Active Pose SLAM

Valencia, Rafael; Andrade‐Cetto, Juan

doi:10.1007/978-3-319-60603-3_5

Cited by 29 publications

(20 citation statements)

References 28 publications

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“…The results of this approach were presented at IROS 2012 [173] and we are currently working on a journal submission on this work.…”

Section: Summary Of Contributionsmentioning

confidence: 99%

“…In [81] for instance, map optimization and pose optimization are jointly taken into account during exploration by defining a set of visibility nodes using a skeleton of the current map free zones, and planning an optimal path through these nodes. The same problem can also be addressed using frontiers instead as the driving nodes for exploration [173].…”

Section: Bibliographical Notesmentioning

confidence: 99%

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Mapping, Planning and Exploration with Pose SLAM

Valencia,

Andrade-Cetto

2018

Springer Tracts in Advanced Robotics

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This thesis reports research on mapping, path planning, and autonomous exploration. These are classical problems in robotics, typically studied independently, and here we link such problems by framing them within a common SLAM approach, adopting Pose SLAM as the basic state estimation machinery. The main contribution of this thesis is an approach that allows a mobile robot to plan a path using the map it builds with Pose SLAM and to select the appropriate actions to autonomously construct this map.Pose SLAM is the variant of SLAM where only the robot trajectory is estimated and where landmarks are only used to produce relative constraints between robot poses. In Pose SLAM, observations come in the form of relative-motion measurements between robot poses. With regards to extending the original Pose SLAM formulation, this thesis studies the computation of such measurements when they are obtained with stereo cameras and develops the appropriate noise propagation models for such case. Furthermore, the initial formulation of Pose SLAM assumes poses in SE(2) and in this thesis we extend this formulation to SE(3), parameterizing rotations either with Euler angles and quaternions. We also introduce a loop closure test that exploits the information from the filter using an independent measure of information content between poses. In the application domain, we present a technique to process the 3D volumetric maps obtained with this SLAM methodology, but with laser range scanning as the sensor modality, to derive traversability maps that were useful for the navigation of a heterogeneous fleet of mobile robots in the context of the EU project URUS.Aside from these extensions to Pose SLAM, the core contribution of the thesis is an approach for path planning that exploits the modeled uncertainties in Pose SLAM to search for the path in the pose graph with the lowest accumulated robot pose uncertainty, i.e., the path that allows the robot to navigate to a given goal with the least probability of becoming lost. An added advantage of the proposed path planning approach is that since Pose SLAM is agnostic with respect to the sensor modalities used, it can be used in different environments and with i different robots, and since the original pose graph may come from a previous mapping session, the paths stored in the map already satisfy constraints not easy modeled in the robot controller, such as the existence of restricted regions, or the right of way along paths. The proposed path planning methodology has been extensively tested both in simulation and with a real outdoor robot.Our path planning approach is adequate for scenarios where a robot is initially guided during map construction, but autonomous during execution. For other scenarios in which more autonomy is required, the robot should be able to explore the environment without any supervision. The second core contribution of this thesis is an autonomous exploration method that complements the aforementioned path planning strategy. The method selects the appropriate...

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“…The results of this approach were presented at IROS 2012 [173] and we are currently working on a journal submission on this work.…”

Section: Summary Of Contributionsmentioning

confidence: 99%

Section: Bibliographical Notesmentioning

confidence: 99%

Mapping, Planning and Exploration with Pose SLAM

Valencia,

Andrade-Cetto

2018

Springer Tracts in Advanced Robotics

Self Cite

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“…There are several works that perform active SLAM with sensors such as lasers for 2D/3D mapping [27], [28], [29], but Davison and Murray were the first who integrated motion with stereo visual SLAM [30] where their objective was to minimize the trajectory error. Most active SLAM algorithms are based on maximizing mutual information [8], [31], which is also referred to as maximizing information gain [32], [33].…”

Section: Active Slam With Information Divergencementioning

confidence: 99%

Application-oriented design space exploration for SLAM algorithms

Saeedi

Nardi

Johns

et al. 2017

2017 IEEE International Conference on Robotics and Automation (ICRA)

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Abstract-In visual SLAM, there are many software and hardware parameters, such as algorithmic thresholds and GPU frequency, that need to be tuned; however, this tuning should also take into account the structure and motion of the camera. In this paper, we determine the complexity of the structure and motion with a few parameters calculated using information theory. Depending on this complexity and the desired performance metrics, suitable parameters are explored and determined.Additionally, based on the proposed structure and motion parameters, several applications are presented, including a novel active SLAM approach which guides the camera in such a way that the SLAM algorithm achieves the desired performance metrics. Real-world and simulated experimental results demonstrate the effectiveness of the proposed design space and its applications.

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“…These works find locally-optimal solutions to the planning problem and provide promising results for robotics applications, especially point-to-point planning queries. Work in path planning for information gathering [12] and active SLAM systems [13][14][15] focused more on the interaction between planning and SLAM, and how the performance and efficiency of SLAM is improved with intelligent decisions regarding which paths to travel.…”

Section: A Related Workmentioning

confidence: 99%

Risk aversion in belief-space planning under measurement acquisition uncertainty

Chaves

Walls

Galceran

et al. 2015

2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Abstract-This paper reports on a Gaussian belief-space planning formulation for mobile robots that includes random measurement acquisition variables that model whether or not each measurement is actually acquired. We show that maintaining the stochasticity of these variables in the planning formulation leads to a random belief covariance matrix, allowing us to consider the risk associated with the acquisition in the objective function. Inspired by modern portfolio theory and utility optimization, we design objective functions that are risk-averse, and show that risk-averse planning leads to decisions made by the robot that are desirable when operating under uncertainty. We show the benefit of this approach using simulations of a planar robot traversing an uncertain environment and of an underwater robot searching for loopclosure actions while performing visual SLAM.

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Active Pose SLAM

Cited by 29 publications

References 28 publications

Mapping, Planning and Exploration with Pose SLAM

Mapping, Planning and Exploration with Pose SLAM

Application-oriented design space exploration for SLAM algorithms

Risk aversion in belief-space planning under measurement acquisition uncertainty

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