A novel optimal path-planning and following algorithm for wheeled robots on deformable terrains. (August 2021)
- Record Type:
- Journal Article
- Title:
- A novel optimal path-planning and following algorithm for wheeled robots on deformable terrains. (August 2021)
- Main Title:
- A novel optimal path-planning and following algorithm for wheeled robots on deformable terrains
- Authors:
- Taghavifar, Hamid
Rakheja, Subhash
Reina, Giulio - Abstract:
- Highlights: A novel path-planning and following algorithm is proposed for robots on deformable terrains. Exponential sliding mode reaching law is practiced for a smooth asymptotic stability of controller. CAPSO is adopted for multi-criteria path-planning and RBF-NN as a disturbance observer. Abstract: An immense body of research has focused on path-planning and following of wheeled robots in unstructured surfaces. Nonholonomic robots traveling over deformable terrains together with complex operating conditions, however, pose further challenges in terms of a higher demand for robustness and optimality. In this paper, a Chaos-enhanced Accelerated Particle Swarm Optimization (CAPSO) algorithm is employed for planning an optimal path of a wheeled robot, so as to ensure shortest path from the starting point to the target location together with safety through guaranteed avoidance of collisions with static and dynamic obstacles. The fundamental terramechanics concepts are employed to derive essential forces and moments acting on the wheeled robot. Subsequently, a kineto-dynamic model of the robot is developed for designing a novel robust control algorithm based on an exponential-integral-sliding mode (EISMC) scheme and a RBF-NN approximator. The results revealed that the proposed algorithm is responsive and robust to withstand adverse effects of structured and unstructured uncertainties by using the designed adaptation law according to the Lyapunov stability theorem. TheHighlights: A novel path-planning and following algorithm is proposed for robots on deformable terrains. Exponential sliding mode reaching law is practiced for a smooth asymptotic stability of controller. CAPSO is adopted for multi-criteria path-planning and RBF-NN as a disturbance observer. Abstract: An immense body of research has focused on path-planning and following of wheeled robots in unstructured surfaces. Nonholonomic robots traveling over deformable terrains together with complex operating conditions, however, pose further challenges in terms of a higher demand for robustness and optimality. In this paper, a Chaos-enhanced Accelerated Particle Swarm Optimization (CAPSO) algorithm is employed for planning an optimal path of a wheeled robot, so as to ensure shortest path from the starting point to the target location together with safety through guaranteed avoidance of collisions with static and dynamic obstacles. The fundamental terramechanics concepts are employed to derive essential forces and moments acting on the wheeled robot. Subsequently, a kineto-dynamic model of the robot is developed for designing a novel robust control algorithm based on an exponential-integral-sliding mode (EISMC) scheme and a RBF-NN approximator. The results revealed that the proposed algorithm is responsive and robust to withstand adverse effects of structured and unstructured uncertainties by using the designed adaptation law according to the Lyapunov stability theorem. The effectiveness of the proposed algorithm is also validated against several reported frameworks. … (more)
- Is Part Of:
- Journal of terramechanics. Volume 96(2021)
- Journal:
- Journal of terramechanics
- Issue:
- Volume 96(2021)
- Issue Display:
- Volume 96, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 96
- Issue:
- 2021
- Issue Sort Value:
- 2021-0096-2021-0000
- Page Start:
- 147
- Page End:
- 157
- Publication Date:
- 2021-08
- Subjects:
- Terramechancis -- Path-planning -- PSO -- Terrain -- Artificial Intelligence
Trafficability -- Periodicals
Praticabilité (Routes) -- Périodiques
Trafficability
Periodicals
629.222 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00224898 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.jterra.2020.12.001 ↗
- Languages:
- English
- ISSNs:
- 0022-4898
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5069.030000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 17230.xml