Motion prediction for moving objects: a statistical approach

Vasquez, Dizan; Fraichard, Thierry

doi:10.1109/robot.2004.1308883

Cited by 78 publications

(60 citation statements)

References 19 publications

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“…The control input u * s that is actually given to a robot has margin greater than or equal to β, (14) and it minimizes the cost in (15) :…”

Section: Avoiding Multiple Passive Agentsmentioning

confidence: 99%

“…In line 6, the function max(m) returns largest margin found for the tested control inputs. Lines 7 to 17 mention the procedure of finding control input, that minimize the cost given in (15), and have overestimated margin greater than or equal to β. If all the tested control inputs have margin less than β then the one with the biggest margin is returned.…”

Section: : End Formentioning

confidence: 99%

“…In most of the applications of navigating an agent, the moving obstacles has free will, and their future behavior is only partially predictable (if at all). When facing such situation, obstacle's path must be predicted using prediction techniques such as the ones presented in [14][15][16][17]. When the on-line path prediction is used to plan motion, it is likely that the model of the future that is obtained will have limited time duration.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Collision Avoidance from Multiple Passive Agents with Partially Predictable Behavior

et al. 2017

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Navigating a robot in a dynamic environment is a challenging task, especially when the behavior of other agents such as pedestrians, is only partially predictable. Also, the kinodynamic constraints on robot motion add an extra challenge. This paper proposes a novel navigational strategy for collision avoidance of a kinodynamically constrained robot from multiple moving passive agents with partially predictable behavior. Specifically, this paper presents a new approach to identify the set of control inputs to the robot, named control obstacle, which leads it towards a collision with a passive agent moving along an arbitrary path. The proposed method is developed by generalizing the concept of nonlinear velocity obstacle (NLVO), which is used to avoid collision with a passive agent, and takes into account the kinodynamic constraints on robot motion. Further, it formulates the navigational problem as an optimization problem, which allows the robot to make a safe decision in the presence of various sources of unmodelled uncertainties. Finally, the performance of the algorithm is evaluated for different parameters and is compared to existing velocity obstacle-based approaches. The simulated experiments show the excellent performance of the proposed approach in term of computation time and success rate.

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“…The control input u * s that is actually given to a robot has margin greater than or equal to β, (14) and it minimizes the cost in (15) :…”

Section: Avoiding Multiple Passive Agentsmentioning

confidence: 99%

Section: : End Formentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Collision Avoidance from Multiple Passive Agents with Partially Predictable Behavior

et al. 2017

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“…Probability density function (PDF) of the normal distribution is used to assess the likelihood of a partial path with the reference patterns (Eq. 5) 17) . When a blind traveler performs a new trajectory, at each production through the path, e.g., production L (t p ) at time instance t p , its location is given to a series of PDFs of path patterns: {L µ1 (t p ), σ 1 2 }, {L µ2 (t p ), σ 2 2 }, … from which the most probable pattern will be chosen.…”

Section: Way-finding Patterns and Path Estimationmentioning

confidence: 99%

A New Path Estimation Strategy for Predicting Blind Persons′ Motion in Indoor Environments

Motlagh

Hong

Ramli

et al. 2009

Journal of Asian Architecture and Building Engineering

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Research on the characteristics of spatial cognition without vision is used to improve the design of indoor environments to be safer for blind and visually handicapped persons. A fuzzy cognitive map (FCM) decision mechanism is presented for modeling path planning strategies adopted by blind travelers including wallfollowing, and shortcutting through the environment. A statistical case based reasoning (CBR) strategy is introduced for anticipating the points of switch between the two mentioned behaviours along the path. The combination of CBR and FCM modules provided a robust model of decision making which can be used for predicting blind motions. In this research, 51 eye-masked subjects contributed for obtaining the path patterns and for validating the results obtained using the proposed path prediction approach.

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“…The approaches in [2] and in [3], [4] aim at estimating the future position of a vehicle by its past movement. For that purpose, a database of motion primitives for different car actions is constructed preliminarily by recording trajectories.…”

Section: Introductionmentioning

confidence: 99%

Interactive scene prediction for automotive applications

Lawitzky

Althoff

Passenberg

et al. 2013

2013 IEEE Intelligent Vehicles Symposium (IV)

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Abstract-In this work, a framework for motion prediction of vehicles and safety assessment of traffic scenes is presented. The developed framework can be used for driver assistant systems as well as for autonomous driving applications. In order to assess the safety of the future trajectories of the vehicle, these systems require a prediction of the future motion of all traffic participants. As the traffic participants have a mutual influence on each other, the interaction of them is explicitly considered in this framework, which is inspired by an optimization problem. Taking the mutual influence of traffic participants into account, this framework differs from the existing approaches which consider the interaction only insufficiently, suffering reliability in real traffic scenes. For motion prediction, the collision probability of a vehicle performing a certain maneuver, is computed. Based on the safety evaluation and the assumption that drivers avoid collisions, the prediction is realized. Simulation scenarios and real-world results show the functionality.

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Motion prediction for moving objects: a statistical approach

Cited by 78 publications

References 19 publications

Collision Avoidance from Multiple Passive Agents with Partially Predictable Behavior

Collision Avoidance from Multiple Passive Agents with Partially Predictable Behavior

A New Path Estimation Strategy for Predicting Blind Persons′ Motion in Indoor Environments

Interactive scene prediction for automotive applications

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