A sensor guided autonomous parking system for nonholonomic mobile robots

Jiang, Kaiwen; Seneviratne, Lakmal

doi:10.1109/robot.1999.769997

Cited by 63 publications

(29 citation statements)

References 8 publications

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“…Either image sensors or ultrasonic sensors can be used for the task [6,12,13,24]. For examples, by using one or two digital cameras, the image around the vehicle can be acquired in real time, and then an image processing algorithm can be employed to identify the parking space.…”

Section: Parking Space Detectionmentioning

confidence: 99%

“…Reference [12] studied parallel parking in tight situations by path planning for a front-wheel steering vehicle. The minimum length of the parking space used was 100 cm with a vehicle length of 60 cm.…”

Section: Size Of the Parking Spacementioning

confidence: 99%

“…Jiang and Seneviratne [12] also studied sensor guided autonomous parking, where the process consists of three phases: scanning, positioning and maneuvering. The path in the maneuvering phase is constructed by two circular arcs of minimum radius tangentially linked to each other.…”

Section: Introductionmentioning

confidence: 99%

“…In the category of path planning approaches references [13,19,20] also do not discuss the size of the parking space. In this category the smallest parking space used in reference [12] is 1.67 times the length of the vehicle. To improve the maneuverability and capability of AGVs, the focus of this research is to develop simple fuzzy controllers that can reverse vehicles into tight spaces and to demonstrate the resulting parking algorithm experimentally using the ATRV-Jr mobile robot shown in Figure 1.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Robust automatic parallel parking in tight spaces via fuzzy logic

Zhao

Collins

2005

Robotics and Autonomous Systems

112

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This paper develops and experimentally demonstrates a robust automatic parallel parking algorithm for parking in tight spaces. Novel fuzzy logic controllers are designed for each step of the maneuvering process. The controllers are first demonstrated by simulation using the kinematic model of a skid steering autonomous ground vehicle (AGV). They are then demonstrated experimentally on a skid steering AGV and it is shown that the developed algorithm has the ability to parallel park AGVs in tight spaces under both vehicle localization errors and parking space detection errors. This paper also presents a genetic fuzzy system which uses a genetic algorithm's learning ability to determine effective parameters for the developed fuzzy logic controllers. The genetic fuzzy system is used to tune the fuzzy logic algorithm for both a skid steering AGV and a front-wheel steering AGV.

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Section: Parking Space Detectionmentioning

confidence: 99%

Section: Size Of the Parking Spacementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Robust automatic parallel parking in tight spaces via fuzzy logic

Zhao

Collins

2005

Robotics and Autonomous Systems

112

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“…References [5]- [9] make use of distance sensors, mounted on the wheels, as feedback signals to the vehicle to perform the task. Currently there are two different approaches adapted by investigators, the path planning approach [5] and skill based approaches [6]- [8].…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Logic Based Autonomous Parallel Parking System with Kalman Filtering

Panomruttanarug

Higuchi

2010

SICE Journal of Control, Measurement, and System Integration

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: This paper presents an emulation of fuzzy logic control schemes for an autonomous parallel parking system in a backward maneuver. There are four infrared sensors sending the distance data to a microcontroller for generating an obstacle-free parking path. Two of them mounted on the front and rear wheels on the parking side are used as the inputs to the fuzzy rules to calculate a proper steering angle while backing. The other two attached to the front and rear ends serve for avoiding collision with other cars along the parking space. At the end of parking processes, the vehicle will be in line with other parked cars and positioned in the middle of the free space. Fuzzy rules are designed based upon a wall following process. Performance of the infrared sensors is improved using Kalman filtering. The design method needs extra information from ultrasonic sensors. Starting from modeling the ultrasonic sensor in 1-D state space forms, one makes use of the infrared sensor as a measurement to update the predicted values. Experimental results demonstrate the effectiveness of sensor improvement.

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Nonlinear path following control of non‐holonomic vehicles with the human as actuator in a parking application

Kochem¹,

Isermann²

2004

Intl J Robust & Nonlinear

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SUMMARYThis paper describes and compares several controllers for precision tracking control of non-holonomic vehicles at low speeds with the driver as actuator in the control loop. A possible application for the developed controllers is a driver assistance system for supporting the driver in a backward parking procedure. The system, designed as a comfort feature, provides the driver with optical and acoustical information through an appropriate human-machine interface (HMI) on how to steer the vehicle into the previously scanned parking spot. Without having an active steering in the vehicle, the driver remains in full control over the vehicle's motion. This paper outlines the main ideas and concepts of the system and focusses on the developed control structures. Finally, experimental results underline the validity of the chosen approach.

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A sensor guided autonomous parking system for nonholonomic mobile robots

Cited by 63 publications

References 8 publications

Robust automatic parallel parking in tight spaces via fuzzy logic

Robust automatic parallel parking in tight spaces via fuzzy logic

Fuzzy Logic Based Autonomous Parallel Parking System with Kalman Filtering

Nonlinear path following control of non‐holonomic vehicles with the human as actuator in a parking application

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