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This paper presents a new adaptive sliding mode control (ASMC) scheme using time-delay estimation (TDE) technique and then applies it to robot manipulators. The proposed ASMC employs a new adaptive law to achieve good tracking performance with small chattering effect. The new adaptive law considers an arbitrarily small vicinity of the sliding manifold, where the derivatives of its adaptive gains are...
This paper introduces a rescue robot to extract a casualty from hazardous environment and suggests a specific whole-body behavior strategy suitable for the rescue mission taking into account the characteristics of the robot configuration. Since the robot has redundant degrees of freedom, a task-priority based CLIK as differential inverse kinematics approach is adopted for real-time implementation...
In this paper, we describe an voice recognition control technology for Mobile robot system which can robustly recognize voice by adults and children in noisy environments. We evaluate the performance of robot control system in a communication robot placed in a real noisy environment. Voice is captured using a wireless microphone. To suppress interference and noise and to attenuate reverberation, we...
First, the basic structure and principle of quadrotor UAV and its practical applications are introduced. Then, some control algorithms are also presented, such as, PID, LQR/LQG, H∞, sliding mode, feedback linearization, back stepping, model predictive, robust, adaptive, nested saturation, fuzzy logic, neural network, reinforcement learning, iterative learning, memory and brain emotional learning-based...
We propose a method for generating interpretable descriptions of inputs that cause faults in high-dimensional software interfaces. Our method models the set of fault-triggering inputs as a Cartesian product and identifies this set by actively querying the system under test. The active sampling scheme is very efficient in the common case that few fields in the interface are relevant to causing the...
If the control authority of a running system is insufficient to reach a target state in a single step, i.e. if deadbeat control is not possible, then a stabilizing controller is faced with the decision on how to plan intermediate steps. In this work, we compare the performance of a simple greedy control policy (that computes deadbeat inputs and simply caps them) with the optimal performance found...
Fractional order calculus is a generalization of the familiar integer order calculus in that, it allows for differentiation/integration with orders of any real number. The use of fractional order calculus in systems and control applications provides the user an extra design variable, the order of differointegration, which can be tuned to improve the desired behavior of the overall system. We propose...
We address the operation of robotic legs with intrinsic elasticity in hopping cycles determined by the mechanical resonant properties of the system. This ensures energy efficiency and high jumping velocity and distance. Recently, we have shown in simulation that a simple, biologically inspired bang-bang controller operating in the local coordinate of the first resonant mode leads to limit cycles which...
In this work in progress paper, we formulate performance robust event-based control strategies with respect to uncertainties in operation processing times. The proposed policies are based on a time-optimal schedule of operation sequences. A logical operation model is used to specify relations between operations. The control policies generate conditions ensuring to maintain the execution order given...
We present an evaluation of standard image features in the context of long-term visual teach-and-repeat mobile robot navigation, where the environment exhibits significant changes in appearance caused by seasonal weather variations and daily illumination changes. We argue that in the given long-term scenario, the viewpoint, scale and rotation invariance of the standard feature extractors is less important...
This paper proposes a novel motion reproduction method based on environmental disturbance (EnvDs) compensation. The preservation of skillful techniques is an important issue. Although the motion-copying system (MCS) was proposed to deal with this problem, a clear strategy still does not exist for adapting to the environmental variances between the motion saving and reproduction phases. Conventional...
Accurate metrical localization is one of the central challenges in mobile robotics. Many existing methods aim at localizing after building a map with the robot. In this paper, we present a novel approach that instead uses geo-tagged panoramas from the Google Street View as a source of global positioning. We model the problem of localization as a non-linear least squares estimation in two phases. The...
Robots based on tensegrity structures have the potential to be robust, efficient and adaptable. While traditionally being difficult to control, recent control strategies for ball-shaped tensegrity robots have successfully enabled punctuated rolling, hill-climbing and obstacle climbing. These gains have been made possible through the use of machine learning and physics simulations that allow controls...
Robotic systems typically have numerous parameters, e.g. the choice of planning algorithm, real-valued parameters of motion and vision modules, and control parameters. We consider the problem of optimizing these parameters for best worst-case performance over a range of environments. To this end we first propose to evaluate system parameters by adversarially optimizing over environment parameters...
We present an algorithm for generating open-loop trajectories that solve the problem of rearrangement planning under uncertainty. We frame this as a selection problem where the goal is to choose the most robust trajectory from a finite set of candidates. We generate each candidate using a kinodynamic state space planner and evaluate it using noisy rollouts. Our key insight is we can formalize the...
Mapping evolving environments requires an update mechanism to efficiently deal with dynamic objects. In this context, we propose a new approach to update maps pertaining to large-scale dynamic environments with semantics. While previous works mainly rely on large amount of observations, the proposed framework is able to build a stable representation with only two observations of the environment. To...
To analyze auditory scenes of robots' surrounding environments, not only speeches but also non-speech sounds are important, which are spatially distributed and have different spectral and temporal characteristics. Thus, this paper investigates Acoustic Event Identification (AEI) which includes problems of localization, detection, and identification of sound sources. To achieve AEI by a robot in a...
This article depicts an algorithm which matches the output of a Lidar with an initial terrain model to estimate the absolute pose of a robot. Initial models do not perfectly fit the reality and the acquired data set can contain an unknown, and potentially large, proportion of outliers. We present an interval based algorithm that copes with such conditions, by matching the Lidar data with the terrain...
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...
With the increasing usage of autonomous underwater vehicles in offshore applications, it has been important to have a controller that can satisfy a convincing performance throughout the mission. Due to non-linear and time varying dynamic, controlling this vehicle has some special difficulties. Modeling errors that may exist and Uncertainties which associated with the environment firstly evokes that...
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