The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This work presents a model predictive path-following controller, which incorporates adaptive slip estimation for a tracked vehicle. Tracked vehicles are capable of manoeuvring in highly variable and uneven terrain, but difficulties in their control have traditionally limited their use as autonomous platforms. Attempts to compensate for slip in environments typically require that both the forward and...
Performing task-space tracking control on redundant robot manipulators is a difficult problem. When the physical model of the robot is too complex or not available, standard methods fail and machine learning algorithms can have advantages. We propose an adaptive learning algorithm for tracking control of underactuated or non-rigid robots where the physical model of the robot is unavailable. The control...
In this paper, we propose a framework for generating coordinated periodic movements of robotic systems with external inputs. We developed an adaptive pattern generator model that is composed of a two-factor observation model with a style parameter and phase dynamics with a phase variable. The style parameter controls the spatial patterns of the generated trajectories, and the phase variable controls...
Collaborative multi-robot systems are used in a vast array of fields for their innate ability to parallelize domain problems for faster execution. These systems are generally comprised of multiple identical robotic systems in order to simplify manufacturability and programmability, reduce cost, and provide fault tolerance. This work takes advantage of the homogeneity and multiplicity of multi-robot...
This paper proposes a novel hybrid-structured model for the adaptive localization of robots combining a stochastic localization model and a rhythmic action model, for avoiding vacant spaces of landmarks efficiently. In regularly arranged landmark environments, robots may not be able to detect any landmarks for a long time during a straight-like movement. Consequently, locally diverse and smooth movement...
A typical unmanned ground vehicle (UGV) mission can be composed of various tasks and several alternative paths. Small UGVs commonly rely on electric rechargeable batteries for their operations. Since each battery has limited energy storage capacity, it is essential to predict the expected mission energy requirement during the mission execution and update this prediction adaptively via real-time performance...
The paper concerns the control of a lower limb orthosis acting on the knee joint level. Therefore, a model of the shank-orthosis system is given considering the human effort as an external torque acting on the system. A model reference adaptive control law is developed and applied to the orthosis in order to make the system (shank-orthosis) track a desired trajectory predefined by a rehabilitation...
In this paper, a new open-loop model for a Magneto-Rheological (MR) based actuator is presented. The model consists of two parts relating the output torque of the actuator to its internal magnetic field, and the internal magnetic field to the applied current. Each part possesses its own hysteretic behavior. The first part uses an open-loop Bouc-Wen model to relate the output torque to internal magnetic...
This paper presents a novel approach to tracking dynamic objects in 3D range data. Its key contribution lies in the generative object detection algorithm which allows the tracker to robustly extract objects of varying sizes and shapes from the observations. In contrast to tracking methods using discriminative detectors, we are thus able to generalize over a wide range of object classes matching our...
Autonomous decentralized control is a key concept for the realization of highly adaptive behavior. However, universal design of autonomous decentralized control that ensures rich adaptability is still lacking. In this study, we tackle this problem through the development of a two-dimensional sheet-like robot, SheetBot. The SheetBot is a suitable model system for the establishment of universal design...
We describe a model of “trust” in human-robot systems that is inferred from their interactions, and inspired by similar concepts relating to trust among humans. This computable quantity allows a robot to estimate the extent to which its performance is consistent with a human's expectations, with respect to task demands. Our trust model drives an adaptive mechanism that dynamically adjusts the robot's...
Virtual Metrology (VM) is a method to conjecture manufacturing quality of a process tool based on data sensed from the process tool and without physical metrology operations. Historical data is used to produce the initial VM models, and then these models are applied to operate in a process drift/shift environment. The accuracy of VM highly depends on the modeling samples adopted during initial-creating...
We develop a technique to automatically generate a control policy for a robot moving in an environment that includes elements with partially unknown, changing behavior. The robot is required to achieve an optimal surveillance mission, in which a certain request needs to be serviced repeatedly, while the expected time in between consecutive services is minimized. We define a fragment of Linear Temporal...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.