Normal Distributions Transform Occupancy Maps: Application to large-scale online 3D mapping

Abstract

Autonomous vehicles operating in real-world industrial environments have to overcome numerous challenges, chief among which is the creation and maintenance of consistent 3D world models. This paper proposes to address the challenges of online real-world mapping by building upon previous work on compact spatial representation and formulating a novel 3D mapping approach -the Normal Distributions Transform Occupancy Map (NDT-OM). The presented algorithm enables accurate real-time 3D mapping in large-scale dynamic environments employing a recursive update strategy. In addition, the proposed approach can seamlessly provide maps at multiple resolutions allowing for fast utilization in high-level functions such as localization or path planning. Compared to previous approaches that use the NDT representation, the proposed NDT-OM formulates an exact and efficient recursive update formulation and models the full occupancy of the map.

Fast 3D mapping in highly dynamic environments using normal distributions transform occupancy maps

“…In our prior work [10], we introduced the Normal Distributions Transform Occupancy Maps (NDT-OM) -a 3D mapping approach using the NDT representation. NDT-OM introduced recursive covariance updates and models the occupancy of each cell using the log-likelihood approach [9], similarly to an occupancy grid.…”

“…In addition, the NDT-OM is recursively updated. NDT-OM was shown in [10] to be feasible for mapping large-scale environments, even in the presence of dynamic changes. However, it does not account for two important aspects of the map update procedure.…”

“…NDT has later been extended to 3D scan registration [5], [12]. In a recent paper [10] we introduced the Normal Distributions Transform Occupancy All autohors are with Center of Applied Autonomous Sensor Systems (AASS), Örebro University, Sweden. Email: {first name}.…”

“…The second aspect concerns the update of an NDT cell covariance estimate in dynamic environments. In our previous work [10], measurements from dynamic objects are fused into the model, resulting in covariance estimates that represents a combination of both static and dynamic entities. In this paper, we address these shortcomings by: 1) introducing a probabilistic occupancy update approach that accounts for the shape of the estimated covariance in each cell during raycasting and 2) proposing a modified recursive covariance adaptation approach that allows faster adaptation to dynamic changes in the environment.…”

RMAP: a rectangular cuboid approximation framework for 3D environment mapping

“…A fully probabilistic grid structure based on octrees titled Octomap (Wurm et al 2010;Hornung et al 2013) has been presented which generates accurate 3D environment representations. Recently an extension of 3D NDT concepts titled NDT-OM (Occupancy mapping) has been presented (Saarinen et al 2013) which has similar computational complexity to Octomap (Wurm et al 2010;Hornung et al 2013), whereas the memory complexity issue is not discussed.…”