PMID- 38005639
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20231127
IS  - 1424-8220 (Electronic)
IS  - 1424-8220 (Linking)
VI  - 23
IP  - 22
DP  - 2023 Nov 17
TI  - Application of Path Planning and Obstacle Avoidance for Riverbank Inspection.
LID - 10.3390/s23229253 [doi]
LID - 9253
AB  - Most coastal trash comes from land. To prevent and control ocean pollution, it 
      should be handled using sources that can maintain a clean ocean and improve the 
      marine ecological environment. The proposed system can be used to inspect 
      riverbanks and identify garbage on riverbanks. This waste can then be cleaned up 
      before flowing into the sea. In this study, we utilized an unmanned aerial 
      vehicle (UAV) to inspect riverbanks and applied path planning and obstacle 
      avoidance to enhance the efficiency of UAV performance and ensure good 
      adaptability in a complicated environment. Since most rivers in the middle and 
      upper sections of the study area are rough and meandering, path planning was 
      first addressed so that the drone could use the shortest path and less energy to 
      perform the inspection task. Branches frequently protrude from the riverbank on 
      both sides. Therefore, an instant obstacle avoidance algorithm was added to avoid 
      various obstacles. Path planning was based on an Improved Particle Swarm 
      Optimization (IPSO). A fuzzy system was added to the IPSO to adjust the 
      parameters that could shorten the planned path. The Artificial Potential Field 
      (APF) was applied for real-time dynamic obstacle avoidance. The proposed UAV 
      system could be used to perform riverbank inspection successfully.
FAU - Jhang, Jhong-Wei
AU  - Jhang JW
AD  - Department of Communications, Navigation and Control Engineering, National Taiwan 
      Ocean University, Keelung 202301, Taiwan.
FAU - Juang, Jih-Gau
AU  - Juang JG
AUID- ORCID: 0000-0003-2683-9931
AD  - Department of Communications, Navigation and Control Engineering, National Taiwan 
      Ocean University, Keelung 202301, Taiwan.
LA  - eng
GR  - MOST 110-2221-E-019 -075 -MY2/National Science and Technology Council, Taiwan/
GR  - Grand 110A29004/Rongcheng Circular Economy and Environmental Protection 
      Foundation, Taiwan/
PT  - Journal Article
DEP - 20231117
PL  - Switzerland
TA  - Sensors (Basel)
JT  - Sensors (Basel, Switzerland)
JID - 101204366
SB  - IM
PMC - PMC10674266
OTO - NOTNLM
OT  - artificial potential field
OT  - improved particle swarm optimization
OT  - obstacle avoidance
OT  - path planning
COIS- The authors declare no conflict of interest.
EDAT- 2023/11/25 12:43
MHDA- 2023/11/25 12:44
PMCR- 2023/11/17
CRDT- 2023/11/25 01:29
PHST- 2023/10/06 00:00 [received]
PHST- 2023/11/04 00:00 [revised]
PHST- 2023/11/14 00:00 [accepted]
PHST- 2023/11/25 12:44 [medline]
PHST- 2023/11/25 12:43 [pubmed]
PHST- 2023/11/25 01:29 [entrez]
PHST- 2023/11/17 00:00 [pmc-release]
AID - s23229253 [pii]
AID - sensors-23-09253 [pii]
AID - 10.3390/s23229253 [doi]
PST - epublish
SO  - Sensors (Basel). 2023 Nov 17;23(22):9253. doi: 10.3390/s23229253.