Optimized and trusted collision avoidance for unmanned aerial vehicles using approximate dynamic programming

Abstract

Safely integrating unmanned aerial vehicles into civil airspace is contingent upon development of a trustworthy collision avoidance system. This paper proposes an approach whereby a parameterized resolution logic that is considered trusted for a given range of its parameters is adaptively tuned online. Specifically, to address the potential conservatism of the resolution logic with static parameters, we present a dynamic programming approach for adapting the parameters dynamically based on the encounter state. We compute the adaptation policy offline using a simulation-based approximate dynamic programming method that accommodates the high dimensionality of the problem. Numerical experiments show that this approach improves safety and operational performance compared to the baseline resolution logic, while retaining trustworthiness.

Efficiency and Safety in Autonomous Vehicles Through Planning With Uncertainty

“…The thesis will also include an investigation of the tradeoff between trustworthiness and performance in the context of aerial collision avoidance (Sunberg, Kochenderfer, and Pavone 2017). Some approaches to aerial collision avoidance consist of a set of rules that can be verified or analytically proven to prevent collision given constraints on the behavior of other aircraft.…”

Hold Or take Optimal Plan (HOOP): A quadratic programming approach to multi-robot trajectory generation

“…Probabilistic approaches extend single-robot planners, such as RRT* (Cap et al, 2013) and Roadmaps (Peasgood et al, 2008), to multi-robot planning. Optimization-based approaches have also been applied to aerial robots for collision avoidance between vehicles (Alonso–Mora et al, 2015; Pallottino et al, 2002; Sunberg et al, 2016), as well as for formation control in general (Mellinger et al, 2012).…”

Decentralized motion planning with collision avoidance for a team of UAVs under high level goals

“…In the case of aerial vehicles, tasks involving area coverage/inspection or rescue missions point out the importance of using multi-agent setups. The standard problem of formation control for a team of aerial vehicles is addressed in [1]- [6], whereas [7]- [11] consider leader-follower formation approaches, where the latter also treats the problem of collision avoidance with static obstacles in the environment; [12], [13] and [14] employ dynamic programming, Model Predictive Control and reachable set algorithms, respectively, for interagent collision avoidance. In [15] the cooperative evader pursuit problem is treated.…”