Efficient neighbourhood-based information gain approach for exploration of complex 3D environments

Quin, Phillip; Paul, Gavin; Alempijevic, Alen; Liu, Dikai; Dissanayake, Gamini

doi:10.1109/icra.2013.6630745

Cited by 31 publications

(21 citation statements)

References 10 publications

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“…In [13] a greedy approach was adopted which maximised the information gain for the entire set of poses, however this was found to be inefficient, especially when (as is the case in this application) the robot base is mobile and the robot's DOF count is increased. Alternatively, the nearest neighbour could be selected by analysing the pose set and moving to the nearest pose in configuration space (C-space) [17]. Randomly selecting a safe pose from the set would require no gain calculations but can be expected to be inefficient since it is undirected.…”

Section: Methodsmentioning

confidence: 99%

A sliding window approach to exploration for 3D map building using a biologically inspired bridge inspection robot

Paul

Quin

et al. 2015

2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER)

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This paper presents a Sliding Window approach to viewpoint selection when exploring an environment using a RGB-D sensor mounted to the end-effector of an inchworm climbing robot for inspecting areas inside steel bridge archways which cannot be easily accessed by workers. The proposed exploration approach uses a kinematic chain robot model and information theory-based next best view calculations to predict poses which are safe and are able to reduce the information remaining in an environment. At each exploration step, a viewpoint is selected by analysing the Pareto efficiency of the predicted information gain and the required movement for a set of candidate poses. In contrast to previous approaches, a sliding window is used to determine candidate poses so as to avoid the costly operation of assessing the set of candidates in its entirety. Experimental results in simulation and on a prototype climbing robot platform show the approach requires fewer gain calculations and less robot movement, and therefore is more efficient than other approaches when exploring a complex 3D steel bridge structure.

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Section: Methodsmentioning

confidence: 99%

A sliding window approach to exploration for 3D map building using a biologically inspired bridge inspection robot

Paul

Quin

et al. 2015

2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER)

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“…These views are re-evaluated using the convolution of two functions: the utility function and a Gaussian function that accounts for the positioning errors. A new exploration algorithm called nearest neighbour NBV (NN-NBV) was presented in the study by Quin et al, 29 which reduces the number of evaluated viewpoints considering the closest viewpoints in the configuration space. It also reduces the number of gain calculations, overall computations and the time required to perform the exploration.…”

Section: Exploratory-based Viewpoint Generationmentioning

confidence: 99%

A survey on inspecting structures using robotic systems

Almadhoun

Taha

Seneviratne

et al. 2016

International Journal of Advanced Robotic Systems

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Advancements in robotics and autonomous systems are being deployed nowadays in many application domains such as search and rescue, industrial automation, domestic services and healthcare. These systems are developed to tackle tasks in some of the most challenging, labour intensive and dangerous environments. Inspecting structures (e.g. bridges, buildings, ships, wind turbines and aircrafts) is considered a hard task for humans to perform and of critical importance since missing any details could affect the structure's performance and integrity. Additionally, structure inspection is time and resource intensive and should be performed as efficiently and accurately as possible. Inspecting various structures has been reported in the literature using different robotic platforms to: inspect difficult to reach areas and detect various types of faults and anomalies. Typically, inspection missions involve performing three main tasks: coverage path planning, shape, model or surface reconstruction and the actual inspection of the structure. Coverage path planning ensures the generation of an optimized path that guarantees the complete coverage of the structure of interest in order to gather highly accurate information to be used for shape/model reconstruction. This article aims to provide an overview of the recent work and breakthroughs in the field of coverage path planning and model reconstruction, with focus on 3D reconstruction, for the purpose of robotic inspection.

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“…It then details the formulation of the objective functions before presenting a pose optimisation nearest neighbour algorithm. Section III presents experimental results using data collected both in our laboratory and on-site, comparing the new approach to alternative approaches [5], [7], [11]. Section IV discusses the limitations and possible drawbacks to the approach.…”

Section: Introductionmentioning

confidence: 99%

Key feature-based approach for efficient exploration of structured environments

Paul

Quin

Yang

et al. 2015

2015 IEEE International Conference on Robotics and Biomimetics (ROBIO)

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This paper presents an exploration approach for robots to determine sensing actions that facilitate the building of surface maps of structured partially-known environments. This approach uses prior knowledge about key environmental features to rapidly generate an estimate of the rest of the environment. Specifically, in order to quickly detect key features, partial surface patches are used in combination with pose optimisation to select a pose from a set of nearest neighbourhood candidates, from which to make an observation of the surroundings. This paper enables the robot to greedily search through a sequence of nearest neighbour poses in configuration space, then converge upon poses from which key features can best be observed. The approach is experimentally evaluated and found to result in significantly fewer exploration steps compared to alternative approaches.

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Efficient neighbourhood-based information gain approach for exploration of complex 3D environments

Cited by 31 publications

References 10 publications

A sliding window approach to exploration for 3D map building using a biologically inspired bridge inspection robot

A sliding window approach to exploration for 3D map building using a biologically inspired bridge inspection robot

A survey on inspecting structures using robotic systems

Key feature-based approach for efficient exploration of structured environments

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