This paper presents a novel method for using volumetric information in the C-space for generating collision-free paths for robotic manipulators in the presence of obstacles. The method is based on the RRT paradigm, i.e., incrementally building trees in C-space in order to connect the initial configuration to the final one. Bubbles of free C-space are used within a carefully modified extend procedure to add lengthy edges to the tree. In particular, we propose an expanded version of the bubble, which enables even more efficient exploration. The method is validated and compared to other planning algorithms within a simulation study that includes several types of manipulators and obstacle scenarios.

This paper presents a new approach to C-space exploration and path planning for robotic manipulators using the structure named bur of free C-space. This structure builds upon the so-called bubble, which is a local volume of free C-space, easily computed using the distance information in the workspace. We show how the same distance information can be used to compute the bur that can reach substantially beyond the boundary of the bubble. It is shown how burs can be used to form a rapidly exploring bur tree (RBT): a space-filling tree that resembles RRT. Such a structure can easily be used within a suitably tailored path planning algorithm. Simulation study shows how the RBT-based algorithm outperforms the classical RRT-based method.