Fast Path Computation using Lattices in the Sensor-Space for Forest Navigation
Published in 2021 IEEE International Conference on Robotics and Automation (ICRA), 2021
Recommended citation: B. Martinez R. Junior and G. A. S. Pereira, "Fast Path Computation using Lattices in the Sensor-Space for Forest Navigation," 2021 IEEE International Conference on Robotics and Automation (ICRA), 2021, pp. 1117-1123, doi: 10.1109/ICRA48506.2021.9561241. https://ieeexplore.ieee.org/abstract/document/9561241
Abstract: Fast autonomous motion in cluttered and unknown environments, such as forests, is highly dependent on low-latency obstacle avoidance strategies. In this context, this paper presents a motion planning strategy that relies on lattices for the fast computation of local paths that both avoid obstacles and follow a vector field that encodes the global robot task. Lattices are constructed in the sensor space and represent a set of search trees that can be quickly pruned in function of the detected obstacles. The remaining lattice trees are used to optimize a vector field-dependent functional, thus generating the best free local path that tracks the field. To illustrate the proposed approach, we present simulation and real-world experiments of a planar robot moving in a cluttered, forest-like environment. Download paper here
Recommended citation: B. Martinez R. Junior and G. A. S. Pereira, “Fast Path Computation using Lattices in the Sensor-Space for Forest Navigation,” 2021 IEEE International Conference on Robotics and Automation (ICRA), 2021, pp. 1117-1123, doi: 10.1109/ICRA48506.2021.9561241.