Reactive sampling-based path planning with temporal logic specifications

Vasile, Cristian-Ioan; Li, Xiao; Belta, Călin

doi:10.1177/0278364920918919

“…STyLuS * [20] is a scalable algorithm for multi-agent optimal control with temporal logics. [21] utilizes RRT to plan paths for long-term LTL goals with short-term reactive specifications. In [22], the authors propose the Spatio-temporal RRT* algorithm which can handle STL specifications containing only "always" operators.…”

Section: A Related Workmentioning

confidence: 99%

Multi-Agent Motion Planning From Signal Temporal Logic Specifications

Sun

¹

,

Chen

²

,

Mitra

³

et al. 2022

IEEE Robot. Autom. Lett.

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We tackle the challenging problem of multi-agent cooperative motion planning for complex tasks described using signal temporal logic (STL), where robots can have nonlinear and nonholonomic dynamics. Existing methods in multi-agent motion planning, especially those based on discrete abstractions and model predictive control (MPC), suffer from limited scalability with respect to the complexity of the task, the size of the workspace, and the planning horizon. We present a method based on timed waypoints to address this issue. We show that timed waypoints can help abstract nonlinear behaviors of the system as safety envelopes around the reference path defined by those waypoints. Then the search for waypoints satisfying the STL specifications can be inductively encoded as a mixedinteger linear program. The agents following the synthesized timed waypoints have their tasks automatically allocated, and are guaranteed to satisfy the STL specifications while avoiding collisions. We evaluate the algorithm on a wide variety of benchmarks. Results show that it supports multi-agent planning from complex specification over long planning horizons, and significantly outperforms state-of-the-art abstraction-based and MPC-based motion planning methods. The implementation is available at https://github.com/sundw2014/STLPlanning.

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“…STyLuS * [20] is a scalable algorithm for multiagent optimal control with temporal logics. [21] utilizes RRT to plan paths for long-term LTL goals with short-term reactive specifications. In [22], the authors proposes the spatiotemporal RRT* algorithm which can handle STL specifications containing only "always" operators.…”

Section: A Related Workmentioning

confidence: 99%

Multi-agent Motion Planning from Signal Temporal Logic Specifications

Sun¹,

Chen²,

Mitra³

et al. 2022

Preprint

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We tackle the challenging problem of multi-agent cooperative motion planning for complex tasks described using signal temporal logic (STL), where robots can have nonlinear and nonholonomic dynamics. Existing methods in multi-agent motion planning, especially those based on discrete abstractions and model predictive control (MPC), suffer from limited scalability with respect to the complexity of the task, the size of the workspace, and the planning horizon. We present a method based on timed waypoints to address this issue. We show that timed waypoints can help abstract nonlinear behaviors of the system as safety envelopes around the reference path defined by those waypoints. Then the search for waypoints satisfying the STL specifications can be inductively encoded as a mixedinteger linear program. The agents following the synthesized timed waypoints have their tasks automatically allocated, and are guaranteed to satisfy the STL specifications while avoiding collisions. We evaluate the algorithm on a wide variety of benchmarks. Results show that it supports multi-agent planning from complex specification over long planning horizons, and significantly outperforms state-of-the-art abstraction-based and MPC-based motion planning methods. The implementation is available at https://github.com/sundw2014/STLPlanning.

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“…Rapidly exploring Random Tree (RRT), shown in [ 10 ], is widely used because RRT may efficiently find feasible paths in high dimensional spaces with low computational cost as shown in [ 11 , 12 , 13 ]. Recently, RRT solutions in high dimensional spaces, such as temporal logic specifications, were proposed in [ 14 ].…”

Section: Introductionmentioning

confidence: 99%

Trajectory Planner CDT-RRT* for Car-Like Mobile Robots toward Narrow and Cluttered Environments

Kwon

¹

,

Cha

²

,

Seong

³

et al. 2021

Sensors

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In order to achieve the safe and efficient navigation of mobile robots, it is essential to consider both the environmental geometry and kinodynamic constraints of robots. We propose a trajectory planner for car-like robots on the basis of the Dual-Tree RRT (DT-RRT). DT-RRT utilizes two tree structures in order to generate fast-growing trajectories under the kinodynamic constraints of robots. A local trajectory generator has been newly designed for car-like robots. The proposed scheme of searching a parent node enables the efficient generation of safe trajectories in cluttered environments. The presented simulation results clearly show the usefulness and the advantage of the proposed trajectory planner in various environments.

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Reactive sampling-based path planning with temporal logic specifications

Cited by 39 publications

References 71 publications

Multi-Agent Motion Planning From Signal Temporal Logic Specifications

Multi-Agent Motion Planning From Signal Temporal Logic Specifications

Multi-agent Motion Planning from Signal Temporal Logic Specifications

Trajectory Planner CDT-RRT* for Car-Like Mobile Robots toward Narrow and Cluttered Environments

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