Corpus ID: 232076422

Geometrically Constrained Trajectory Optimization for Multicopters

  title={Geometrically Constrained Trajectory Optimization for Multicopters},
  author={Zhepei Wang and Xiaoxia Zhou and Chao Xu and Fei Gao},
We present an optimization-based framework for multicopter trajectory planning subject to geometrical spatial constraints and user-defined dynamic constraints. The basis of the framework is a novel trajectory representation built upon our novel optimality conditions for unconstrained control effort minimization. We design linear-complexity operations on this representation to conduct spatial-temporal deformation under various planning requirements. Smooth maps are utilized to exactly eliminate… Expand
Decentralized Spatial-Temporal Trajectory Planning for Multicopter Swarms
Decentralized spatial-temporal trajectory planning is introduced, which puts a well-formed trajectory representation named MINCO into multi-agent scenarios and ensures high-quality local planning for each agent subject to any constraint from either the coordination of the swarm or safety requirements in cluttered environments. Expand
FAST-Dynamic-Vision: Detection and Tracking Dynamic Objects with Event and Depth Sensing
This paper presents a complete perception system including ego-motion compensation, object detection, and trajectory prediction for fast-moving dynamic objects with low latency and high precision and proposes an optimizationbased approach that asynchronously fuses event and depth cameras for trajectory prediction. Expand
DIRECT: A Differential Dynamic Programming Based Framework for Trajectory Generation
  • Kun Cao, Muqing Cao, Shenghai Yuan, Lihua Xie
  • Computer Science, Mathematics
  • ArXiv
  • 2021
A differential dynamic programming (DDP) based framework for polynomial trajectory generation for differentially flat systems is introduced that takes a new perspective from state-space representation such that the linear equation reduces to a finite horizon control system with a fixed state dimension and the required continuity conditions for consecutive polynomials are automatically satisfied. Expand
Elastic Tracker: A Spatio-temporal Trajectory Planner Flexible Aerial Tracking
  • Jialin Ji, Neng Pan, Chao Xu, Fei Gao
  • Computer Science
  • ArXiv
  • 2021
This paper proposes Elastic Tracker, a flexible trajectory planning framework that can deal with challenging tracking tasks with guaranteed safety and visibility, and an occlusion-aware path finding method that works more robustly but with less computation than the existing methods. Expand
Robust Trajectory Planning for Spatial-Temporal Multi-Drone Coordination in Large Scenes
A robust multi-drone planning framework for high-speed trajectories in large scenes using a free-space-oriented map to free the optimization from cumbersome environment data and shows the minimum-singularity differential flatness of the drone dynamics with nonlinear drag effects involved. Expand
A Hybrid-Driven Optimization Framework for Fixed-Wing UAV Maneuvering Flight Planning
  • Renshan Zhang, Su Cao, Kuang Zhao, Huangchao Yu, Yongyang Hu
  • Electronics
  • 2021
Performing autonomous maneuvering flight planning and optimization remains a challenge for unmanned aerial vehicles (UAVs), especially for fixed-wing UAVs due to its high maneuverability and modelExpand
Distributed Swarm Trajectory Optimization for Formation Flight in Dense Environments
  • Lun Quan, Longji Yin, Chao Xu, Fei Gao
  • Computer Science
  • ArXiv
  • 2021
An optimization-based method is presented that ensures collision-free trajectory generation for formation flight and achieves spatial-temporal planning using polynomial trajectories, and is integrated with an autonomous distributed aerial swarm system. Expand
Fast-Racing: An Open-source Strong Baseline for SE(3) Planning in Autonomous Drone Racing
An open-source baseline is proposed, which includes a high-performance SE(3) planner and a challenging simulation platform tailored for drone racing, and develops delicate drone racing tracks which mimic real-world set-up and necessities planning in SE( 3). Expand
GPA-Teleoperation: Gaze Enhanced Perception-aware Safe Assistive Aerial Teleoperation
This paper presents GPA-Teleoperation, a gaze enhanced perception-aware assistive teleoperation framework, which addresses the above issues systematically and refined the path into a safe and feasible trajectory which simultaneously enhances the perception awareness to the environment operators are interested in. Expand
Robust Multi-Robot Trajectory Generation Using Alternating Direction Method of Multiplier
This work proposes a variant of alternating direction method of multiplier (ADMM) to solve constrained trajectory optimization problems, and inherits the theoretical properties of primal interior point method (P-IPM), i.e., guaranteed collision avoidance and homotopy preservation, while being orders of magnitude faster. Expand


Planning Dynamically Feasible Trajectories for Quadrotors Using Safe Flight Corridors in 3-D Complex Environments
This work proposes a method to formulate trajectory generation as a quadratic program (QP) using the concept of a Safe Flight Corridor (SFC), a collection of convex overlapping polyhedra that models free space and provides a connected path from the robot to the goal position. Expand
Multi-Fidelity Black-Box Optimization for Time-Optimal Quadrotor Maneuvers
A multi-fidelity Bayesian optimization framework that models the feasibility constraints based on analytical approximation, numerical simulation, and real-world flight experiments is proposed and resulting trajectories were found to be significantly faster than those obtained through minimum-snap trajectory planning. Expand
Search-based motion planning for quadrotors using linear quadratic minimum time control
A search-based planning method to compute dynamically feasible trajectories for a quadrotor flying in an obstacle-cluttered environment that does not assume a hovering initial condition and is suitable for fast online re-planning while the robot is moving. Expand
Motion planning with sequential convex optimization and convex collision checking
A sequential convex optimization procedure, which penalizes collisions with a hinge loss and increases the penalty coefficients in an outer loop as necessary, and an efficient formulation of the no-collisions constraint that directly considers continuous-time safety are presented. Expand
Efficient mixed-integer planning for UAVs in cluttered environments
  • R. Deits, Russ Tedrake
  • Mathematics, Computer Science
  • 2015 IEEE International Conference on Robotics and Automation (ICRA)
  • 2015
A new approach to the design of smooth trajectories for quadrotor unmanned aerial vehicles (UAVs), which are free of collisions with obstacles along their entire length is presented, using IRIS, a recently developed technique for greedy convex segmentation, to pre-compute convex regions of safe space. Expand
CHOMP: Covariant Hamiltonian optimization for motion planning
In this paper, we present CHOMP (covariant Hamiltonian optimization for motion planning), a method for trajectory optimization invariant to reparametrization. CHOMP uses functional gradientExpand
STOMP: Stochastic trajectory optimization for motion planning
It is experimentally show that the stochastic nature of STOMP allows it to overcome local minima that gradient-based methods like CHOMP can get stuck in. Expand
Aggressive flight of fixed-wing and quadrotor aircraft in dense indoor environments
This paper builds on previous work to show how a search process can be coupled with optimization in the output space of a differentially flat vehicle model to find aggressive trajectories that utilize the full maneuvering capabilities of a quadrotor and presents a novel trajectory representation called a “Dubins–Polynomial trajectory”, which allows us to optimize trajectories for fixed-wing vehicles. Expand
FASTER: Fast and Safe Trajectory Planner for Flights in Unknown Environments
FASTER (Fast and Safe Trajectory Planner) obtains high-speed trajectories by enabling the local planner to optimize in both the free-known and unknown spaces by way of a Mixed Integer Quadratic Program formulation. Expand
Fast UAV Trajectory Optimization using Bilevel Optimization with Analytical Gradients
We present an efficient optimization framework that solves trajectory optimization problems by decoupling state variables from timing variables, thereby decomposing a challenging nonlinearExpand