Aleš Melichár

Dynamics-aware local trajectory control of a tracked vineyard robot via deep reinforcement learning

Autonomous navigation between narrow vineyard rows requires respecting the platform’s dynamics, which trajectory optimizers such as CHOMP and STOMP resolve in batch before motion and again whenever the map changes, so local navigation is cast as a continuous-control Markov decision process whose actions are the per-track torques of a skid-steer robot.