A linear relaxation technique for the position analysis of multi-loop linkages

This report presents a new method able to isolate all configurations that a multi-loop linkage can adopt. We tackle the problem by providing formulation and resolution techniques that fit particularly well together. The adopted formulation yields a system of simple equations (only containing linear and bilinear terms, and trivial trigonometric functions for the helical pair exclusively) whose special structure is later exploited by a branch-and-prune method based on linear relaxations. The method is general, as it can be applied to linkages with single or multiple loops with arbitrary topology, involving lower pairs of any kind, and complete, as all possible solutions get accurately bounded, irrespectively of whether the linkage is rigid or mobile

Extensions of sampling-based approaches to path planning in complex cost spaces: applications to robotics and structural biology

Planning a path for a robot in a complex environment is a crucial issue in robotics. So-called probabilistic algorithms for path planning are very successful at solving difficult problems and are applied in various domains, such as aerospace, computer animation, and structural biology. However, these methods have traditionally focused on finding paths avoiding collisions, without considering the quality of these paths. In recent years, new approaches have been developed to generate high-quality paths: in robotics, this can mean finding paths maximizing safety or control; in biology, this means finding motions minimizing the energy variation of a molecule. In this thesis, we propose several extensions of these methods to improve their performance and allow them to solve ever more difficult problems. The applications we present stem from robotics (industrial inspection and aerial manipulation) and structural biology (simulation of molecular motions and exploration of energy landscapes)

Extensions of sampling-based approaches to path planning in complex cost spaces: applications to robotics and structural biology

Planifier le chemin d’un robot dans un environnement complexe est un problème crucial en robotique. Les méthodes de planification probabilistes peuvent résoudre des problèmes complexes aussi bien en robotique, qu’en animation graphique, ou en biologie structurale. En général, ces méthodes produisent un chemin évitant les collisions, sans considérer sa qualité. Récemment, de nouvelles approches ont été créées pour générer des chemins de bonne qualité : en robotique, cela peut être le chemin le plus court ou qui maximise la sécurité ; en biologie, il s’agit du mouvement minimisant la variation énergétique moléculaire. Dans cette thèse, nous proposons plusieurs extensions de ces méthodes, pour améliorer leurs performances et leur permettre de résoudre des problèmes toujours plus difficiles. Les applications que nous présentons viennent de la robotique (inspection industrielle et manipulation aérienne) et de la biologie structurale (mouvement moléculaire et conformations stables). ABSTRACT : Planning a path for a robot in a complex environment is a crucial issue in robotics. So-called probabilistic algorithms for path planning are very successful at solving difficult problems and are applied in various domains, such as aerospace, computer animation, and structural biology. However, these methods have traditionally focused on finding paths avoiding collisions, without considering the quality of these paths. In recent years, new approaches have been developed to generate high-quality paths: in robotics, this can mean finding paths maximizing safety or control; in biology, this means finding motions minimizing the energy variation of a molecule. In this thesis, we propose several extensions of these methods to improve their performance and allow them to solve ever more difficult problems. The applications we present stem from robotics (industrial inspection and aerial manipulation) and structural biology (simulation of molecular motions and exploration of energy landscapes)

Many Modes of Movement

The interesting array of articles for the special issue “Movement: Molecular to Robotic” (7 Apr., pp. 79-106) examines the biology of movement for animals with endoskeletons, animals with exoskeletons, robots, and molecules, but movement in an entire kingdom—the plant kingdom—is overlooked. Movement in plants is based on physical mechanisms that are very different from most animal movements, and movements have been a central factor in the evolution of many plant adaptations. Mechanisms include hydraulic shifts operating by means of osmotic engines, differential growth, fracturing of structures due to localized desiccation, and cell separations or dissolution leading to projectile actions