The Experts below are selected from a list of 117 Experts worldwide ranked by ideXlab platform

Jua Nieto - One of the best experts on this subject based on the ideXlab platform.

  • voxgraph globally consistent volumetric mapping using signed distance function submaps
    International Conference on Robotics and Automation, 2020
    Co-Authors: Victo Reijgwa, Alexande Millane, Hele Oleynikova, Roland Siegwa, Cesa Cadena, Jua Nieto
    Abstract:

    Globally consistent dense maps are a key requirement for long-term robot navigation in complex environments. While previous works have addressed the challenges of dense mapping and global consistency, most require more computational resources than may be available on-board small robots. We propose a framework that creates globally consistent volumetric maps on a CPU and is lightweight enough to run on computationally constrained platforms. Our approach represents the environment as a collection of overlapping signed distance function (SDF) submaps and maintains global consistency by computing an optimal alignment of the submap collection. By exploiting the underlying SDF representation, we generate correspondence-free constraints between submap pairs that are computationally efficient enough to optimize the global problem each time a new submap is added. We deploy the proposed system on a hexacopter micro aerial vehicle (MAV) with an Intel i7-8650 U CPU in two realistic scenarios: mapping a large-scale area using a 3D LiDAR and mapping an Industrial Space using an RGB-D camera. In the large-scale outdoor experiments, the system optimizes a 120 × 80 m map in less than 4 s and produces absolute trajectory RMSEs of less than 1 m over 400 m trajectories. Our complete system, called voxgraph , is available as open source. 1 1 https://github.com/ethz-asl/voxgraph .

Victo Reijgwa - One of the best experts on this subject based on the ideXlab platform.

  • voxgraph globally consistent volumetric mapping using signed distance function submaps
    International Conference on Robotics and Automation, 2020
    Co-Authors: Victo Reijgwa, Alexande Millane, Hele Oleynikova, Roland Siegwa, Cesa Cadena, Jua Nieto
    Abstract:

    Globally consistent dense maps are a key requirement for long-term robot navigation in complex environments. While previous works have addressed the challenges of dense mapping and global consistency, most require more computational resources than may be available on-board small robots. We propose a framework that creates globally consistent volumetric maps on a CPU and is lightweight enough to run on computationally constrained platforms. Our approach represents the environment as a collection of overlapping signed distance function (SDF) submaps and maintains global consistency by computing an optimal alignment of the submap collection. By exploiting the underlying SDF representation, we generate correspondence-free constraints between submap pairs that are computationally efficient enough to optimize the global problem each time a new submap is added. We deploy the proposed system on a hexacopter micro aerial vehicle (MAV) with an Intel i7-8650 U CPU in two realistic scenarios: mapping a large-scale area using a 3D LiDAR and mapping an Industrial Space using an RGB-D camera. In the large-scale outdoor experiments, the system optimizes a 120 × 80 m map in less than 4 s and produces absolute trajectory RMSEs of less than 1 m over 400 m trajectories. Our complete system, called voxgraph , is available as open source. 1 1 https://github.com/ethz-asl/voxgraph .

Alexande Millane - One of the best experts on this subject based on the ideXlab platform.

  • voxgraph globally consistent volumetric mapping using signed distance function submaps
    International Conference on Robotics and Automation, 2020
    Co-Authors: Victo Reijgwa, Alexande Millane, Hele Oleynikova, Roland Siegwa, Cesa Cadena, Jua Nieto
    Abstract:

    Globally consistent dense maps are a key requirement for long-term robot navigation in complex environments. While previous works have addressed the challenges of dense mapping and global consistency, most require more computational resources than may be available on-board small robots. We propose a framework that creates globally consistent volumetric maps on a CPU and is lightweight enough to run on computationally constrained platforms. Our approach represents the environment as a collection of overlapping signed distance function (SDF) submaps and maintains global consistency by computing an optimal alignment of the submap collection. By exploiting the underlying SDF representation, we generate correspondence-free constraints between submap pairs that are computationally efficient enough to optimize the global problem each time a new submap is added. We deploy the proposed system on a hexacopter micro aerial vehicle (MAV) with an Intel i7-8650 U CPU in two realistic scenarios: mapping a large-scale area using a 3D LiDAR and mapping an Industrial Space using an RGB-D camera. In the large-scale outdoor experiments, the system optimizes a 120 × 80 m map in less than 4 s and produces absolute trajectory RMSEs of less than 1 m over 400 m trajectories. Our complete system, called voxgraph , is available as open source. 1 1 https://github.com/ethz-asl/voxgraph .

