[go: up one dir, main page]

Gray et al., 2012 - Google Patents

Predictive control for agile semi-autonomous ground vehicles using motion primitives

Gray et al., 2012

View PDF
Document ID
14831702826426836336
Author
Gray A
Gao Y
Lin T
Hedrick J
Tseng H
Borrelli F
Publication year
Publication venue
2012 American Control Conference (ACC)

External Links

Snippet

This paper presents a hierarchical control framework for the obstacle avoidance of autonomous and semi-autonomous ground vehicles. The high-level planner is based on motion primitives created from a four-wheel nonlinear dynamic model. Parameterized …
Continue reading at scholar.archive.org (PDF) (other versions)

Classifications

    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/02Control of position or course in two dimensions
    • G05D1/021Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0287Control of position or course in two dimensions specially adapted to land vehicles involving a plurality of land vehicles, e.g. fleet or convoy travelling
    • G05D1/0291Fleet control
    • G05D1/0295Fleet control by at least one leading vehicle of the fleet
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/02Control of position or course in two dimensions
    • G05D1/021Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0276Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
    • G05D1/0278Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle using satellite positioning signals, e.g. GPS
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/02Control of position or course in two dimensions
    • G05D1/021Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0212Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory

Similar Documents

Publication Publication Date Title
Gray et al. Predictive control for agile semi-autonomous ground vehicles using motion primitives
Brown et al. Coordinating tire forces to avoid obstacles using nonlinear model predictive control
Wischnewski et al. A tube-MPC approach to autonomous multi-vehicle racing on high-speed ovals
Carvalho et al. Predictive control of an autonomous ground vehicle using an iterative linearization approach
Zhang et al. Trajectory planning and tracking for autonomous vehicle based on state lattice and model predictive control
Liang et al. A novel combined decision and control scheme for autonomous vehicle in structured road based on adaptive model predictive control
Gao Model predictive control for autonomous and semiautonomous vehicles
Wu et al. Route planning and tracking control of an intelligent automatic unmanned transportation system based on dynamic nonlinear model predictive control
Rasekhipour et al. A potential field-based model predictive path-planning controller for autonomous road vehicles
Ritschel et al. Nonlinear model predictive path-following control for highly automated driving
Buyval et al. Deriving overtaking strategy from nonlinear model predictive control for a race car
Gao et al. Robust nonlinear predictive control for semiautonomous ground vehicles
Yuan et al. Mixed local motion planning and tracking control framework for autonomous vehicles based on model predictive control
Minh et al. Feasible path planning for autonomous vehicles
Li et al. Combining local trajectory planning and tracking control for autonomous ground vehicles navigating along a reference path
Ajanović et al. Search-based task and motion planning for hybrid systems: Agile autonomous vehicles
Yu et al. Formally robust and safe trajectory planning and tracking for autonomous vehicles
Franco et al. Short-term path planning with multiple moving obstacle avoidance based on adaptive MPC
Chen et al. Fast trajectory planning and robust trajectory tracking for pedestrian avoidance
Gong et al. Game theory-based decision-making and iterative predictive lateral control for cooperative obstacle avoidance of guided vehicle platoon
Pagot et al. Fast planning and tracking of complex autonomous parking maneuvers with optimal control and pseudo-neural networks
Viana et al. Distributed cooperative path-planning for autonomous vehicles integrating human driver trajectories
Guirguis et al. Path tracking control based on an adaptive MPC to changing vehicle dynamics
Ajanovic et al. Search-based motion planning for performance autonomous driving
Ko et al. Integrated path planning and tracking control of autonomous vehicle for collision avoidance based on model predictive control and potential field