Pub Date : 2018-08-01DOI: 10.1109/CCTA.2018.8511483
A. Subramaniam, Tushar Jain
In this paper, we present a novel integrated fault-diagnosis and fault-tolerant control approach based on the nonlinear model-predictive control (NMPC) technique for heating, ventilation, and air conditioning systems in commercial buildings, which addresses the economic objectives while maintaining the thermal comfort of users possibly under the event of faults. The fault diagnosis system uses a full order nonlinear observer to detect and estimate multiple stuck faults in VAV dampers. Based on the complete information received about the occurred fault, the NMPC is reconfigured to accommodate the aftereffects of faults. The effectiveness of the proposed control and monitoring approach is demonstrated on a one floor, three-zone building constructed using SIMulation of Building and Devices (SIMBAD) toolbox.
{"title":"Fault Tolerant Economic Model Predictive Control for Energy Efficiency in a Multi-Zone Building","authors":"A. Subramaniam, Tushar Jain","doi":"10.1109/CCTA.2018.8511483","DOIUrl":"https://doi.org/10.1109/CCTA.2018.8511483","url":null,"abstract":"In this paper, we present a novel integrated fault-diagnosis and fault-tolerant control approach based on the nonlinear model-predictive control (NMPC) technique for heating, ventilation, and air conditioning systems in commercial buildings, which addresses the economic objectives while maintaining the thermal comfort of users possibly under the event of faults. The fault diagnosis system uses a full order nonlinear observer to detect and estimate multiple stuck faults in VAV dampers. Based on the complete information received about the occurred fault, the NMPC is reconfigured to accommodate the aftereffects of faults. The effectiveness of the proposed control and monitoring approach is demonstrated on a one floor, three-zone building constructed using SIMulation of Building and Devices (SIMBAD) toolbox.","PeriodicalId":358360,"journal":{"name":"2018 IEEE Conference on Control Technology and Applications (CCTA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131815046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/CCTA.2018.8511399
Qinling Zheng, Zhan Ping, S. Soares, Yu Hu, Zhiqiang Gao
As more and more massive data storage drives are used in super high density, the power used to cool the servers has become an increasingly large component of the total power consumption. Therefore, improving server cooling efficiency has become an essential requirement in data centers. However, because the thermal dynamics of the server system has characteristics such as nonlinearity, significant inter-loop coupling, and continuously fast changing/unknown workload disturbances, these pose huge challenges to control engineers and data center architect engineers. To address the above concerns, this paper presents an active disturbance rejection control (ADRC) based temperature control solution to realize the thermal regulation in a one-unit (1U) server to simultaneously improve fan power consumption efficiency and regulate the server components' temperature to avoid downgraded performance caused by overheating. In this study, an experimental testbed is built and modeled to capture the thermal dynamics of a typical 1U blade server where the thermal characteristics and existing solutions are both systematically evaluated. Performance of the design concept is proved both in simulation and hardware testbed. Experimental results show that, with the proposed control solution, temperature overshoot is greatly eliminated, temperatures are more tightly controlled and the server components' throttling rate are greatly decreased. Furthermore, the proposed method is shown to be able to save up to 22% energy when the temperature set-point is increased.
