Dual-Arm Robot Motion Planning Based on Cooperative Coevolution

Ćurković, Petar; Jerbić, Bojan

doi:10.1007/978-3-642-11628-5_18

Cited by 11 publications

(6 citation statements)

References 10 publications

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“…A printout of evidence must be taken from office PC (8). The notice must then be given to any one of the culprits, Racheal (21) or Monica (22).…”

Section: Hardware Resultsmentioning

confidence: 99%

Robot Mission Planning using Co-evolutionary Optimization

Kala¹

2019

Robotica

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SummaryMission planning is a complex motion planning problem specified by using Temporal Logic constituting of Boolean and temporal operators, typically solved by model verification algorithms with an exponential complexity. The paper proposes co-evolutionary optimization thus building an iterative solution to the problem. The language for mission specification is generic enough to represent everyday missions, while specific enough to design heuristics. The mission is broken into components which cooperate with each other. The experiments confirm that the robot is able to outperform the search, evolutionary and model verification techniques. The results are demonstrated by using a Pioneer LX robot.

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“…A printout of evidence must be taken from office PC (8). The notice must then be given to any one of the culprits, Racheal (21) or Monica (22).…”

Section: Hardware Resultsmentioning

confidence: 99%

Robot Mission Planning using Co-evolutionary Optimization

Kala¹

2019

Robotica

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“…Currently there are no algorithms to solve real time agent collision or they exist but with limitations. Collision between two agents with kinematic chains of 3 DOF can be solved in a definite period of time [14]. For the reason of limited computational power and the collision detection not being the centre of this research the function (F) described in chapter 3 was used.…”

Section: Methodsmentioning

confidence: 99%

Autonomous Planning Framework for Distributed Multiagent Robotic Systems

Švaco

Šekoranja

Jerbić

2011

Technological Innovation for Sustainability

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Abstract. In this paper a creative action planning algorithm (CAPA) is presented for solving multiagent planning problems and task allocation. The distributed multiagent system taken in consideration is a system of m autonomous agents. Agents workspace contains simplified blocks which form different space structures. By employing the planning algorithm and through interaction agents allocate tasks which they execute in order to assemble the required space structure. The planning algorithm is based on an inductive engine. From a given set of objects which can differ from the initial set agents need to reach a solution in the anticipated search space. A multiagent framework for autonomous planning is developed and implemented on an actual robotic system consisting of three 6 DOF industrial robots.

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“…Co-evolutionary algorithms offer great potential for concurrent multiagent domains [12–14]. Concepts of co-evolution were also successfully coupled with other heuristic optimization techniques [15–17] to solve complex optimization problems when search-spaces are connected.…”

Section: The Proposed Co-evolutionary Algorithmmentioning

confidence: 99%

Co-Evolutionary Algorithm for Motion Planning of Two Industrial Robots with Overlapping Workspaces

Ćurković

Jerbić

Stipančić

2013

International Journal of Advanced Robotic Systems

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A high level of autonomy is a prerequisite for achieving robotic presence in a broad spectrum of work environments. If there is more than one robot in a given environment and the workspaces of robots are shared, then the robots present a dynamic obstacle to each other, which is a potentially dangerous situation. This paper deals with the problem of motion planning for two six-degrees-offreedom (DOF) industrial robots whose workspaces overlap. The planning is based on a novel hall of famePareto-based co-evolutionary algorithm. The modification of the algorithm is directed towards speeding-up coevolution, to achieve real-time implementation in an industrial robotic system composed of two FANUC LrMate 200iC robots. The results of the simulation and implementation show the great potential of the method in terms of convergence, robustness and time.

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Dual-Arm Robot Motion Planning Based on Cooperative Coevolution

Cited by 11 publications

References 10 publications

Robot Mission Planning using Co-evolutionary Optimization

Robot Mission Planning using Co-evolutionary Optimization

Autonomous Planning Framework for Distributed Multiagent Robotic Systems

Co-Evolutionary Algorithm for Motion Planning of Two Industrial Robots with Overlapping Workspaces

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