$D^*_{+}$: A Generic Platform-Agnostic and Risk-Aware Path Planing Framework with an Expandable Grid

Karlsson, Samuel; Koval, Anton; Kanellakis, Christoforos; Agha–mohammadi, Ali–akbar; Nikolakopoulos, George

doi:10.48550/arxiv.2112.05563

Cited by 6 publications

(7 citation statements)

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“…However, the above method only ensures the safety of waypoints, and cannot guarantee the safety of trajectories generated according to waypoints. The method based on the risk index has been widely used on unmanned aerial vehicles [22], underwater vehicles [23], and ground mobile robots [24], but they still have some safety hazards.…”

Section: Related Workmentioning

confidence: 99%

A Global Trajectory Planning Framework Based on Minimizing the Risk Index

et al. 2023

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At present, autonomous mobile robots are widely used in industrial and commercial fields. However, although the global path searched by existing mobile robot path planning methods has no collision with obstacles, there is a problem in that the path is close to obstacles and is not smooth, and there is a collision safety risk when the robot is actually moving. To solve the above problems, this paper proposes a global path planning method based on minimizing the risk index. Firstly, the distance calculation method of the heuristic function of the traditional graph search algorithm is improved to reduce the number of nodes in the search space. Additionally, by selecting the appropriate search neighborhood, the search efficiency and path smoothness of the algorithm are improved. Thirdly, to increase the distance between the original search path and obstacles, the risk index path search strategy is proposed. Finally, the minimized snap trajectory smoothing method with a safe corridor is used to smooth the original waypoint. Both simulation and real robot experimental results show that the minimum distance between waypoints and obstacles is increased by 43.72% on average, and the number of trajectory inflection points are reduced by 75.12% on average after optimization. As such, the proposed method can fully guarantee safety and generate smooth mobile robot paths in global trajectory planning tasks.

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Section: Related Workmentioning

confidence: 99%

A Global Trajectory Planning Framework Based on Minimizing the Risk Index

et al. 2023

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“…In order to realize the concept of hyper-modality robots [47], risk-aware path planning [48] is necessary to be considered. Autonomous path planning algorithms for ground-based robotic manoeuvres on planetary exploration are documented in [49,50] and for ground and aerial robots in [51].…”

Section: Autonomous Path Planningmentioning

confidence: 99%

Resiliency in Space Autonomy: a Review

et al. 2023

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Purpose of Review: The article provides an extensive overview on the resilient autonomy advances made across various missions, orbital or deep-space, that captures the current research approaches while investigating the possible future direction of resiliency in space autonomy. Recent Findings: In recent years, the need for several automated operations in space applications has been rising, that ranges from the following: spacecraft proximity operations, navigation and some station keeping applications, entry, decent and landing, planetary surface exploration, etc. Also, with the rise of miniaturization concepts in spacecraft, advanced missions with multiple spacecraft platforms introduce more complex behaviours and interactions within the agents, which drives the need for higher levels of autonomy and accommodating collaborative behaviour coupled with robustness to counter unforeseen uncertainties. This collective behaviour is now referred to as resiliency in autonomy. As space missions are getting more and more complex, for example applications where a platform physically interacts with non-cooperative space objects (debris) or planetary bodies coupled with hostile, unpredictable, and extreme environments, there is a rising need for resilient autonomy solutions. Summary Resilience with its key attributes of robustness, redundancy and resourcefulness will lead toward new and enhanced mission paradigms of space missions.

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“…Occupancy mapping, frontier generation, frontier selection, and occupancy-based path planning all rely on the ability to produce a consistent and, most importantly, a dense map of the environment, where a selected frontier point can be reached or seen without risking a crash, and where holes or unseen areas in the map don't promote unwanted or risky path planning behavior e.g. getting stuck, generating paths that go through holes or too close to the walls (a problem specifically analyzed in [34]), or excessively moving backand-forth in order to completely map the area due to hardto-see frontiers. In general, for rapid deployment and efficient exploration, the proposed desired navigation behavior in these tunnels is to move in the center of the tunnel, at a good distance from the ground and ceiling, while following the tunnel direction and avoiding any encountered obstacles.…”

Section: The Subterranean Tunnel Environmentmentioning

confidence: 99%

COMPRA: A COMPact Reactive Autonomy Framework for Subterranean MAV Based Search-And-Rescue Operations

Lindqvist

Kanellakis

Mansouri

et al. 2022

J Intell Robot Syst

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This work establishes COMPRA, a compact and reactive autonomy framework for fast deployment of Micro Aerial Vehicles (MAVs) in subterranean Search-and- Rescue (SAR) missions. A COMPRA-enabled MAV is able to autonomously explore previously unknown areas while specific mission criteria are considered e.g. an object of interest is identified and localized, the remaining useful battery life, the overall desired exploration mission duration. The proposed architecture follows a low-complexity algorithmic design to facilitate fully on-board computations, including nonlinear control, state-estimation, navigation, exploration behavior and object localization capabilities. The framework is mainly structured around a reactive local avoidance planner, based on enhanced Potential Field concepts and using instantaneous 3D pointclouds, as well as a computationally efficient heading regulation technique, based on depth images from an instantaneous camera stream. Those techniques decouple the collision-free path generation from the dependency of a global map and are capable of handling imprecise localization occasions. Field experimental verification of the overall architecture is performed in relevant unknown Global Positioning System (GPS)-denied environments.

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$D^*_{+}$: A Generic Platform-Agnostic and Risk-Aware Path Planing Framework with an Expandable Grid

Cited by 6 publications

References 0 publications

A Global Trajectory Planning Framework Based on Minimizing the Risk Index

A Global Trajectory Planning Framework Based on Minimizing the Risk Index

Resiliency in Space Autonomy: a Review

COMPRA: A COMPact Reactive Autonomy Framework for Subterranean MAV Based Search-And-Rescue Operations

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