{"title":"An Active Disturbance Rejection Control Approach to Fan Control in Servers","authors":"Qinling Zheng, Zhan Ping, S. Soares, Yu Hu, Zhiqiang Gao","doi":"10.1109/CCTA.2018.8511399","DOIUrl":"https://doi.org/10.1109/CCTA.2018.8511399","url":null,"abstract":"As more and more massive data storage drives are used in super high density, the power used to cool the servers has become an increasingly large component of the total power consumption. Therefore, improving server cooling efficiency has become an essential requirement in data centers. However, because the thermal dynamics of the server system has characteristics such as nonlinearity, significant inter-loop coupling, and continuously fast changing/unknown workload disturbances, these pose huge challenges to control engineers and data center architect engineers. To address the above concerns, this paper presents an active disturbance rejection control (ADRC) based temperature control solution to realize the thermal regulation in a one-unit (1U) server to simultaneously improve fan power consumption efficiency and regulate the server components' temperature to avoid downgraded performance caused by overheating. In this study, an experimental testbed is built and modeled to capture the thermal dynamics of a typical 1U blade server where the thermal characteristics and existing solutions are both systematically evaluated. Performance of the design concept is proved both in simulation and hardware testbed. Experimental results show that, with the proposed control solution, temperature overshoot is greatly eliminated, temperatures are more tightly controlled and the server components' throttling rate are greatly decreased. Furthermore, the proposed method is shown to be able to save up to 22% energy when the temperature set-point is increased.","PeriodicalId":358360,"journal":{"name":"2018 IEEE Conference on Control Technology and Applications (CCTA)","volume":"176 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131855519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/CCTA.2018.8511466
Jafar Abbaszadeh Chekan, Saeid Bashash, S. Taheri
This paper presents a novel data-driven control strategy for the computationally efficient power management of plug-in hybrid electric vehicles (PHEVs). The proposed method relies on a set of real-time control policies trained through a linear regression process based on a large set of optimal powertrain decisions obtained from dynamic programming. The control policies receive the real-time powertrain system information such as the demanded propulsion force, vehicle speed, battery state-of-charge, etc. to compute the required torque values for the engine and the electric drivetrain system. The proposed controller makes near-optimal decisions when it is evaluated for the same test conditions as trained. When the test and training settings are different, however, the controller decisions deviate from optimality. We show that this deviation can be mitigated by including future drive cycle information such as trip length in the control computations.
{"title":"A Data-Driven Control Strategy for Trip Length-Conscious Power Management of Plug-In Hybrid Electric Vehicles","authors":"Jafar Abbaszadeh Chekan, Saeid Bashash, S. Taheri","doi":"10.1109/CCTA.2018.8511466","DOIUrl":"https://doi.org/10.1109/CCTA.2018.8511466","url":null,"abstract":"This paper presents a novel data-driven control strategy for the computationally efficient power management of plug-in hybrid electric vehicles (PHEVs). The proposed method relies on a set of real-time control policies trained through a linear regression process based on a large set of optimal powertrain decisions obtained from dynamic programming. The control policies receive the real-time powertrain system information such as the demanded propulsion force, vehicle speed, battery state-of-charge, etc. to compute the required torque values for the engine and the electric drivetrain system. The proposed controller makes near-optimal decisions when it is evaluated for the same test conditions as trained. When the test and training settings are different, however, the controller decisions deviate from optimality. We show that this deviation can be mitigated by including future drive cycle information such as trip length in the control computations.","PeriodicalId":358360,"journal":{"name":"2018 IEEE Conference on Control Technology and Applications (CCTA)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134403258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/CCTA.2018.8511387
Minh-Duc Hua, Guillaume Allibert
This paper revisits the problem of estimating the pose (i.e. position and attitude) of a robotic vehicle by combining landmark position measurements provided by a stereo camera with measurements of an Inertial Measurement Unit. The distinguished features with respect to similar works on the topic are two folds: First, the vehicle's linear velocity is not measured neither in the body frame nor in the inertial frame; Second, no prior knowledge on the gravity direction expressed in the inertial frame is required. Instead both the linear velocity and the gravity direction are estimated together with the pose. Another innovative feature of the paper relies on the idea of over-parametrizing the gravity direction vector evolving on the unit 2-sphere $S^{2}$ by an element of SO(3) so that the error system in first order approximations can be written in an “elegant” linear time-varying form. The proposed deterministic observer is accompanied with an observability analysis that points out an explicit observability condition under which local exponential stability is granted. Reported simulation results further indicate that the observer's domain of convergence is large.
