recently
proposed. Theoretically, it allows for full link decoupling, while
simultaneously being able to lock the spring in the drive train via a
switch-and-hold mechanism. Thus, the user would be in full control of the
potential energy storage and release timing. In this work, we introduce an
initial proof-of-concept of Bi-Stiffness-Actuation in the form of a 1-DoF
physical prototype, which is implemented using a modular testbed. We present a
hybrid system model, as well as the mechatronic implementation of the actuator.
We corroborate the feasibility of the concept by conducting a series of
hardware experiments using an open-loop control signal obtained by trajectory
optimization. Here, we compare the performance of the prototype with a
comparable SEA implementation. We show that BSA outperforms SEA 1) in terms of
maximum velocity at low final times and 2) in terms of the movement strategy
itself: The clutch mechanism allows the BSA to generate consistent launch
sequences while the SEA has to rely on lengthy and possibly dangerous
oscillatory swing-up motions. Furthermore, we demonstrate that providing full
control authority over the energy transfer timing and link decoupling allows
the user to synchronously release both elastic joint and gravitational energy.
This facilitates the optimal exploitation of elastic and gravitational
potentials in a synergistic manner.Comment: 8 pages, 9 figures. Submitted to IEEE Robotics and Automation Letter
From dissipativity theory to compositional synthesis of symbolic models
International audienceIn this work, we introduce a compositional framework for the construction of finite abstractions (a.k.a. symbolic models) of interconnected discrete-time control systems. The compositional scheme is based on the joint dissipativity-type properties of discrete-time control subsystems and their finite abstractions. In the first part of the paper, we use a notion of so-called storage function as a relation between each subsystem and its finite abstraction to construct compositionally a notion of so-called alternating simulation function as a relation between interconnected finite abstractions and that of control systems. The derived alternating simulation function is used to quantify the error between the output behavior of the overall interconnected concrete system and that of its finite abstraction. In the second part of the paper, we propose a technique to construct finite abstractions together with their corresponding storage functions for a class of discrete-time control systems under some incremental passivity property. We show that if a discrete-time control system is so-called incrementally passivable, then one can construct its finite abstraction by a suitable quantization of the input and state sets together with the corresponding storage function. Finally, the proposed results are illustrated by constructing a finite abstraction of a network of linear discrete-time control systems and its corresponding alternating simulation function in a compositional way without imposing any restriction on the gains or the number of the subsystems
Symbolic Models for a Class of Impulsive Systems
International audienceSymbolic models have been used as the basis of a systematic framework to address control design of several classes of hybrid systems with sophisticated control objectives. However, results available in the literature are not concerned with impulsive systems which are an important modeling framework of many applications. In this paper, we provide an approach for constructing symbolic models for a class of impulsive systems possessing some stability properties. We formally relate impulsive systems and their symbolic models using a notion of so-called alternating simulation function. We show that behaviors of the constructed symbolic models are approximately equivalent to those of the impulsive systems. Finally, we illustrate the effectiveness of our results through a case study