Hierarchical Task Planning for Multiarm Robot with Multiconstraint

Wang, Yifan; Chen, Gang; Jia, Qingxuan; Yu, Boyang

doi:10.1155/2016/2508304

Cited by 7 publications

(4 citation statements)

References 19 publications

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“…Although this problem is challenging, a great deal of related work has sought to overcome similar complexities in adjacent problems by efficiently searching over the planning space through the use of symbolic methods, artificial intelligence (AI), and various optimization techniques [7]. Like other planning techniques, symbolic methods such as HTNs are utilized to search over the planning space efficiently [11]. We leverage HTNs for their increased decision transparency and reliability-two characteristics essential for maintaining an urban RDZ.…”

Section: B Intelligent Controlmentioning

confidence: 99%

“…In the context of RDZs, transparency and safety are crucial since an incorrect plan could broadly impact surrounding telecommunications services [5]. Given this, we focus on a classical planning approach known as HTNs [11]. HTNs are dependency graphs that are constructed with domain knowledge, meaning that the policy π is hand-crafted rather than learned.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

BoTM: Basestation-on-the-move, a Radio Access Network Management Primitive

Gottipati

Merwe

2021

IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)

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FlexRDZ is an online, autonomous manager for radio dynamic zones (RDZ) that seeks to enable the safe operation of RDZs through real-time control of deployed test transmitters. FlexRDZ leverages Hierarchical Task Networks and digital twin modeling to plan and resolve RDZ violations in near real-time. We prototype FlexRDZ with GTPyhop and the Terrain Integrated Rough Earth Model (TIREM). We deploy and evaluate FlexRDZ within a simulated version of the Salt Lake City POWDER testbed, a potential urban RDZ environment. Our simulations show that FlexRDZ enables up to a 20 dBm reduction in mobile interference and a significant reduction in the total power of leaked transmissions while preserving the overall communication capabilities and uptime of test transmitters. To our knowledge, FlexRDZ is the first autonomous system for RDZ management.

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Section: B Intelligent Controlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

BoTM: Basestation-on-the-move, a Radio Access Network Management Primitive

Gottipati

Merwe

2021

IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)

View full text Add to dashboard Cite

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“…The world knowledge, which is categorized into static knowledge, can be easily and feasibly exhibited, as is said by the previous researches on robot task planning. In this regard, as a result of the feasibility of representing world knowledge, the problem file of the task planner can be obtained from the world knowledge efficiently [11,12]. However, comparatively, the causal knowledge [13], is more represented in the formal language, like the PDDL (Planning Domain Definition Language) [14], HTN (Hierarchical Task Network) [15], and so on.…”

Section: Introductionmentioning

confidence: 99%

RTPO: A Domain Knowledge Base for Robot Task Planning

Sun

Chen

2019

Electronics

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Knowledge can enhance the intelligence of robots’ high-level decision-making. However, there is no specific domain knowledge base for robot task planning in this field. Aiming to represent the knowledge in robot task planning, the Robot Task Planning Ontology (RTPO) is first designed and implemented in this work, so that robots can understand and know how to carry out task planning to reach the goal state. In this paper, the RTPO is divided into three parts: task ontology, environment ontology, and robot ontology, followed by a detailed description of these three types of knowledge, respectively. The OWL (Web Ontology Language) is adopted to represent the knowledge in robot task planning. Then, the paper proposes a method to evaluate the scalability and responsiveness of RTPO. Finally, the corresponding task planning algorithm is designed based on RTPO, and then the paper conducts experiments on the basis of the real robot TurtleBot3 to verify the usability of RTPO. The experimental results demonstrate that RTPO has good performance in scalability and responsiveness, and the robot can achieve given high-level tasks based on RTPO.

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“…Referring to classifying workspace of space manipulators based on different base control modes in [15] and [19], we construct 5 types of RS according to different base control modes. Task realizability evaluation and path planning domain construction can be performed in a certain type of RS, and path planning is accomplished by A * algorithm [33]. For high-DOF space manipulators, the dimensionality of RS is too high to be drawn, so we apply the RS analytical method to the 3-DOF free-floating space manipulator.…”

Section: Introductionmentioning

confidence: 99%

Representation Space Analytical Method for Path Planning of Free-Floating Space Manipulators

2019

Self Cite

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Path planning is necessary for free-floating space manipulators to perform space tasks. However, the coupled motion between manipulator and base directly acts on path planning procedure, which results in current manipulator motion state is dependent on previous motion state, so we must consider the control of base-coupled motion in path planning. In this paper, we propose a general path planning strategy for free-floating space manipulators based on the representation space (RS) analytical method. RS consists of the representation variables which are connected to task attributes and base-coupled motion simultaneously, and it can be utilized to check task realizability and construct a path planning domain for free-floating space manipulators. To analyze the effects of base-coupled motion on path planning, we classify RS into five types according to different base control modes: fixed vehicle RS (FRS), attitude constrained RS (CRS), maximum reachable RS (MRS), guaranteed RS (GRS), and partly guaranteed RS (PGRS). CRS tells us the variation of base attitude (instead of base centroid position) directly influences task realizability and path planning, so we should particularly consider the control of motion of base attitude in path planning. With appropriately considering the control of base attitude and satisfying the base attitude deflection limitation, only PGRS can be utilized to check task realizability and construct a path planning domain for free-floating space manipulators. Then, we design a path planning strategy in PGRS based on A * algorithm. Finally, we apply the RS analytical method to the 3-DOF free-floating space manipulator to visually show RS, and the effectiveness of the method is verified by a simulation experiment. The RS analytical method is appropriate to path planning for any kinds of manipulators and various tasks. We only need to select the suitable representation variables, which can faithfully reflect task and manipulator attributes.

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Hierarchical Task Planning for Multiarm Robot with Multiconstraint

Cited by 7 publications

References 19 publications

BoTM: Basestation-on-the-move, a Radio Access Network Management Primitive

BoTM: Basestation-on-the-move, a Radio Access Network Management Primitive

RTPO: A Domain Knowledge Base for Robot Task Planning

Representation Space Analytical Method for Path Planning of Free-Floating Space Manipulators

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