2012 IEEE/RSJ International Conference on Intelligent Robots and Systems 2012
DOI: 10.1109/iros.2012.6385662
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Planning trajectories on uneven terrain using optimization and non-linear time scaling techniques

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Cited by 11 publications
(4 citation statements)
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“…However as it will be shown in section V that the quality of feature tracking is significantly better on the constrained path. Figure 2(b) shows the satisfaction of constraint (7). As it can be seen from the figure, constraint satisfaction is good at almost all the place except a marginal violation at the middle of the path.…”
Section: A Initial Guess For Non-linear Optimizationmentioning
confidence: 90%
See 1 more Smart Citation
“…However as it will be shown in section V that the quality of feature tracking is significantly better on the constrained path. Figure 2(b) shows the satisfaction of constraint (7). As it can be seen from the figure, constraint satisfaction is good at almost all the place except a marginal violation at the middle of the path.…”
Section: A Initial Guess For Non-linear Optimizationmentioning
confidence: 90%
“…Further when moving from one viewpoint to another additional waypoints are generated to facilitate reversal along the path when conventional maneuvers do not satisfy the orientation constraints. Finally we invoke non-linear time scaling techniques, first introduced in [7] to embed velocity profiles onto the planned paths. The velocity profile provides for higher velocities when the camera is further away from objects while reduces as the camera approaches the object.…”
Section: Introductionmentioning
confidence: 99%
“…By using a B-cubic patch map, a near-optimal path planner for rough terrain navigation was proposed in [21], which adopted a layered control strategy that separated the trajectory planning and path following. Singh et al [22] proposed to use a non-linear time scaling technique to generate an optimal path on uneven terrain, with a special focus on avoiding possible slip of the vehicle. These methods are mainly designed for unmanned vehicles.…”
Section: B Path Planning Techniquesmentioning
confidence: 99%
“…Αρχικά, οι ερευνητές επέκτειναν τις υπάρχουσες βασικές θεωρίες (Eathakota et al (2011), Page et al (2006)) για αυτές τις περιπτώσεις, είτε δημιούργησαν νέες απλές θεωρίες (Miró et al (2010), Waheed & Fotouhi (2009)). Η αύξηση των κινηματικών περιορισμών που υπάρχουν σε αυτήν την περίπτωση (μέγιστη κλίση εδάφους, περιοχές όπου μπορεί να γίνει ανατροπή του οχήματος) οδήγησε την έρευνα προς πιο πολύπλοκους σχεδιαστές (Iagnemma et al (2008), Tahirovic & Magnani (2011)), που στην πλειονότητα των περιπτώσεων περιελάμβανε ελεγκτές πολλαπλών σταδίων (Cowlagi & Tsiotras (2012), Singh et al (2011Singh et al ( , 2012).…”
Section: βασικότερες τεχνικές σχεδιασμού κίνησηςunclassified