Author
Listed:
- Lim Yi
(ROAR Lab, Engineering Product Development, Singapore University of Technology and Design, Singapore 487372, Singapore)
- Anh Vu Le
(ROAR Lab, Engineering Product Development, Singapore University of Technology and Design, Singapore 487372, Singapore
Optoelectronics Research Group, Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City 700000, Vietnam)
- Joel Chan Cheng Hoong
(ROAR Lab, Engineering Product Development, Singapore University of Technology and Design, Singapore 487372, Singapore)
- Abdullah Aamir Hayat
(ROAR Lab, Engineering Product Development, Singapore University of Technology and Design, Singapore 487372, Singapore)
- Balakrishnan Ramalingam
(ROAR Lab, Engineering Product Development, Singapore University of Technology and Design, Singapore 487372, Singapore)
- Rajesh Elara Mohan
(ROAR Lab, Engineering Product Development, Singapore University of Technology and Design, Singapore 487372, Singapore)
- Kristor Leong
(ROAR Lab, Engineering Product Development, Singapore University of Technology and Design, Singapore 487372, Singapore)
- Karthikeyan Elangovan
(ROAR Lab, Engineering Product Development, Singapore University of Technology and Design, Singapore 487372, Singapore)
- Minh Tran
(Optoelectronics Research Group, Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City 700000, Vietnam)
- Minh V. Bui
(Faculty of Engineering and Technology, Nguyen Tat Thanh University, 300A-Nguyen Tat Thanh, Ward 13, District 4, Ho Chi Minh City 700000, Vietnam)
- Phan Van Duc
(Faculty of Automotive Engineering, School of Engineering and Technology, Van Lang University, Ho Chi Minh City 700000, Vietnam)
Abstract
Pavement in outdoor settings is an unstructured environment with sharp corners, varying widths, and pedestrian activity that poses navigation challenges while cleaning for autonomous systems. In this work, an approach towards navigating without collision in constrained pavement spaces using the optimal instantaneous center of rotation (ICR) is demonstrated using an in-house developed omnidirectional reconfigurable robot named Panthera. The Panthera reconfigurable design results in varying footprints, supported by passive linear joints along the robot width, with locomotion and steering action using four wheels independent steering drive (4WISD). The robot kinematics and perception sensors system are discussed. Further, the ICR selection is carried out using multi-objective optimization, considering functions for steering, varying width, distance, and clearance to avoid a collision. The framework is incorporated in a local navigation planner and demonstrated experimentally in real pavement settings. The results with optimal selection of ICR in two dimensional space within the robot footprint successfully perform smooth navigation in the constraint space. It is experimentally highlighted with four different scenarios, i.e., constraint conditions encountered by a robot during navigation. Moreover, the formulation of optimal selection of ICR while avoiding collision is generic and can be used for other mobile robot architectures.
Suggested Citation
Lim Yi & Anh Vu Le & Joel Chan Cheng Hoong & Abdullah Aamir Hayat & Balakrishnan Ramalingam & Rajesh Elara Mohan & Kristor Leong & Karthikeyan Elangovan & Minh Tran & Minh V. Bui & Phan Van Duc, 2022.
"Multi-Objective Instantaneous Center of Rotation Optimization Using Sensors Feedback for Navigation in Self-Reconfigurable Pavement Sweeping Robot,"
Mathematics, MDPI, vol. 10(17), pages 1-22, September.
Handle:
RePEc:gam:jmathe:v:10:y:2022:i:17:p:3169-:d:905629
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