  • voxgraph globally consistent volumetric mapping using signed distance function submaps
    arXiv: Robotics, 2020
    Co-Authors: Victor Reijgwart, Alexande Millane, Hele Oleynikova, Roland Siegwart, Cesar Cadena, Juan Nieto
    Abstract:

    Globally consistent dense maps are a key requirement for long-term robot navigation in complex environments. While previous works have addressed the challenges of dense mapping and global consistency, most require more computational resources than may be available on-board small robots. We propose a framework that creates globally consistent volumetric maps on a CPU and is lightweight enough to run on computationally constrained platforms. Our approach represents the environment as a collection of overlapping Signed Distance Function (SDF) submaps, and maintains global consistency by computing an optimal alignment of the submap collection. By exploiting the underlying SDF representation, we generate correspondence free constraints between submap pairs that are computationally efficient enough to optimize the global problem each time a new submap is added. We deploy the proposed system on a hexacopter Micro Aerial Vehicle (MAV) with an Intel i7-8650U CPU in two realistic scenarios: mapping a large-scale area using a 3D LiDAR, and mapping an Industrial Space using an RGB-D camera. In the large-scale outdoor experiments, the system optimizes a 120x80m map in less than 4s and produces absolute trajectory RMSEs of less than 1m over 400m trajectories. Our complete system, called voxgraph, is available as open source.

Hele Oleynikova - One of the best experts on this subject based on the ideXlab platform.

  • voxgraph globally consistent volumetric mapping using signed distance function submaps
    International Conference on Robotics and Automation, 2020
    Co-Authors: Victo Reijgwa, Alexande Millane, Hele Oleynikova, Roland Siegwa, Cesa Cadena, Jua Nieto
    Abstract:

    Globally consistent dense maps are a key requirement for long-term robot navigation in complex environments. While previous works have addressed the challenges of dense mapping and global consistency, most require more computational resources than may be available on-board small robots. We propose a framework that creates globally consistent volumetric maps on a CPU and is lightweight enough to run on computationally constrained platforms. Our approach represents the environment as a collection of overlapping signed distance function (SDF) submaps and maintains global consistency by computing an optimal alignment of the submap collection. By exploiting the underlying SDF representation, we generate correspondence-free constraints between submap pairs that are computationally efficient enough to optimize the global problem each time a new submap is added. We deploy the proposed system on a hexacopter micro aerial vehicle (MAV) with an Intel i7-8650 U CPU in two realistic scenarios: mapping a large-scale area using a 3D LiDAR and mapping an Industrial Space using an RGB-D camera. In the large-scale outdoor experiments, the system optimizes a 120 × 80 m map in less than 4 s and produces absolute trajectory RMSEs of less than 1 m over 400 m trajectories. Our complete system, called voxgraph , is available as open source. 1 1 https://github.com/ethz-asl/voxgraph .

  • voxgraph globally consistent volumetric mapping using signed distance function submaps
    arXiv: Robotics, 2020
    Co-Authors: Victor Reijgwart, Alexande Millane, Hele Oleynikova, Roland Siegwart, Cesar Cadena, Juan Nieto
    Abstract:

    Globally consistent dense maps are a key requirement for long-term robot navigation in complex environments. While previous works have addressed the challenges of dense mapping and global consistency, most require more computational resources than may be available on-board small robots. We propose a framework that creates globally consistent volumetric maps on a CPU and is lightweight enough to run on computationally constrained platforms. Our approach represents the environment as a collection of overlapping Signed Distance Function (SDF) submaps, and maintains global consistency by computing an optimal alignment of the submap collection. By exploiting the underlying SDF representation, we generate correspondence free constraints between submap pairs that are computationally efficient enough to optimize the global problem each time a new submap is added. We deploy the proposed system on a hexacopter Micro Aerial Vehicle (MAV) with an Intel i7-8650U CPU in two realistic scenarios: mapping a large-scale area using a 3D LiDAR, and mapping an Industrial Space using an RGB-D camera. In the large-scale outdoor experiments, the system optimizes a 120x80m map in less than 4s and produces absolute trajectory RMSEs of less than 1m over 400m trajectories. Our complete system, called voxgraph, is available as open source.