{"title":"Riccati Observer Design for Pose, Linear Velocity and Gravity Direction Estimation Using Landmark Position and IMU Measurements","authors":"Minh-Duc Hua, Guillaume Allibert","doi":"10.1109/CCTA.2018.8511387","DOIUrl":"https://doi.org/10.1109/CCTA.2018.8511387","url":null,"abstract":"This paper revisits the problem of estimating the pose (i.e. position and attitude) of a robotic vehicle by combining landmark position measurements provided by a stereo camera with measurements of an Inertial Measurement Unit. The distinguished features with respect to similar works on the topic are two folds: First, the vehicle's linear velocity is not measured neither in the body frame nor in the inertial frame; Second, no prior knowledge on the gravity direction expressed in the inertial frame is required. Instead both the linear velocity and the gravity direction are estimated together with the pose. Another innovative feature of the paper relies on the idea of over-parametrizing the gravity direction vector evolving on the unit 2-sphere $S^{2}$ by an element of SO(3) so that the error system in first order approximations can be written in an “elegant” linear time-varying form. The proposed deterministic observer is accompanied with an observability analysis that points out an explicit observability condition under which local exponential stability is granted. Reported simulation results further indicate that the observer's domain of convergence is large.","PeriodicalId":358360,"journal":{"name":"2018 IEEE Conference on Control Technology and Applications (CCTA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130339090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/CCTA.2018.8511573
Moinak Pyne, B. Yurkovich, S. Yurkovich
For the development, simulation and validation of data-driven battery aging models, a critical aspect is having access to large amounts of reliable aging data. Although normal operation of battery packs can be simulated in the lab to generate aging data, a variety of other non-operational profiles are typically needed, requiring many hours of testing, often at conditions different than normal operational conditions observed when the battery pack is deployed in its intended application. Moreover, application of prolonged and multiple capacity tests can be detrimental to the health of the battery. In view of these concerns, this article continues a line of research into capacity fade estimation approaches that require less data and time for the data generation process; in particular, an approach using rule based machine learning for Li-ion battery packs is proposed. Using data generated in the laboratory, aging behavior is characterized by measurable features and a supervised learning approach in order to estimate capacity fade using real-time operational data toward the goal of eliminating the need for specific capacity tests. The experimental results presented in this article focus on proof of concept and are part of a comprehensive study into general capacity estimation and capacity fade estimation in battery packs.
{"title":"Toward the Use of Operational Cycle Data for Capacity Estimation","authors":"Moinak Pyne, B. Yurkovich, S. Yurkovich","doi":"10.1109/CCTA.2018.8511573","DOIUrl":"https://doi.org/10.1109/CCTA.2018.8511573","url":null,"abstract":"For the development, simulation and validation of data-driven battery aging models, a critical aspect is having access to large amounts of reliable aging data. Although normal operation of battery packs can be simulated in the lab to generate aging data, a variety of other non-operational profiles are typically needed, requiring many hours of testing, often at conditions different than normal operational conditions observed when the battery pack is deployed in its intended application. Moreover, application of prolonged and multiple capacity tests can be detrimental to the health of the battery. In view of these concerns, this article continues a line of research into capacity fade estimation approaches that require less data and time for the data generation process; in particular, an approach using rule based machine learning for Li-ion battery packs is proposed. Using data generated in the laboratory, aging behavior is characterized by measurable features and a supervised learning approach in order to estimate capacity fade using real-time operational data toward the goal of eliminating the need for specific capacity tests. The experimental results presented in this article focus on proof of concept and are part of a comprehensive study into general capacity estimation and capacity fade estimation in battery packs.","PeriodicalId":358360,"journal":{"name":"2018 IEEE Conference on Control Technology and Applications (CCTA)","volume":"225 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115068224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/CCTA.2018.8511621
Gabriele Pozzato, S. Formentin, Giulio Panzani, S. Savaresi
In this work, the Energy Management Strategy (EMS) problem is solved considering an Electric Vehicle (EV) equipped with a Range Extender (REX), a device developed to increase the All Electric Range (AER) provided by the battery, which can be switched ON and OFF depending on the need. First, a control-oriented modeling of the powertrain is introduced focusing attention on REX description in terms of power generation, and thermal dynamics. Secondly, the EMS problem is formalized as a mixed-integer convex program. Thus, the optimal energy management policy is obtained by minimizing an objective function taking into account electricity and battery aging costs, REX fuel consumption and start-up costs. The introduction of REX thermal dynamics allows for temperature varying start-up costs and simplified REX aging modeling. To show the effectiveness of the EMS, an electric bus case study is dealt with and a sensitivity analysis is performed over some critical optimization parameters to understand when purchasing a REX is interesting and economically effective.
