Collision-free state estimation

In state estimation, we often want the maximum likelihood estimate of the current state. For the commonly used joint multivariate Gaussian distribution over the state space, this can be efficiently found using a Kalman filter. However, in complex environments the state space is often highly constrained. For example, for objects within a refrigerator, they cannot interpenetrate each other or the refrigerator walls. The multivariate Gaussian is unconstrained over the state space and cannot incorporate these constraints. In particular, the state estimate returned by the unconstrained distribution may itself be infeasible. Instead, we solve a related constrained optimization problem to find a good feasible state estimate. We illustrate this for estimating collision-free configurations for objects resting stably on a 2-D surface, and demonstrate its utility in a real robot perception domain.National Science Foundation (U.S.) (Grant 019868)United States. Office of Naval Research. Multidisciplinary University Research Initiative (Grant N00014-09-1-1051)United States. Air Force Office of Scientific Research (Grant AOARD-104135

Cooperative Collision Avoidance at Intersections: Algorithms and Experiments

In this paper, we leverage vehicle-to-vehicle (V2V) communication technology to implement computationally efficient decentralized algorithms for two-vehicle cooperative collision avoidance at intersections. Our algorithms employ formal control theoretic methods to guarantee a collision-free (safe) system, whereas overrides are only applied when necessary to prevent a crash. Model uncertainty and communication delays are explicitly accounted for by the model and by the state estimation algorithm. The main contribution of this work is to provide an experimental validation of our method on two instrumented vehicles engaged in an intersection collision avoidance scenario in a test track

Estimation for decentralized safety control under communication delay and measurement uncertainty

International audienceThis paper addresses the design of a decentralized safety controller for two agents, subject to communication delay and imperfect measurements. The control objective is to ensure safety, meaning that the state of the two-agent system does not enter an undesired set in the state space. Assuming that we know a feedback map designed for the delay free-case, we propose a state estimation strategy which guarantees control agreement between the two agents. We present an estimation technique for bounded communication delays, assuming that the agents share the same internal clock, and extend it for infinitely-distributed communication delays by determining a lower bound for the probability of safety. We also explain how the proposed approach can be extended to a general system of N agents and discuss efficient computation of our estimation strategy. Performance of the controller and relevance of the proposed approach are discussed in light of simulations performed for a collision avoidance problem between two semi-autonomous vehicles at an intersection

Estimation for decentralized safety control under communication delay and measurement uncertainty

This paper addresses the design of a decentralized safety controller for two agents, subject to communication delay and imperfect measurements. The control objective is to ensure safety, meaning that the state of the two-agent system does not enter an undesired set in the state space. Assuming that we know a feedback map designed for the delay free-case, we propose a state estimation strategy which guarantees control agreement between the two agents. We present an estimation technique for bounded communication delays, assuming that the agents share the same internal clock, and extend it for infinitely-distributed communication delays by determining a lower bound for the probability of safety. We also explain how the proposed approach can be extended to a general system of N agents and discuss efficient computation of our estimation strategy. Performance of the controller and relevance of the proposed approach are discussed in light of simulations performed for a collision avoidance problem between two semi-autonomous vehicles at an intersection. Keywords: Multi-agent systems; Communication delay; Estimation/prediction approaches; Safety contro

Performance Evaluation of Vision-Based Algorithms for MAVs

An important focus of current research in the field of Micro Aerial Vehicles (MAVs) is to increase the safety of their operation in general unstructured environments. Especially indoors, where GPS cannot be used for localization, reliable algorithms for localization and mapping of the environment are necessary in order to keep an MAV airborne safely. In this paper, we compare vision-based real-time capable methods for localization and mapping and point out their strengths and weaknesses. Additionally, we describe algorithms for state estimation, control and navigation, which use the localization and mapping results of our vision-based algorithms as input.Comment: Presented at OAGM Workshop, 2015 (arXiv:1505.01065