Optimal Control Of An Object When It Is Aimed At A Mobile Target Under Uncertainty

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White Paper Technology and Innovation for the Future of

uncertainty about their future direction. Some, such as advanced robotics ($35 billion market) and 3D printing ($5 billion market), have a long industrial history and are on the cusp of mainstream adoption, albeit in certain geographies and industries. Others, such as artificial intelligence and

University of Windsor Scholarship at UWindsor

Dec 11, 2013 tion [27]. Aimed at tackling the problem as-sociated with object manipulation in extremely small sizes, man-machine interfaces have been designed to bridge the macro and nano worlds mostly by means of virtual reality or augmented reality [3, 18]. The massive construction of nanoscale struc-tures, however, requires large numbers of au-


Digital Object Identifier (DOI): see top of this page. Perception latency is the time necessary to perceive the environment and process the captured data to generate control commands. Depending on the task, the processing algorithm, the available computing power, and the sensor (e.g., lidar, camera, event camera, RGB-D camera), the perception

Reconstruction of Complex Environments by Robust Pre-aligned ICP

tationally symmetric object, for purposes of reconstruction and classification of the original object. The idea is simple, acquire the front and back 3-D views of the fragment and align them using the (same) axis of symmetry. Axes are estimated using 3-D Hough transform under the hypothesis that all surface normals intersect in points

Sensor Control for Multi-Object Tracking Using Labeled Multi

solution of multi-target sensor control problem by exploiting a new family of the RFS and its related lter. The Labeled Multi-Bernoulli RFS (which is the special case of -GLMB RFS) is a new family of RFS which conjugate with respect to the multi-object observation likelihood and is closed under Chapman-Kolmogorov equation [15], [16].

Sensor Placement for Grid Coverage under Imprecise Detections

three-dimensional) of points. A target in the sensor field is therefore a logical object, which is represented by a set of sensors that see it. An irregular sensor field is modeled as a collection of grids. The optimization framework is however inherently probabilistic due to the uncertainty associated with sensor detections. The proposed


defined as: conventional hierarchical, flat heterogeneous mobile sensor network structure, hybrid approaches [1]. Figure 1 presents a graphical illustration of such a collaborative system for pipeline surveillance. A sensor fusion architecture, aimed specifically at identifying pipeline leaks

Optimal Event-Driven Multiagent Persistent Monitoring of a

mize an uncertainty metric associated with a finite number of data sources. In a one-dimensional (1-D) mission space, we adopt an optimal control framework and show that the solution can be reduced to a simpler parametric optimiza-tion problem: Determining a sequence of locations where each agent may dwell for a finite amount of time and then


program to find the optimal trajectories. In the environmental monitoring context, the authors in [7] address the problem of adaptive exploration for an autonomous ocean monitoring system. Feedback control laws are then derived to coordinate the robots along the trajectories that optimize a predefined exploration performance metric.

A Robot Who Knows How to Take the Elevator

to compute the optimal structure and motion solution. 2.2 Zehao Yu - Navigation Navigation is the problem of moving a robot from one place to a target place according to some instruction within some environment. It s the basis of many real world mobile robotic application such as house cleaning, patrolling, package

Adaptive and Intelligent Navigation of Autonomous Planetary

tracking control, dynamic target tracking and object recognition, but we do not cover these aspects in this paper due to page limit. Fig. 1 illustrates the general architecture for the autonomous navigation of a rover system. Path planning consists of finding a feasible path from a

Modelling and Simulation Online Collective Action Exploring

Uncertainty An Intelligent Agents Perspective Belief-based Stability in Coalition Formation with Uncertainty An Intelligent Agents Perspective discusses coalition stability. It extends the classic stability concept of the non-transferable util-ity core by proposing new belief-based stability criteria under uncertainty, and illustrates how the

Multi-AUVs Cooperative Target Search Based on Autonomous

Oct 26, 2020 target search. The characteristic of the underwater target search is that the mission areas are large, and the targets are randomly distributed within the mission area, which requires the AUV to search the whole area in the shortest time to determine the location of the target [9]. Most MAS adopt centralized control structure.

Prediction-Based Object Recovery Using Bayesian Iterative

target as well as recovering nodes and cluster headsfrom failures. George K. al. [12] identified Sensor Atia et Scheduling for Energy-Efficient Target Tracking in Sensor Networks to correspond to the problem of tracking an object moving randomly through a dense network of wireless sensors devised approximate strategies for and

Uncertainty-based information extraction in wireless sensor

The uncertainty of control decision was defined as an estimate of probability associated with cases where the control decision is not optimal. According to the proposed approach, input data are delivered from WSN if it is expected that such operation will result in decrease of the decision uncertainty. Selection of

ARREST: A RSSI Based Approach for Mobile Sensing and Tracking

that a LQG controller can provide the optimal control of a robot along a known/pre-calculated path, when the uncertainty in the motion as well as the noise in observations are Gaus-sian. Extending this concept, Van Den Berg et al. [30], [31] and Tornero et al. [32] proposed LQG based robotic path

How to organise, plan and control projects

Plan, monitor and control the work and resources of the project Manage risks and issues as they occur Maintain communications with those impacted by the project and its outcome Report progress and issues to SRO/Project Board/Stakeholders Decide ongoing viability in the light of experience and any changes in requirements


effective management decisions to achieve the expected future target. The energy cluster should create the conditions for basic, integrated development within the objective function aimed at activating its technological, scientific-technical, industrial-commercial and human resources, as well as prejudice, minimization of active and passive

Sensor Placement for Effective Coverage and Surveillance in

aimed at optimizing the number of sensors and determining their placement to support distributed sensor networks. The optimization framework is inherently probabilistic due to the uncertainty associated with sensor detections. The proposed algorithms address coverage optimization under the constraints of imprecise detections and terrain properties.

Lidar design, use, and calibration concepts for correct

framework, aimed directly at optimizing the quality of the output information, for use in mobile robot navigational algorithms, is given. The design concepts for producing correct range estimates in the presence of a large dynamic range ( 120 dB) of surface albedo is addressed. The performance limits, which can be


ground control center (GCC), but it is also used to collect visual information in the form of static and dynamic images to enhance data collection and event detection at the ground level. One relevant example is dispatching the UAV to validate a perimeter breach along the pipeline by target tracking and identification.

Methods Research and Software Development for Parameters

object assignment by targets based on current information but under uncertainty conditions, it is difficult to prove the task of target assignment in the form

Vision-Based Control for Fast 3-D Reconstruction With an

The control community has also considered driving systems to states that minimize some objective in real time. For example, extremum seeking control (ESC) is an approach that seeks to optimize a measurable target function online. Krstic and Wang [23] provided the first stability analysis of an extremum seeking feedback control for single-input