Visual Servo Application Using Model Predictive Control (MPC) Method on Pan-tilt Camera Platform

Saragih, Christ Freben Dommaris; Kinasih, Fabiola Maria Teresa Retno; Machbub, Carmadi; Rusmin, Pranoto Hidaya; Rohman, Arief Syaichu

doi:10.1109/ica.2019.8916673

Cited by 9 publications

(6 citation statements)

References 14 publications

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“…Visual servoing is a technique which uses feedback information extracted from a visual sensor to control the motion of a robot [13]. This is exactly what happens in Airlight.…”

Section: Servo Actuationmentioning

confidence: 99%

Airlight (A UAVs based light guidance and search light system)

Paleja¹,

Kumar²,

Choraria³

et al. 2022

J. Phys.: Conf. Ser.

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Airlight, an UAV (Unmanned Aerial Vehicle) based real time focus and searching light system is a proposed solution which ensures guiding people safely on their path during a dark environment is one less thing to worry about. It is designed to identify a person through algorithms of object detection and also through usage of IoT and sensorics to enable power efficient use of spotlight and hence autonomously guiding people on their path during night-time. Airlight proves to be useful in various sectors such as helping farmers to look after their fields during night-time, security purposes, guiding construction workers while lifting heavy objects, military applications etc.

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“…Visual servoing is a technique which uses feedback information extracted from a visual sensor to control the motion of a robot [13]. This is exactly what happens in Airlight.…”

Section: Servo Actuationmentioning

confidence: 99%

Airlight (A UAVs based light guidance and search light system)

Paleja¹,

Kumar²,

Choraria³

et al. 2022

J. Phys.: Conf. Ser.

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“…When the objective is to perform active tracking, but the target dynamics is unknown, Active Disturbance Rejection Controllers (ADRC) [215] can be used: the uncertainties on the target dynamics are estimated and compensated through an extended state observer (ESO), and then treated as system disturbances. As an alternative to ADRCs, Model Predictive Controllers (MPCs) can be used [216]; MPCs generate optimal control signals, have predictive capabilities, embed input saturation constraints in the objective function [42], and allow to solve non-linear control problems. The optimization problem (28) accounts for a one-step look-ahead action; hence, it is referred to as myopic path-planning [175].…”

Section: B Control Space Constraints and Optimizationmentioning

confidence: 99%

Active Sensing for Search and Tracking: A Review

Varotto¹,

Cenedese²,

Cavallaro³

2021

Preprint

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Active Position Estimation (APE) is the task of localizing one or more targets using one or more sensing platforms. APE is a key task for search and rescue missions, wildlife monitoring, source term estimation, and collaborative mobile robotics. Success in APE depends on the level of cooperation of the sensing platforms, their number, their degrees of freedom and the quality of the information gathered. APE control laws enable active sensing by satisfying either pure-exploitative or pure-explorative criteria. The former minimizes the uncertainty on position estimation; whereas the latter drives the platform closer to its task completion. In this paper, we define the main elements of APE to systematically classify and critically discuss the state of the art in this domain. We also propose a reference framework as a formalism to classify APE-related solutions. Overall, this survey explores the principal challenges and envisages the main research directions in the field of autonomous perception systems for localization tasks. It is also beneficial to promote the development of robust active sensing methods for search and tracking applications.

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“…In an additional note, the ratio between q and r parameter will determine the system performances. A detailed explanation about MPC design for this pan-tilt camera platform is available on [24] while the design process is based on [25,26]. Table 1.…”

Section: B Model Predictive Controlmentioning

confidence: 99%

State Machine Implementation for Human Object Tracking using Combination of MobileNet, KCF Tracker, and HOG Features

Kinasih¹,

Saragih²,

Machbub³

et al. 2019

ijeei

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Since the Viola and Jones' method on real-time face detection was proposed in 2001, numerous works for object detection, person recognition, and object tracking have been published by papers and journals. Each method has its strong points and drawbacks. That means that in a system which only employs a standalone method, we could only get either speed or accuracy. In this paper, we proposed a state-machine method to combine face recognition, face detection, and tracker to harness the tracker promptness while maintaining the ability to distinguish the person of interest with the other person and backgrounds, to overcome the limitations of the standalone method. Subsequently, the information gathered from this image processing side will be delivered to the hardware tracker. The image processing side becomes a visual sensor that provides feedback or measurement value i.e. center point coordinate value from the detected face. The 2 DOF hardware tracker camera platform being used implements Model Predictive Control to calculate required control action thus the platform is able to track the target object, keeping it at the center of the frame. MPC method is chosen because it produces an optimal control signal while considering the input signal saturation aspect. The MPC control signals deliver a good control pan and tilt system response with rise time < 1 second and overshoot <15%. It is also noticed that the FSM implemented in this paper is able to meet the goal with a considerable performance for indoor settings.

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Visual Servo Application Using Model Predictive Control (MPC) Method on Pan-tilt Camera Platform

Cited by 9 publications

References 14 publications

Airlight (A UAVs based light guidance and search light system)

Airlight (A UAVs based light guidance and search light system)

Active Sensing for Search and Tracking: A Review

State Machine Implementation for Human Object Tracking using Combination of MobileNet, KCF Tracker, and HOG Features

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