MPC-Graph: Feedback motion planning using sparse sampling based neighborhood graph

© 2020 IEEE.Robust and safe feedback motion planning and navigation is a critical task for autonomous mobile robotic systems considering the highly dynamic and uncertain nature scenarios of modern applications. For these reasons motion planning and navigation algorithms that have deep roots in feedback control theory has been at the center stage of this domain recently. However, the vast majority of such policies still rely on the idea that a motion planner first generates a set of open-loop possibly time-dependent trajectories, and then a set of feedback control policies track these trajectories in closed-loop while providing some error bounds and guarantees around these trajectories. In contrast to trajectory-based approaches, some researchers developed feedback motion planning strategies based on connected obstacle-free regions, where the task of the local control policies is to drive the robot(s) in between these particular connected regions. In this paper, we propose a feedback motion planning algorithm based on sparse random neighborhood graphs and constrained nonlinear Model Predictive Control (MPC). The algorithm first generates a sparse neighborhood graph as a set of connected simple rectangular regions. After that, during navigation, an MPC based online feedback control policy funnels the robot with nonlinear dynamics from one rectangle to the other in the network, ensuring no constraint violation on state and input variables occurs with guaranteed stability. In this framework, we can drive the robot to any goal location provided that the connected region network covers both the initial condition and the goal position. We demonstrate the effectiveness and validity of the algorithm on simulation studies

Trajectory-Free Motion Planning of an Unmanned Surface Vehicle Based on MPC and Sparse Neighborhood Graph

Unmanned Surface Vehicles (USV) have gained significant attention in military, science, and research applications in recent years. The development of new USV systems and increased application domain of these platforms has necessitated the development of new motion planning methods to improve the autonomy level of USVs and provide safe and robust navigation across unpredictable marine environments. This study proposes a feedback motion planning and control methodology for dynamic fully-and under-actuated USV models built on the recently introduced sparse random neighborhood graphs and constrained nonlinear Model Predictive Control (MPC). This approach employs a feedback motion planning strategy based on sparsely connected obstacle-free regions and the sequential composition of MPC policies. The algorithm generates a sparse neighborhood graph consisting of connected rectangular zones in the discrete planning phase. Inside each node (rectangular region), an MPC-based online feedback control policy funnels the USV with nonlinear dynamics from one rectangle to the other in the network, ensuring no constraint violation on state and input variables occurs. We systematically test the proposed algorithms in different simulation scenarios, including an extreme actuator noise scenario, to test the algorithm’s validity, effectiveness, and robustness

Diagnosis and management of vaginal mullerian cyst in a virgin patient

WOS: 000254751000023PubMed: 18008018Benign cystic lesions of the vagina are uncommon and may become symptomatic. We describe two symptomatic anterior vaginal wall cysts in a virgin patient and the usefulness of imaging modalities. A 36-year-old virgin woman presented with a complaint of vaginal bulging and pelvic pressure. Pelvic examination revealed a cystic mass protruding from the vagina surrounded by the intact hymen. The initial abdominopelvic ultrasound showed a hypoechoic cystic mass measuring 42 x 20 mm in the vagina. She then had a pelvic magnetic resonance imaging (MRI) that revealed two anterior vaginal wall cysts with no communication with the urethra or bladder. The cysts were excised and histologic examination with mucicarmine revealed mucin-secreting tall columnar cells consistent with a diagnosis of mullerian cyst. While both ultrasonographic examination and MRI are helpful in localizing vaginal cysts, MRI is superior in showing multiple cystic lesions of the vagina and their communication with the surrounding structures