{"title":"Least Costly Energy Management for Extended Range Electric Vehicles with Start-Up Characterization","authors":"Gabriele Pozzato, S. Formentin, Giulio Panzani, S. Savaresi","doi":"10.1109/CCTA.2018.8511621","DOIUrl":"https://doi.org/10.1109/CCTA.2018.8511621","url":null,"abstract":"In this work, the Energy Management Strategy (EMS) problem is solved considering an Electric Vehicle (EV) equipped with a Range Extender (REX), a device developed to increase the All Electric Range (AER) provided by the battery, which can be switched ON and OFF depending on the need. First, a control-oriented modeling of the powertrain is introduced focusing attention on REX description in terms of power generation, and thermal dynamics. Secondly, the EMS problem is formalized as a mixed-integer convex program. Thus, the optimal energy management policy is obtained by minimizing an objective function taking into account electricity and battery aging costs, REX fuel consumption and start-up costs. The introduction of REX thermal dynamics allows for temperature varying start-up costs and simplified REX aging modeling. To show the effectiveness of the EMS, an electric bus case study is dealt with and a sensitivity analysis is performed over some critical optimization parameters to understand when purchasing a REX is interesting and economically effective.","PeriodicalId":358360,"journal":{"name":"2018 IEEE Conference on Control Technology and Applications (CCTA)","volume":"125 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115203840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/CCTA.2018.8511486
N. Prakash, Youngki Kim, Denise M. Rizzo, Matthew J. Brusstar, Jason B. Siegel
Eco-driving via velocity trajectory optimization and regenerative braking can both reduce the energy demand of an electric vehicle (EV). However, eco-driving can save more energy than can be recovered via regenerative braking due to the total roundtrip efficiency of the motor/generator. The optimal velocity trajectory would always avoid braking if the constraints allow. This paper investigates energy optimal velocity profiles for various electric ground vehicles over varying road grades, where the autonomous vehicles can adjust their velocity trajectory. The optimal velocity trajectories, numerically obtained from Dynamic Programming, significantly reduce the total energy demand by the motor compared to a constant cruising operation for the same travel distance and time. The optimized velocity trajectories, thus increase vehicle range without a change in battery size or trip time.
{"title":"Role of Regenerative Braking in Velocity Trajectory Optimization of Electrified Powertrains over varying Road Grades","authors":"N. Prakash, Youngki Kim, Denise M. Rizzo, Matthew J. Brusstar, Jason B. Siegel","doi":"10.1109/CCTA.2018.8511486","DOIUrl":"https://doi.org/10.1109/CCTA.2018.8511486","url":null,"abstract":"Eco-driving via velocity trajectory optimization and regenerative braking can both reduce the energy demand of an electric vehicle (EV). However, eco-driving can save more energy than can be recovered via regenerative braking due to the total roundtrip efficiency of the motor/generator. The optimal velocity trajectory would always avoid braking if the constraints allow. This paper investigates energy optimal velocity profiles for various electric ground vehicles over varying road grades, where the autonomous vehicles can adjust their velocity trajectory. The optimal velocity trajectories, numerically obtained from Dynamic Programming, significantly reduce the total energy demand by the motor compared to a constant cruising operation for the same travel distance and time. The optimized velocity trajectories, thus increase vehicle range without a change in battery size or trip time.","PeriodicalId":358360,"journal":{"name":"2018 IEEE Conference on Control Technology and Applications (CCTA)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115237724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/CCTA.2018.8511453
Chung-Shan Shih, Teng-Hu Cheng
An output-feedback-based decentralized controller that uses event-triggered communication is developed for the leader-follower consensus problem. An observer is designed to estimate the state of each agent, and the estimated state is communicated to its neighboring agents for interaction. To eliminate continuous inter-agent communication, another estimators that estimate the states of neighboring agents are designed for control feedback and are updated via intermittent communication to reset increasing estimate errors. The communication times are based on an event-triggered strategy and are adapted based on the interplay between the control performance and the amount of reduced communication. The main contribution of the developed triggering approach is that inter-agent communication is not required to determine when a state update is needed. Since the developed control scheme introduces switched dynamics, analysis is conducted to indicate that Zeno behavior does not exist. A convergence analysis is also conducted to show bounded convergence of the developed control methodology.
