Trajectory Planning for a Knuckle Boom Crane Using Differential Dynamic Programming

Knuckle boom cranes are widely used in numerous applications, making effective obstacle avoidance trajectory planning critical for automation. However, the cranes’ inherent kinematic constraints pose significant challenges to designing and optimizing such trajectory planning problems. In this study, we develop a trajectory planning method that addresses obstacle avoidance under these kinematic constraints by employing Differential Dynamic Programming (DDP). We first derive an explicit Euler-based dynamic model of the crane, integrating Baumgarte stabilization to suppress kinematic constraint violations within the DDP framework. Additionally, a relaxed log-barrier function is introduced to handle both states and obstacle-avoidance constraints during trajectory planning. Comparative numerical simulations with the Ipopt solver demonstrate the effectiveness of the proposed approach in achieving obstacle avoidance and constraints suppression.     «

Knuckle boom cranes are widely used in numerous applications, making effective obstacle avoidance trajectory planning critical for automation. However, the cranes’ inherent kinematic constraints pose significant challenges to designing and optimizing such trajectory planning problems. In this study, we develop a trajectory planning method that addresses obstacle avoidance under these kinematic constraints by employing Differential Dynamic Programming (DDP). We first derive an explicit Euler-base...     »