Path planning and redundancy resolution of structure-climbing redundant robots
This thesis addresses critical challenges in the planning and control of biped structure-climbing redundant robots that navigate three-dimensional truss structures such as bridges, building skeletons, and power transmission towers. Maintenance tasks in these environments, traditionally performed by...
| Autor: | |
|---|---|
| Tipo de recurso: | tesis doctoral |
| Fecha de publicación: | 2026 |
| País: | España |
| Institución: | Universidad Miguel Hernández de Elche |
| Repositorio: | REDIUMH. Depósito Digital de la UMH |
| OAI Identifier: | oai:dnet:rediumh_____::ae852274ae7a6f89744836884de8594b |
| Acceso en línea: | https://hdl.handle.net/11000/39841 |
| Access Level: | acceso abierto |
| Palabra clave: | Self-motion manifolds Global redundancy resolution Redundant manipulators Motion planning Obstacle avoidance Path planning Climbing robots Redundant robots Truss structures Workspace CDU::6 - Ciencias aplicadas::68 - Industrias, oficios y comercio de artículos acabados. Tecnología cibernética y automática CDU::6 - Ciencias aplicadas::62 - Ingeniería. Tecnología::621 - Ingeniería mecánica en general. Tecnología nuclear. Electrotecnia. Maquinaria CDU::5 - Ciencias puras y naturales::51 - Matemáticas |
| Sumario: | This thesis addresses critical challenges in the planning and control of biped structure-climbing redundant robots that navigate three-dimensional truss structures such as bridges, building skeletons, and power transmission towers. Maintenance tasks in these environments, traditionally performed by human workers, present significant safety risks that can be mitigated through robotic solutions. Two fundamental challenges are addressed in the present thesis: path planning for structure navigation and redundancy resolution for optimal joint trajectory generation. First, we develop a hierarchical path planning algorithm that decomposes complex 3D exploration into manageable subproblems: a first planner determines the global path in the complete structure, while a second planner derives the local path in each visited face of the structure. This approach is generalizable, and efficiently handles transitions between structural faces while avoiding collisions. Second, we present three complementary approaches to redundancy resolution. The first method is based on Feasibility Maps (FMs), which provide a representation of the redundant-time space, on which we deploy an RRT-based algorithm to generate feasible joint trajectories while optimizing performance criteria. Building upon this, we extend the concept to Augmented Feasibility Maps (AFMs), which incorporates the task dimension into the redundancy resolution process, effectively tackling both the task-trajectory generation and redundancy resolution problems simultaneously. For the third approach, we developed a global redundancy resolution framework based on Self-Motion Manifolds (SMMs), which characterize the complete set of inverse kinematics solutions.We perform a spatial and topological analysis on the transformations of the SMMs throughout the task trajectory, and derive optimal joint trajectories from this analysis. All of these methods are able to incorpórate task constraints, such as joint limits and obstacle avoidance, into the redundancy resolution process. Finally, we introduce a novel homotopy-based method for computing SMMs that addresses limitations of existing approaches. This method effectively identifies all disjoint manifold components without requiring closed-form kinematic solutions, demonstrating superior performance compared to traditional continuation methods. The contributions are validated through extensive simulation tests, showing significant improvements over existing methods in terms of computational efficiency, path quality, and practical applicability. This research advances the state of the art in structure-climbing robotics and redundancy resolution, bringing these climbing robots closer to practical deployment in industrial inspection and maintenance applications. |
|---|