Off-road path recognition using computer vision : evaluating state-of-the-art road techniques when applied to adverse terrain conditions
This work presents a number of state-of-the-art methods for road recognition applied to adverse off-road scenarios. In general, reliable deployment of unmanned ground vehicles in these kinds of environments depends on the combined use of expensive sophisticated sensors, in order to guarantee the sys...
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2022
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| Διαθέσιμο Online: | http://hdl.handle.net/10889/16087 |
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nemertes-10889-160872022-09-06T05:13:24Z Off-road path recognition using computer vision : evaluating state-of-the-art road techniques when applied to adverse terrain conditions Αναγνώριση μονοπατιού εκτός-δρόμου με χρήση ρομποτικής όρασης : εφαρμογή σύγχρονων τεχνικών αναγνώρισης δρόμου σε αντίξοες συνθήκες Καράμπαλης, Λάμπρος Karampalis, Lampros Computer vision Off-road recognition Ρομποτική όραση Αναγνώριση αντίξοου δρόμου This work presents a number of state-of-the-art methods for road recognition applied to adverse off-road scenarios. In general, reliable deployment of unmanned ground vehicles in these kinds of environments depends on the combined use of expensive sophisticated sensors, in order to guarantee the system’s robustness. Of the available sensors, cameras present the most inexpensive and approachable option. Thus, this work recreates and evaluates computer vision methods, developed for road following off-road or not, when applied on more challenging scenarios than those originally tested on, dictated by road texture and colour, obstructive foliage and terrain and inconsistent lighting conditions. The conclusions do not intent to identify a method better than the others, but rather evaluate the strengths and weaknesses of each method, while keeping an open mind on possible combinations and additions that would prove the methods more effective. Η παρούσα εργασία παραθέτει αριθμό σύγχρονων μεθόδων αναγνώρισης δρόμου που δύνανται να εφαρμοστούν σε εκτός δρόμου συνθήκες. Γενικότερα, η πρακτική χρήση μη επανδρωμένων οχημάτων σε αντίξοες συνθήκες προϋποθέτει την χρήση πολλαπλών εξειδικευμένων αισθητήρων προκειμένου να εγγυάται την αξιοπιστία και την σθεναρότητα του συστήματος. Από τους διαθέσιμους αισθητήρες, οι οπτικές κάμερες εκπροσωπούν την οικονομικότερη και πιο προσιτή επιλογή στο πλαίσιο έρευνας της παρούσας εργασίας. Επακόλουθα, η εργασία περιλαμβάνει την αναπαραγωγή τεχνικών ρομποτικής όρασης, ήδη ανεπτυγμένων από άλλους ερευνητές, που αποσκοπούν στην διερεύνηση ύπαρξης δρόμου διαμορφωμένου ή μη, και την αξιολόγηση αυτών σε συνθήκες αντιξοότερες από αυτές που αποσκοπούσε η δημιουργία τους. Τα αποτελέσματα της αξιολόγησης δεν έχουν στόχο να προβάλλουν την ικανότερη των μεθόδων, αλλά τη διερεύνηση των δυνατοτήτων και αδυναμιών αυτών, έχοντας υπόψιν πιθανούς συνδυασμούς και προσθήκες προς τη βελτίωση της αποτελεσματικότητας αυτών. 2022-03-17T06:37:35Z 2022-03-17T06:37:35Z 2022-02-11 http://hdl.handle.net/10889/16087 en application/pdf |
| institution |
UPatras |
| collection |
Nemertes |
| language |
English |
| topic |
Computer vision Off-road recognition Ρομποτική όραση Αναγνώριση αντίξοου δρόμου |
| spellingShingle |
Computer vision Off-road recognition Ρομποτική όραση Αναγνώριση αντίξοου δρόμου Καράμπαλης, Λάμπρος Off-road path recognition using computer vision : evaluating state-of-the-art road techniques when applied to adverse terrain conditions |
| description |
This work presents a number of state-of-the-art methods for road recognition applied to adverse off-road scenarios. In general, reliable deployment of unmanned ground vehicles in these kinds of environments depends on the combined use of expensive sophisticated sensors, in order to guarantee the system’s robustness. Of the available sensors, cameras present the most inexpensive and approachable option. Thus, this work recreates and evaluates computer vision methods, developed for road following off-road or not, when applied on more challenging scenarios than those originally tested on, dictated by road texture and colour, obstructive foliage and terrain and inconsistent lighting conditions. The conclusions do not intent to identify a method better than the others, but rather evaluate the strengths and weaknesses of each method, while keeping an open mind on possible combinations and additions that would prove the methods more effective. |
| author2 |
Karampalis, Lampros |
| author_facet |
Karampalis, Lampros Καράμπαλης, Λάμπρος |
| author |
Καράμπαλης, Λάμπρος |
| author_sort |
Καράμπαλης, Λάμπρος |
| title |
Off-road path recognition using computer vision : evaluating state-of-the-art road techniques when applied to adverse terrain conditions |
| title_short |
Off-road path recognition using computer vision : evaluating state-of-the-art road techniques when applied to adverse terrain conditions |
| title_full |
Off-road path recognition using computer vision : evaluating state-of-the-art road techniques when applied to adverse terrain conditions |
| title_fullStr |
Off-road path recognition using computer vision : evaluating state-of-the-art road techniques when applied to adverse terrain conditions |
| title_full_unstemmed |
Off-road path recognition using computer vision : evaluating state-of-the-art road techniques when applied to adverse terrain conditions |
| title_sort |
off-road path recognition using computer vision : evaluating state-of-the-art road techniques when applied to adverse terrain conditions |
| publishDate |
2022 |
| url |
http://hdl.handle.net/10889/16087 |
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