Steven Rothberg - One of the best experts on this subject based on the ideXlab platform.

  • regional logistics hubs freight activity and Industrial Space demand econometric analysis
    Research in transportation business and management, 2014
    Co-Authors: Christopher Lindsey, Hani S. Mahmassani, Matt Mullarkey, Terry Nash, Steven Rothberg
    Abstract:

    Abstract There has been a continuing interest among transportation researchers and the logistics industry in the relationship between the consumption of Industrial Space and freight transportation activity. With the growing importance of logistics and supply chain economics to global industries, firms organizing their Industrial activities and locating their warehousing and operational centers must increasingly consider the availability, quality and cost of a range of transportation services. Accordingly, the development of logistics facilities in conjunction with regional freight transportation hubs has become an important element of the overall Industrial economy, predicated on the notion that robust freight activity is a good indicator of the consumption of Industrial Space. In this study, we conduct an econometric analysis of a longitudinal data set consisting of twenty metropolitan markets observed annually from 1997 to 2007. From those results, we develop a methodology to score and rank metropolitan markets according to their potential for Industrial Space consumption based on macroeconomic, demographic, and freight flow variables.

  • Industrial Space demand and freight transportation activity exploring the connection
    Journal of Transport Geography, 2014
    Co-Authors: Christopher Lindsey, Hani S. Mahmassani, Matt Mullarkey, Terry Nash, Steven Rothberg
    Abstract:

    There has been continuing interest among transportation planners, economic development specialists, and private industry about the relationship between the demand for Industrial Space and the level of freight transportation activity. With the growing importance of logistics and supply chain economics for many Industrial and business activities, firms organizing their Industrial activities and locating their warehousing and operational centers increasingly must consider the availability, quality, and cost of a range of transportation services, particularly in connection with essential intermodal activities. Accordingly, development of major logistics parks in conjunction with major intermodal hubs has become an important element in the overall Industrial economy, predicated on the notion that robust freight activity is a good indicator of demand for Industrial Space. In this study, using regression techniques, we examine the relationship between freight transportation activity and Industrial Space demand at the metropolitan area level. The results confirm this relationship, reflecting significant statistical association between higher levels of freight traffic and higher levels of Industrial Space demand. This relationship is more pronounced in inland versus port markets. In addition, the data reveal that there was a shock to Industrial Space demand in 2001, thereby altering the structural relationship between demand and the drivers of demand.

  • Industrial Space demand and freight transportation activity exploring the connection
    Transportation Research Board 92nd Annual MeetingTransportation Research Board, 2013
    Co-Authors: Christopher Lindsey, Hani S. Mahmassani, Matt Mullarkey, Terry Nash, Steven Rothberg
    Abstract:

    There has been continuing interest among transportation planners, economic development specialists and private industry about the relationship between the demand for Industrial Space and the level of freight transportation activity. With the growing importance of logistics and supply chain economics to many Industrial and business activities, the organization of Industrial activity and optimal location of warehousing and operational centers must increasingly consider the availability, quality and cost of a range of transportation services, particularly in connection with essential intermodal activities. Accordingly, development of major logistics parks in conjunction with major intermodal hubs has become an important element in the overall Industrial economy, predicated on the notion that robust freight activity is a good indicator of demand for Industrial Space. In this study, using regression techniques, the authors examine the relationship between freight transportation activity and Industrial Space demand at the metropolitan area level. The results confirm this relationship, reflecting significant statistical association between higher levels of freight traffic and higher levels of Industrial Space demand. This relationship is more pronounced in inland versus port markets. In addition, the data reveals that there was a shock to the demand for Industrial Space in the year 2001, thereby altering the structural relationship between demand and the drivers of demand.