Cartesian-Space Motion Planning for Autonomous Construction Machines

Matteo Ragaglia, Alfredo Argiolas, Marta Niccolini
2017 Proceedings of the 34th International Symposium on Automation and Robotics in Construction (ISARC)   unpublished
Nowadays, the construction industry is probably the least productive and most dangerous among the various industry sectors. Given this scenario, it is quite clear that the introduction of Autonomous Construction Machines (ACMs) could represent a great opportunity to improve both productivity and safety. To this purpose, a fundamental problem that has to be tackled is trajectory planning. In the last 15 years, several sample-based algorithms have been proposed, that relies on Joint-Space
more » ... Joint-Space sampling. Unfortunately, this feature often results in trajectories that are quite counterintuitive from the point of view of a human being. In this work we propose "cart-RRT", a Cartesian-Space randomized algorithm that improves the intuitiveness of the output trajectory, while ensuring both its safety (in terms of collision avoidance) and its feasibility.
doi:10.22260/isarc2017/0136 fatcat:zjv3uexjhzeujk4l66cngfvx4m