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This paper discusses the learning of robot point-to-point motions via non-linear dynamical systems and Gaussian Mixture Regression (GMR). The novelty of the proposed approach consists in guaranteeing the stability of a learned dynamical system via Contraction theory. A contraction analysis is performed to derive sufficient conditions for the global stability of a dynamical system represented by GMR...
This work proposes an adaptive dynamic controller for an unmanned aerial vehicle (UAV) to track a desired trajectory. Initially, reference velocities are generated by a controller that is based only on the kinematic model of the UAV. Subsequently, new control actions are calculated to compensate for the internal dynamics of the robot. Then the model parameters that characterize the robot dynamics...
This paper addresses the assist-as-needed (AAN) control problem for robotic orthoses. The objective is to design a stable AAN controller with an adjustable assistance level. The controller aims to follow a desired trajectory while allowing an adjustable tracking error with low control effort to provide a freedom zone for the user. By ensuring the stability of the system and providing the freedom zone,...
This paper describes the design and implementation of a repetitive controller (RC) for tracking periodic trajectories in aerial robots, such as unmanned aerial vehicles (UAVs). The RC is ideally suited for situations where the robot is required to execute a defined flight pattern, over and over again in a periodic fashion. Applications include precision agriculture, and search and rescue, where the...
Dynamic Movement Primitives (DMPs) are a generic approach for trajectory modeling in an attractor land-scape based on differential dynamical systems. DMPs guarantee stability and convergence properties of learned trajectories, and scale well to high dimensional data. In this paper, we propose DMP+, a modified formulation of DMPs which, while preserving the desirable properties of the original, 1)...
This paper presents the implementations of Model Predictive Control for the standing balance control of a humanoid to reject external disturbances. The strategies allow the robot to have a compliant behaviour against external forces resulting in a stable and smooth response. The first, ZMP based controller, compensates for the center of mass deviation while the second, attitude controller, regulates...
In this paper, an algorithm called transverse contracting dynamic system primitive (CDSP) to learn the dynamics of periodic motions from demonstrations is presented. Learning motion plans is essential in making robot programming possible by non-expert programmers as well as realizing human-robot collaboration. The complex periodic motion of the human arm is generated by an orbitally stable closed-loop...
In this paper, we propose a distributed hybrid control strategy for multi-agent systems where each agent has a local task specified as a Linear Temporal Logic (LTL) formula and at the same time is subject to relative-distance constraints with its neighboring agents. The local tasks capture the temporal requirements on individual agents' behaviors, while the relative-distance constraints impose requirements...
In this paper, we propose a novel evolutionary algorithm(EA)-based formation control with collision avoidance for nonholonomic mobile robots. In most conventional approaches, multi-robot formation control problem with collision avoidance can be formulated as a constrained nonlinear optimization problem in model predictive control (MPC) framework. The conventional approaches, therefore, suffer from...
Guiding virtual fixtures have been proposed as a method for human-robot co-manipulation. They constrain the motion of the robot to task-relevant trajectories, which enables the human to execute the task more efficiently, accurately and/or ergonomically. When sequences of different tasks must be solved, multiple guiding virtual fixtures are required, and the appropriate guide for the current task must...
Recent studies revealed that hand gesture-based interfaces can complement therapies for individuals with upper motor impairments and reduce the need of traditional rehabilitation sessions through hospital visits. Unfortunately, existing gesture-based interfaces have been developed without considering the physical limitations of users with motor impairments. An analytic approach was presented in our...
In this paper we exploit Iterative Learning Controllers (ILC) schemes in force adaptation tasks. We propose to encode the control signal with Radial Basis Functions (RBF), which enhances the robustness of the ILC scheme and allows to vary the execution speed of the learned motion. For that a novel control scheme is proposed, which updates the feedforward compensation signals based on current iteration...
This paper presents a teleoperation system for two six-degree-of-freedom ARMin arm rehabilitation skeletons. Two control strategies are presented: unilateral teleoperation, which is realized with proportional-derivative controllers, and bilateral teleoperation, which is realized with compliance control and torque feedback. An empirical procedure for identifying the best control gains of the unilateral...
A robust tracking control problem is considered for an unknown Euler-Lagrange system to track a desired time-varying trajectory. Unknown dynamics including friction effects and impact forces from the environment are considered in the paper. It is challenging to model these two types of uncertain forces for Euler-Lagrange Systems such as robot manipulators and motors. A robust controller with adaptive...
The paper presents the concept and stability analysis of a trajectory-tracking feedback control system for truly N-trailer robots equipped with arbitrary number of trailers interconnected by the non-zero hitching offsets. Thanks to application of the cascaded-like control structure the considered solution is modular and highly scalable with respect to a number of trailers. Formal analysis of the closed-loop...
This article addresses the visual servoing of a rigid robotic manipulator under fixed camera configuration. A tool is mounted on the end-effector of a robot which can be controlled by automatic visual feedback. The control goal is to drive the tip of the tool to follow a visually determined three dimensional target trajectory by using a two-camera vision system without assuming any pointwise correspondence...
This paper investigates the problem of practical finite-time trajectory tracking and practical finite-time stabilization of two important classes of dynamical systems by means of C(∞) feedbacks. It is shown that Hamiltonian mechanical systems and systems in strict feedback form can be made globally finite-time stable by smooth parameterized feedbacks. We show that we could bring all the trajectories...
We present a novel optimization-based motion planning algorithm for high degree-of-freedom (DOF) robots. Our approach combines a multi-contact dynamics formulation with optimization-based planning to compute collision-free, smooth and dynamically stable trajectories. Our formulation is general and can handle multiple simultaneous contacts and non-planar surfaces. We highlight the performance of our...
In this paper, taking the advantages of the simplicity of PD control and the high tracking performance of SMC and avoiding the drawbacks of both control methods, a new hybrid PD-SMC tracking control is proposed for trajectory tracking control of a serial robot by applying the hybridization concept. The unique features of the proposed hybrid control law are the model-free nonlinear feedback control...
In this paper, we present a system that enables humanoid robots to imitate complex whole-body motions of humans in real time. In our approach, we use a compact human model and consider the positions of the endeffectors as well as the center of mass as the most important aspects to imitate. Our system actively balances the center of mass over the support polygon to avoid falls of the robot, which would...
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