Robust Trajectory Planning for a Multirotor against Disturbance based on Hamilton-Jacobi Reachability Analysis

Seo, Ho Seong; Lee, Donggun; Son, Clark Youngdong; Tomlin, Claire J.; Kim, H. Jin

doi:10.1109/iros40897.2019.8968126

Cited by 33 publications

(25 citation statements)

References 23 publications

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“…al [18] learns a tracking error function offline to conservatively approximate reachable set at runtime, with hardware implementation and time-varying uncertainties as future work. Most similar to our problem space, [19] approximates in real-time the reachable set given current disturbance, while our work precomputes margins for faster adaptation.…”

Section: Related Workmentioning

confidence: 99%

Adaptive Safety Margin Estimation for Safe Real-Time Replanning under Time-Varying Disturbance

Ho,

Patrikar,

Bonatti

et al. 2021

Preprint

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Safe navigation in real time is challenging because engineers need to work with uncertain vehicle dynamics, variable external disturbances, and imperfect controllers. A common safety strategy is to inflate obstacles by hand-defined margins. However, arbitrary static margins often fail in more dynamic scenarios, and using worst-case assumptions is overly conservative for most settings where disturbances over time. In this work, we propose a middle ground: safety margins that adapt on-the-fly. In an offline phase, we use Monte Carlo simulations to pre-compute a library of safety margins for multiple levels of disturbance uncertainties. Then, at runtime, our system estimates the current disturbance level to query the associated safety margins that best trades off safety and performance. We validate our approach with extensive simulated and real-world flight tests. We show that our adaptive method significantly outperforms static margins, allowing the vehicle to operate up to 1.5 times faster than worstcase static margins while maintaining safety. Video: https://youtu.be/SHzKHSUjdUU

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Section: Related Workmentioning

confidence: 99%

Adaptive Safety Margin Estimation for Safe Real-Time Replanning under Time-Varying Disturbance

Ho,

Patrikar,

Bonatti

et al. 2021

Preprint

View full text Add to dashboard Cite

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“…Similarly, the HJ reachability analysis also suffers from the curse of dimensionality, which also requires long computation when the dimension increases. The approximation of reachable sets using ellipsoids is a technique to significantly reduce the computation burden [19] and can be adopted for motion planning [8]. Nevertheless, most of the previous works only consider the disturbances with a constant bound, which differs from the the real world scenarios.…”

Section: Related Work Proximity Effects Between Rotor-crafts and Obst...mentioning

confidence: 99%

“…With the estimated disturbance, the HJ-reachability problem is formulated for analyzing the control error bound. The resulting reachable sets of the errors are approximated using ellipsoids for higher computational efficiency [19] [8], so as to facilitate the safe motion planning mentioned in the following section.…”

Section: Control Error Bound Calculationmentioning

confidence: 99%

Estimation and Adaption of Indoor Ego Airflow Disturbance with Application to Quadrotor Trajectory Planning

Zhou¹,

Liu²,

Shen³

2021

Preprint

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It is ubiquitously accepted that during the autonomous navigation of the quadrotors, one of the most widely adopted unmanned aerial vehicles (UAVs), safety always has the highest priority. However, it is observed that the ego airflow disturbance can be a significant adverse factor during flights, causing potential safety issues, especially in narrow and confined indoor environments. Therefore, we propose a novel method to estimate and adapt indoor ego airflow disturbance of quadrotors, meanwhile applying it to trajectory planning. Firstly, the hover experiments for different quadrotors are conducted against the proximity effects. Then with the collected acceleration variance, the disturbances are modeled for the quadrotors according to the proposed formulation. The disturbance model is also verified under hover conditions in different reconstructed complex environments. Furthermore, the approximation of Hamilton-Jacobi reachability analysis is performed according to the estimated disturbances to facilitate the safe trajectory planning, which consists of kinodynamic path search as well as B-spline trajectory optimization. The whole planning framework is validated on multiple quadrotor platforms in different indoor environments.

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“…8. As the Pixhawk autopilot only accepts position or velocity control commands, we generated the rate command of the position/attitude of the quadrotor the using disturbance observer presented in [31].…”

Section: B Flight Experimentsmentioning

confidence: 99%

Trajectory Optimization and Replanning Framework for a Micro Air Vehicle in Cluttered Environments

2020

Self Cite

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In the present study, we propose a trajectory optimization and replanning algorithm for micro air vehicles (MAVs) in cluttered environments. To generate the path of an MAV in a cluttered environment, we first design an offline global path optimization algorithm. This algorithm generates a global trajectory for safe aerial delivery; this trajectory enables an MAV to avoid static obstacles marked in the navigation map and satisfies the MAV's initial and arrival velocities. The MAV's trajectory is replanned by exploiting dynamic movement primitives (DMPs) and a time adjustment algorithm to enable computationally efficient unknown obstacle avoidance in local path planning. To validate the applicability of the proposed algorithm, we compare simulation results with those obtained using an existing approach based on DMPs. Furthermore, an autonomous flight is demonstrated in an outdoor environment using a custom-made MAV driven by the proposed approach.

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Robust Trajectory Planning for a Multirotor against Disturbance based on Hamilton-Jacobi Reachability Analysis

Cited by 33 publications

References 23 publications

Adaptive Safety Margin Estimation for Safe Real-Time Replanning under Time-Varying Disturbance

Adaptive Safety Margin Estimation for Safe Real-Time Replanning under Time-Varying Disturbance

Estimation and Adaption of Indoor Ego Airflow Disturbance with Application to Quadrotor Trajectory Planning

Trajectory Optimization and Replanning Framework for a Micro Air Vehicle in Cluttered Environments

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