{"title":"Output-Feedback-Based Event-Triggered Control of Multi-Agent Systems Without Continuous Inter-Agent Communication","authors":"Chung-Shan Shih, Teng-Hu Cheng","doi":"10.1109/CCTA.2018.8511453","DOIUrl":"https://doi.org/10.1109/CCTA.2018.8511453","url":null,"abstract":"An output-feedback-based decentralized controller that uses event-triggered communication is developed for the leader-follower consensus problem. An observer is designed to estimate the state of each agent, and the estimated state is communicated to its neighboring agents for interaction. To eliminate continuous inter-agent communication, another estimators that estimate the states of neighboring agents are designed for control feedback and are updated via intermittent communication to reset increasing estimate errors. The communication times are based on an event-triggered strategy and are adapted based on the interplay between the control performance and the amount of reduced communication. The main contribution of the developed triggering approach is that inter-agent communication is not required to determine when a state update is needed. Since the developed control scheme introduces switched dynamics, analysis is conducted to indicate that Zeno behavior does not exist. A convergence analysis is also conducted to show bounded convergence of the developed control methodology.","PeriodicalId":358360,"journal":{"name":"2018 IEEE Conference on Control Technology and Applications (CCTA)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114152584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/CCTA.2018.8511395
S. Bortoff
In this paper we derive a dynamic model of the Delta robot that is well-suited to an object-oriented modeling framework. The approach uses an augmented Lagrangian or Hamiltonian formulation together with Baumgarte's method of index reduction, and results in a singularity-free dynamic model that is well suited to dynamic analysis, control system synthesis and time-domain simulation. The object-oriented structure enables broad application to problems such as coordinated control and robotic assembly. We present several common control algorithms and conduct a dynamic analysis of the Delta robot that shows that the open-loop system is unstable for large volumes of the reachable workspace, which has fundamental implications on closed-loop performance.
{"title":"Object-Oriented Modeling and Control of Delta Robots","authors":"S. Bortoff","doi":"10.1109/CCTA.2018.8511395","DOIUrl":"https://doi.org/10.1109/CCTA.2018.8511395","url":null,"abstract":"In this paper we derive a dynamic model of the Delta robot that is well-suited to an object-oriented modeling framework. The approach uses an augmented Lagrangian or Hamiltonian formulation together with Baumgarte's method of index reduction, and results in a singularity-free dynamic model that is well suited to dynamic analysis, control system synthesis and time-domain simulation. The object-oriented structure enables broad application to problems such as coordinated control and robotic assembly. We present several common control algorithms and conduct a dynamic analysis of the Delta robot that shows that the open-loop system is unstable for large volumes of the reachable workspace, which has fundamental implications on closed-loop performance.","PeriodicalId":358360,"journal":{"name":"2018 IEEE Conference on Control Technology and Applications (CCTA)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114233361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/CCTA.2018.8511318
S. Sabatini, M. Corno, Simone Fiorenti, S. Savaresi
Occupancy grid maps are by far the most used spatial representation of the environment for robot navigation. This paper proposes a simple and effective way to improve the occupancy grid accuracy by superimposing a small oscillation to the robot motion when a predefined path is given. The method is especially suited for range sensors with long range capabilities but poor angular resolution. The innovative solid state LiDAR technology is an example of such sensor configuration and is used in this work for the experimental evaluation of the presented dithering technique. Experimental results quantitatively demonstrated that the proposed oscillating motion is effective especially in speeding up the detection of corridor like clearances in the environment.
{"title":"Improving Occupancy Grid Mapping via Dithering for a Mobile Robot Equipped with Solid-State LiDAR Sensors","authors":"S. Sabatini, M. Corno, Simone Fiorenti, S. Savaresi","doi":"10.1109/CCTA.2018.8511318","DOIUrl":"https://doi.org/10.1109/CCTA.2018.8511318","url":null,"abstract":"Occupancy grid maps are by far the most used spatial representation of the environment for robot navigation. This paper proposes a simple and effective way to improve the occupancy grid accuracy by superimposing a small oscillation to the robot motion when a predefined path is given. The method is especially suited for range sensors with long range capabilities but poor angular resolution. The innovative solid state LiDAR technology is an example of such sensor configuration and is used in this work for the experimental evaluation of the presented dithering technique. Experimental results quantitatively demonstrated that the proposed oscillating motion is effective especially in speeding up the detection of corridor like clearances in the environment.","PeriodicalId":358360,"journal":{"name":"2018 IEEE Conference on Control Technology and Applications (CCTA)","volume":"559 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115102336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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