Experimental results of robotic excavation using fuzzy behavior control

Shi, Xiaobo; Wang, Fei‐Yue; Lever, Paul

doi:10.1016/0967-0661(95)00220-0

Cited by 21 publications

(10 citation statements)

References 5 publications

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“…The motivation for this type of approach is quite simple: Since the human control process of excavation tasks requires no analytic models of machine/environment interactions, it is advantageous to build an excavation control system using experience and knowledge from skilled human operators. So far, both laboratory testing with prototype excavation machines and field implementation in industrial wheel loaders and other type of vehicles have produced successful results and demonstrated great potentials for our proposed control method [18], [25], [26], [28]. This paper describes the first part of our work in robotic excavation, fuzzy agent algorithms and their laboratory experiments.…”

Section: Introductionmentioning

confidence: 94%

“…However, for excavation, especially rock excavation, it is impossible to predict what exactly will happen to machines because the characteristics of the materials at the excavation site cannot be predetermined, and the digging conditions change continuously as machines disturb the material. This complexity implies that automated excavation machines might not be able to utilize conventional control methods that are based on mathematical equations, since it is impractical or infeasible to develop analytical model to specify interaction between an excavation machine and its environment [18]. Thus, new control methods must be developed for such applications.…”

Section: Introductionmentioning

confidence: 97%

“…This has lead to our work on using behavior programming, fuzzy control and neural networks for automated excavation since early 1990s [9]- [11], [16]- [18], [22]. The motivation for this type of approach is quite simple: Since the human control process of excavation tasks requires no analytic models of machine/environment interactions, it is advantageous to build an excavation control system using experience and knowledge from skilled human operators.…”

Section: Introductionmentioning

confidence: 99%

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Agent-Based Control for Fuzzy Behavior Programming in Robotic Excavation

Wang

2004

IEEE Trans. Fuzzy Syst.

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This paper discusses the concept, formulation, and implementation of the agent-based control for fuzzy behavior programming in robotic excavation. Petri net transducers are introduced to describe excavation control agent coordination and specification, while fuzzy control rules are used to implement primitive motions. A prototype laboratory excavation system is built with PUMA robotic manipulators and a force/torque sensor. Extensive experiments have been conducted and the results have demonstrated that the proposed control method is capable of continuously adapting and replanning its actions based on sensory feedback, and completing its excavation tasks in dynamic and unstructured environments.Index Terms-Agent-based control (ABC), agent coordination, behavior programming, fuzzy logic, Petri net transducers, robotic excavation.

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Section: Introductionmentioning

confidence: 94%

Section: Introductionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

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Agent-Based Control for Fuzzy Behavior Programming in Robotic Excavation

Wang

2004

IEEE Trans. Fuzzy Syst.

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“…Variations of this approach are presented for example in the work of Singh (1995), Shi et al (1996), andWang (2004). Other approaches treat the reactive forces in digging as external disturbances.…”

Section: Related Researchmentioning

confidence: 99%

Experiments in Autonomous Earth Moving

Bonchis

Hillier

Ryde

et al. 2011

IFAC Proceedings Volumes

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This paper presents a technology demonstrator currently under development and describes experiments carried out to date in autonomous bulk material handling using mobile equipment. Our primary platform is a Bobcat S185 skid-steer loader instrumented with an onboard computer, a sensor suite, and a communication link that support various levels of automation, from remote control to supervised autonomy. We present the main system components and discuss the autonomous cleaning of spillage and carryback, common bulk handling task in mining, currently executed exclusively using manually and/or remotely operated loaders. The system architecture is based on Spring, a Robotics Software Framework developed by CSIRO to support rapid development of new robotic systems, distributed as an Open Source package.

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“…However, it would be more desirable to control the unpredictable interaction between bucket and obstacle intelligently real time while continuing the excavation task instead of stopping. In university of Arizona, studies related avoidance obstacles have been conducted [9]. This studies presented implements of excavation tasks as sequences of behaviors and behaviors as sequences of actions.…”

Section: Introductionmentioning

confidence: 99%

Avoidance of Earth Obstacles for Intelligent Excavator

Bae¹,

Lee²,

Hong³

2011

28th International Symposium on Automation and Robotics in Construction (ISARC 2011)

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ABSTRACT:In this paper, we develop an algorithm for avoidance of earth obstacles using model-reference impedance control for autonomous excavator. There have been many research in the past regarding autonomous excavation, which were only concerned about position control, force control and path generation. However in order to apply the control system or algorithm to the actual autonomous excavation, it is essential that prediction and avoidance of potential obstacle must be carried out. When earth obstacles such as rocks and tree roots are detected by force/torque sensor, accidents can be easily prevented by halting the excavation task using a simple fail-safe algorithm. However, it would be more desirable to control the unpredictable bucket/earth obstacle interactions intelligently on-line while continuing the excavation task instead of stopping. Impedance control is a control scheme, which is used for defining dynamic relationship between end-effector and environment when the end-effector is constrained in the environment. In this case end-effector would be the bucket tip and environment would be the earth obstacle. In this paper a novel algorithm was developed which realize the obstacle avoidance of autonomous excavator that can regulate bucket force in real time.For the experimental use, hydraulic manipulator which resembles commercial excavator was designed. Two kinds of sensor, potentiometers and 6 axis force/torque sensor, were used to provide position and bucket tip force feedback information. Experimental results indicate that bucket has avoided earth obstacle smoothly without large force and all desired task is completed.

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Experimental results of robotic excavation using fuzzy behavior control

Cited by 21 publications

References 5 publications

Agent-Based Control for Fuzzy Behavior Programming in Robotic Excavation

Agent-Based Control for Fuzzy Behavior Programming in Robotic Excavation

Experiments in Autonomous Earth Moving

Avoidance of Earth Obstacles for Intelligent Excavator

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