An Agent-Based Cognitive Robot Architecture

Wei, Changyun; Hindriks, Koen V.

doi:10.1007/978-3-642-38700-5_4

Cited by 18 publications

(15 citation statements)

References 18 publications

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“…2 Robots in the BW4T are GOAL [5], the agent programming language that we have used for implementing our proposed approach. We also use GOAL agents to control real robots in the work [18], but the simulator is much easier for collecting data and repeat experiments. GOAL, is a rule-based language that supports explicit communication among agents that make decisions based on mental states consisting of knowledge, beliefs, and goals.…”

Section: Methodsmentioning

confidence: 99%

Altruistic coordination for multi-robot cooperative pathfinding

2015

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When multiple robots perform tasks in a shared workspace, they might be confronted with the risk of blocking each other's ways, which will lead to conflicts or interference among them. Planning collision-free paths for all the robots is a challenge for a multi-robot system, which is also known as the multi-robot cooperative pathfinding problem in which each robot has to navigate from its starting location to the destination while keeping avoiding stationary obstacles as well as the other robots. In this paper, we present a novel fully decentralized approach to this problem. Our approach allows robots to make real-time responses to dynamic environments and can resolve a set of benchmark deadlock situations subject to complex spatial constraints in a shared workspace by means of altruistic coordination. Specifically, when confronted with congested situations, each robot can employ waiting, moving-forwards, dodging, retreating and turning-head strategies to make local adjustments. Most importantly, each robot only needs to coordinate and communicate with the others that are located within its coordinated network in our approach, which can reduce communication overhead in fully decentralized multi-robot systems. In addition, experimental results also show that our proposed approach provides an efficient and competitive solution to this problem.

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Section: Methodsmentioning

confidence: 99%

Altruistic coordination for multi-robot cooperative pathfinding

2015

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“…In [20], an agent programming language called Goal is used to program a cognitive robot control architecture that combines low-level sub-symbolic control with high-level symbolic control. The Goal language helps to realize a cognitive layer where low-level execution control and processing of sensor data are delegated to components in other layers.…”

Section: Related Workmentioning

confidence: 99%

The KnowLang Approach to Self-adaptation

Vassev

Hinchey

2015

Software, Services, and Systems

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Abstract. Self-adaptive systems autonomously monitor their behavior and eventually modify that behavior according to changes in the operational environment or in the system itself. In this entry, we present an approach to implementing self-adaptation capabilities with KnowLang, a special framework for knowledge representation and reasoning. KnowLang provides for a special knowledge context and a special reasoner operating in that context. The approach is formal and demonstrates how knowledge representation and reasoning help to establish the vital connection between knowledge, perception, and actions that realize selfadaptive behavior. Knowledge is used against the perception of the world to generate appropriate actions in compliance with some set of goals and beliefs.

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“…More recently agent based approaches have been explored in the control of spacecraft [68], Unmanned Aircraft [55,86,70], and robotics [87]. Many of these approaches are explicitly BDI based and are motivated by the desire to separate the symbolic and sub-symbolic reasoning and model the mission designer's intent.…”

Section: Agent Controlled Hybrid Systemsmentioning

confidence: 99%

Practical verification of decision-making in agent-based autonomous systems

et al. 2014

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We present a verification methodology for analysing the decision-making component in agent-based hybrid systems. Traditionally hybrid automata have been used to both implement and verify such systems, but hybrid automata based modelling, programming and verification techniques scale poorly as the complexity of discrete decision-making increases making them unattractive in situations where complex logical reasoning is required. In the programming of complex systems it has, therefore, become common to separate out logical decision-making into a separate, discrete, component. However, verification techniques have failed to keep pace with this development. We are exploring agent-based logical components and have developed a model checking technique for such components which can then be composed with a separate analysis of the continuous part of the hybrid system. Among other things this allows program model checkers to be used to verify the actual implementation of the decision-making in hybrid autonomous systems.

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An Agent-Based Cognitive Robot Architecture

Cited by 18 publications

References 18 publications

Altruistic coordination for multi-robot cooperative pathfinding

Altruistic coordination for multi-robot cooperative pathfinding

The KnowLang Approach to Self-adaptation

Practical verification of decision-making in agent-based autonomous systems

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