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Physical human-robot interaction is one of the hottest topic in robotics and safety issues are its fundamental aspect. The present paper contributes to this aspect in that collision detections can be completed on the servo level in an intuitive way. The principle of the proposed collision detection strategy is based on the relative difference of the feedback commanded torque, which is able to identify...
While there has been recent success with robotic therapy approaches, individual differences in motor impairments motivate the need for customized therapy. Our latest work with healthy participants considered the likelihood of one's error to construct a customized force field training environment, which we termed an error field. We believe error statistics could characterize individual motor impairments...
This paper introduces a cable-driven robot for upper-limb rehabilitation. Kinematic and dynamic of this rehabilitation robot is analyzed. A sliding mode controller combined with a nonlinear disturbance observer is proposed to control this robot in the presence of disturbances. Simulation is carried out to prove the effectiveness of the proposed control scheme, and the results of the proposed controller...
Because of the remarkable non-linearity, large inertia and strong atmospheric disturbances, traditional control methods cannot ensure the trajectory tracking control performance for a parafoil airdrop robot. In this sense, we propose a trajectory tracking control method based on active disturbance rejection control. Then the proposed control method is evaluated by simulation and airdrop experiment...
This paper is focused on motion control of a nonholonomic car-like robot. The main idea of the proposed control method is based on an approximate decoupling of phase-constrained kinematics in order to imitate an omnidirectional robot. In order to facilitate the feedback design, the original kinematics is simplified and represented by a nilpotent homogeneous locally equivalent control system. Next,...
The improvement of movement smoothness over the course of therapy is one of the positive outcomes observed during robotic rehabilitation. Although movements are generally robust to disturbances, certain perturbations might disrupt an individual's ability to produce these smooth movements. In this paper, we explore how a rehabilitation robot's inherent dynamics impact movement smoothness during pointing...
We present a framework from vision based hand movement prediction in a real-world human-robot collaborative scenario for safety guarantee. We first propose a perception submodule that takes in visual data solely and predicts human collaborator's hand movement. Then a robot trajectory adaptive planning submodule is developed that takes the noisy movement prediction signal into consideration for optimization...
This paper introduces an extension to a method for fast and close to optimal trajectory generation for articulated robots in the case where dynamic constraints and real-time capability are considered. We aim at solving reaching motion problems without pre-defined timing requirements, where the robot starts from its current state trying to reach the final desired state. Our approach combines the advantage...
Modulation of stiffness provides a great deal of advantage in the way humans interact with the environment, and is very important in successfully performing activities of daily living. In the context of human-machine interactions, stiffness control could provide a safer interaction, especially when dealing with unpredictable environment. In this paper we propose a user-modulated stiffness and position...
When used as part of a hybrid controller, finite-memory strategies synthesizedfrom linear-time temporal logic (LTL) specifications rely on an accurate dynamics model in order to ensure correctness of trajectories. In the presence of uncertainty about the underlying model, there may exist unexpected trajectories that manifest as unexpected transitions under control of the strategy. While some disturbances...
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...
Controlling a bicycle without human interaction is still a challenge for researchers. Most of the studies on this topic focus on the physical area of bicycle or designing controllers based on automatic control knowledge such as feedback controller, LQR controller. This study focuses on applying a state-of-the-art deep reinforcement learning algorithm called Deep Deterministic Policy Gradient to control...
In this article, an approach for multi-vehicles localization and guiding is described and demonstrated with experiments in real conditions. The general methodology of the presented work is based on a top down approach implemented in each vehicle of the fleet and having a map of the environment to estimate the absolute localization of each vehicle. The principle is to select, at each time, the best...
The paper reports on the energy consumption of smooth trajectories for stop-and-go navigation of aerial robots. We consider a decimeter-scale quadrotor tasked to travel on straight line, constant height trajectories from an initial hover configuration to another hover configuration. We investigate three prominent types of smooth trajectories (minimum acceleration, minimum jerk and minimum snap), and...
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...
In this paper, we try to show the state of the art on the formation control of multiple quadrotors. From the literature, we summarize some most interested issues such as potential applications, representation of multiple quadrotor formation, consensus, formation control, formation configurations, localization, etc. According to these research, we point out the difficulties and the tendency of research...
We present a modified trajectory tracking controller based on a novel re-parameterization of the reference trajectory with respect to an independent variable whose dynamics can be controlled. A hybrid controller is designed so that the dynamics of both the robot and the reference parameter can respond to disturbances. The proposed hybrid controller is more robust to large disturbances, and hence is...
In this paper we present the use of linear programming to systematically create control software for choreographed UAVs. This application requires the control of multiple UAVs where each UAV follows a predefined trajectory while simultaneously maintaining safety properties, such as keeping a safe distance between each other and geofencing. Modeling and incorporating safety requirements into the movement...
While teleoperation provides a possibility for a robot to operate at extreme conditions instead of a human, teleoperating a robot still demands a heavy mental workload from a human operator. Learning from demonstrations can reduce the human operator's burden by learning repetitive teleoperation tasks. However, one of challenging issues is that demonstrations via teleoperation are less consistent compared...
In this paper, we address robust iterative learning control (ILC) problem for nonrepetitive systems subject to iteration-varying desired references generated by high-order internal models (HOIM). A modified high-order ILC algorithm is proposed by incorporating HOIM into the ILC algorithm design. We give one condition to guarantee the bounded system trajectories and tracking errors under the assumption...
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