A path following control of an unmanned autonomous forklift

Tamba, Tua A.; Hong, Bonghee; Hong, Keum‐Shik

doi:10.1007/s12555-009-0114-y

Cited by 66 publications

(30 citation statements)

References 18 publications

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“…Trajectory planning by the system is needed to navigate the vehicle. The optimal trajectory based on the global map has been widely studied in the field of robot navigation [30][31][32]. The coordinate points of all stalks are mapped in accordance with the world coordinate.…”

Section: Detection Of the Crop Row Linementioning

confidence: 99%

RBF-Based Monocular Vision Navigation for Small Vehicles in Narrow Space below Maize Canopy

et al. 2016

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Abstract:Maize is one of the major food crops in China. Traditionally, field operations are done by manual labor, where the farmers are threatened by the harsh environment and pesticides. On the other hand, it is difficult for large machinery to maneuver in the field due to limited space, particularly in the middle and late growth stage of maize. Unmanned, compact agricultural machines, therefore, are ideal for such field work. This paper describes a method of monocular visual recognition to navigate small vehicles between narrow crop rows. Edge detection and noise elimination were used for image segmentation to extract the stalks in the image. The stalk coordinates define passable boundaries, and a simplified radial basis function (RBF)-based algorithm was adapted for path planning to improve the fault tolerance of stalk coordinate extraction. The average image processing time, including network latency, is 220 ms. The average time consumption for path planning is 30 ms. The fast processing ensures a top speed of 2 m/s for our prototype vehicle. When operating at the normal speed (0.7 m/s), the rate of collision with stalks is under 6.4%. Additional simulations and field tests further proved the feasibility and fault tolerance of our method.

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Section: Detection Of the Crop Row Linementioning

confidence: 99%

RBF-Based Monocular Vision Navigation for Small Vehicles in Narrow Space below Maize Canopy

et al. 2016

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“…In other works by the same authors, a laser scanner is also used for localization and generation of free-obstacles trajectories in factory buildings [25]. There are also some proposals that employ different sensory devices to provide better performance or even include the information of additional devices such as sonars [22].…”

Section: Related Workmentioning

confidence: 99%

Robust behavior and perception using hierarchical state machines: a pallet manipulation experiment

Peña¹,

Manso²,

Pinero³

et al. 2011

jopha

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Abstract-Interacting with simple objects in semi-controlled environments is a rich source of challenging situations for mobile robots, particularly when performing sequential tasks. In this paper we present the computational architecture and results obtained from a pallet manipulation experiment with a real robot. To achieve a good success rate in locating and picking the pallets a set of behaviors is assembled in a hierarchical state machine. The behaviors are arranged in such a way that the global uncertainty of the task is progressively reduced when approaching the goal. To do so, actions are generated in each stage that increase the confidence of the robot of being in that particular relation to the world. In order to set up this experiment, it is required a non-trivial set of working senso-motor behaviors. We build on this set to design and test a pallet moving task in which the robot has to locate, approach, obtain the pose, pick up and, finally move the pallet to its target position. The only sensory sources of information available to the robot are a binocular vision system and its internal odometry. To carry out this task we have equipped a RobEx robot with a 1 DOF forklift and a 4 DOF binocular head. We present the conceptual and computational models and the results of the experiments in a real setup.

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“…Current warehouse automation systems [1] are designed for permanent storage and distribution facilities, where indoor environments may be highly prepared and kept free of people, and substantial prior knowledge may be assumed of manipuland placement and geometry. Some work has correspondingly focused on forklift control [2], and pallet recognition [3], [4] and manipulation [5]- [7] for limited pallet types and environment classes. In contrast, our vehicle is designed to operate in the dynamic, unstructured, and human-occupied facilities that are typical of the military supply chain, and to handle cargo pallets with differing geometry, appearance, and loads.…”

Section: Introductionmentioning

confidence: 99%

A voice-commandable robotic forklift working alongside humans in minimally-prepared outdoor environments

Teller¹,

Walter²,

Antone

et al. 2010

2010 IEEE International Conference on Robotics and Automation

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Abstract-One long-standing challenge in robotics is the realization of mobile autonomous robots able to operate safely in existing human workplaces in a way that their presence is accepted by the human occupants. We describe the development of a multi-ton robotic forklift intended to operate alongside human personnel, handling palletized materials within existing, busy, semi-structured outdoor storage facilities.The system has three principal novel characteristics. The first is a multimodal tablet that enables human supervisors to use speech and pen-based gestures to assign tasks to the forklift, including manipulation, transport, and placement of palletized cargo. Second, the robot operates in minimally-prepared, semistructured environments, in which the forklift handles variable palletized cargo using only local sensing (and no reliance on GPS), and transports it while interacting with other moving vehicles. Third, the robot operates in close proximity to people, including its human supervisor, other pedestrians who may cross or block its path, and forklift operators who may climb inside the robot and operate it manually. This is made possible by novel interaction mechanisms that facilitate safe, effective operation around people.We describe the architecture and implementation of the system, indicating how real-world operational requirements motivated the development of the key subsystems, and provide qualitative and quantitative descriptions of the robot operating in real settings.

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A path following control of an unmanned autonomous forklift

Cited by 66 publications

References 18 publications

RBF-Based Monocular Vision Navigation for Small Vehicles in Narrow Space below Maize Canopy

RBF-Based Monocular Vision Navigation for Small Vehicles in Narrow Space below Maize Canopy

Robust behavior and perception using hierarchical state machines: a pallet manipulation experiment

A voice-commandable robotic forklift working alongside humans in minimally-prepared outdoor environments

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