DeepAI AI Chat
Log In Sign Up

Toward Verifiable Real-Time Obstacle Motion Prediction for Dynamic Collision Avoidance

by   Vincent Kurtz, et al.

Next generation Unmanned Aerial Vehicles (UAVs) must reliably avoid moving obstacles. Existing dynamic collision avoidance methods are effective where obstacle trajectories are linear or known, but such restrictions are not accurate to many real-world UAV applications. We propose an efficient method of predicting an obstacle's motion based only on recent observations, via online training of an LSTM neural network. Given such predictions, we define a Nonlinear Probabilistic Velocity Obstacle (NPVO), which can be used select a velocity that is collision free with a given probability. We take a step towards formal verification of our approach, using statistical model checking to approximate the probability that our system will mispredict an obstacle's motion. Given such a probability, we prove upper bounds on the probability of collision in multi-agent and reciprocal collision avoidance scenarios. Furthermore, we demonstrate in simulation that our method avoids collisions where state-of-the-art methods fail.


page 1

page 2

page 3

page 4


Probabilistic Collision Constraint for Motion Planning in Dynamic Environments

Online generation of collision free trajectories is of prime importance ...

IVO: Inverse Velocity Obstacles for Real Time Navigation

In this paper, we present "IVO: Inverse Velocity Obstacles" an ego-centr...

Intent-Aware Probabilistic Trajectory Estimation for Collision Prediction with Uncertainty Quantification

Collision prediction in a dynamic and unknown environment relies on know...

Learning Probabilistic Trajectory Models of Aircraft in Terminal Airspace from Position Data

Models for predicting aircraft motion are an important component of mode...

Future Near-Collision Prediction from Monocular Video: Feasibility, Dataset, and Challenges

We explore the possibility of using a single monocular camera to forecas...

Utilizing the RRT*-Algorithm for Collision Avoidance in UAV Photogrammetry Missions

This paper presents the application of the Rapidly-exploring Random Tree...

Conservative collision prediction and avoidance for stochastic trajectories in continuous time and space

Existing work in multi-agent collision prediction and avoidance typicall...