Predictive and Multirate Sensor-Based Planning Under Uncertainty

Mora, Marta C.; Tornero, Josep

doi:10.1109/tits.2014.2366974

Cited by 11 publications

(7 citation statements)

References 39 publications

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“…If the robot is holonomic (equal variance in X and Y positions), the ellipse turns into a circumference. If spherical bounding volumes are used to account for the vehicle size, in the case of an omnidirectional vehicle, these volumes can be transformed into an increase in the variance of these functions and an uncertainty bounding volume can be defined, as in [33], including the uncertainty area due to noise as well as the robot volume (radius of the bounding sphere). Additionally, a security radius can also be considered in this model in the context of minimum distance from walls.…”

Section: Source Term Definitionmentioning

confidence: 99%

Real-Time Path Planning Based on Harmonic Functions under a Proper Generalized Decomposition-Based Framework

Montés

Chinesta

Mora

et al. 2021

Sensors

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This paper presents a real-time global path planning method for mobile robots using harmonic functions, such as the Poisson equation, based on the Proper Generalized Decomposition (PGD) of these functions. The main property of the proposed technique is that the computational cost is negligible in real-time, even if the robot is disturbed or the goal is changed. The main idea of the method is the off-line generation, for a given environment, of the whole set of paths from any start and goal configurations of a mobile robot, namely the computational vademecum, derived from a harmonic potential field in order to use it on-line for decision-making purposes. Up until now, the resolution of the Laplace or Poisson equations has been based on traditional numerical techniques unfeasible for real-time calculation. This drawback has prevented the extensive use of harmonic functions in autonomous navigation, despite their powerful properties. The numerical technique that reverses this situation is the Proper Generalized Decomposition. To demonstrate and validate the properties of the PGD-vademecum in a potential-guided path planning framework, both real and simulated implementations have been developed. Simulated scenarios, such as an L-Shaped corridor and a benchmark bug trap, are used, and a real navigation of a LEGO®MINDSTORMS robot running in static environments with variable start and goal configurations is shown. This device has been selected due to its computational and memory-restricted capabilities, and it is a good example of how its properties could help the development of social robots.

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Section: Source Term Definitionmentioning

confidence: 99%

Real-Time Path Planning Based on Harmonic Functions under a Proper Generalized Decomposition-Based Framework

Montés

Chinesta

Mora

et al. 2021

Sensors

Self Cite

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“…In these methods, the movement of the robot is determined by repulsive forces associated with obstacles and attractive forces associated to the goal position of the mobile robot. In this work, the potential field projection method (PFP) has been used [50,51].…”

Section: Properties Of Parametric Curves and Its Applications In Robomentioning

confidence: 99%

Path Planning Based on Parametric Curves

Pérez¹,

Aguilar²,

MontésSánchez³

et al. 2018

Advanced Path Planning for Mobile Entities

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Parametric curves are extensively used in engineering. The most commonly used parametric curves are, Bézier, B-splines, (NURBSs), and rational Bézier. Each and every one of them has special features, being the main difference between them the complexity of their mathematical definition. While Bézier curves are the simplest ones, B-splines or NURBSs are more complex. In mobile robotics, two main problems have been addressed with parametric curves. The first one is the definition of an initial trajectory for a mobile robot from a start location to a goal. The path has to be a continuous curve, smooth and easy to manipulate, and the properties of the parametric curves meet these requirements. The second one is the modification of the initial trajectory in real time attending to the dynamic properties of the environment. Parametric curves are capable of enhancing the trajectories produced by path planning algorithms adapting them to the kinematic properties of the robot. In order to avoid obstacles, the shape modification of parametric curves is required. In this chapter, an algorithm is proposed for computing an initial Bézier trajectory of a mobile robot and subsequently modifies it in real time in order to avoid obstacles in a dynamic environment.

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“…In [ 15 ], a general formulation of a predictive and multirate reactive planning method for AV in dynamic environments with uncertainty is introduced. Malone N. [ 16 ] uses a stochastic reachable set-based potential field to improve the success rate of path planning. In [ 11 – 16 ], although dynamic obstacle avoidance is realized, the speed of obstacle is set to a specific value and ignores the acceleration of the obstacle.…”

Section: Section 1: Introductionmentioning

confidence: 99%

Highly smooth and parameter independent obstacle avoidance method for autonomous vehicle with velocity-varying obstacle

Yi,

Liu,

Yuan

2024

PLoS ONE

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One of the primary challenges for autonomous vehicle (AV) is planning a collision-free path in dynamic environment. It is a tricky task for achieving high-performance obstacle avoidance with velocity-varying obstacle. To solve this problem, a highly smooth and parameter independent obstacle avoidance method for autonomous vehicle with velocity-varying obstacle (HSPI-OAM) is presented in this work. The proposed method uses the virtual collision point model to accurately design the desired acceleration, which makes the obtained path highly smooth. At the same time, the method gets rid of the dependence on parameter adjustment and has strong adaptability to different environments. The simulation is implemented on the Matlab-Carsim co-simulation platform, and the simulation results show that the path planned by HSPI-OAM has good performance for obstacle with acceleration.

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Predictive and Multirate Sensor-Based Planning Under Uncertainty

Cited by 11 publications

References 39 publications

Real-Time Path Planning Based on Harmonic Functions under a Proper Generalized Decomposition-Based Framework

Real-Time Path Planning Based on Harmonic Functions under a Proper Generalized Decomposition-Based Framework

Path Planning Based on Parametric Curves

Highly smooth and parameter independent obstacle avoidance method for autonomous vehicle with velocity-varying obstacle

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