This article presents a novel method for exactly reformulating nondifferentiable collision
avoidance constraints into smooth, differentiable constraints using strong duality of convex …

Real-time, guaranteed safe trajectory planning is vital for navigation in unknown
environments. However, real-time navigation algorithms typically sacrifice robustness for …

In this paper, we provide a novel robust collision avoidance approach that is based on a
general tube-based MPC framework. We consider collision avoidance for general nonlinear …

Optimization-based parking path planner has been attracting much more attention due to its
capability to generate the optimal path rather than a feasible one. But when solving this …

To deal with the problem of optimal path planning in 2D space, this paper introduces a new
toolbox named “Navigation with Polytopes” and explains the algorithms behind it. The …

Finding optimal paths for self-driving cars in cluttered environments is one of the major
challenges in autonomous driving. The complexity stems from the nonlinearity of the system …

Stochastic Model Predictive Control has proved to be an efficient method to plan trajectories
in uncertain environments, eg, for autonomous vehicles. Chance constraints ensure that the …

We are captivated by the promise of autonomous systems in our everyday life. However,
ensuring that these systems act safely is an immense challenge: introducing complex …

We present flight patterns for a collision-free passage of swarms of drones through one or
more openings. The narrow openings provide drones with access to an infrastructure …

In this article, we present a motion-planning framework that leverages expert bus driver
behavior, increasing the safety and maneuverability of autonomous buses. Autonomous …