Self-Reactive Planning of Multi-Robots with Dynamic Task Assignments

Yang, Qin; Luo, Zhiwen; Song, Wen-Zhan; Parasuraman, Ramviyas

doi:10.1109/mrs.2019.8901075

Cited by 22 publications

(11 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…EN G -Energy-based: According to our previous work in [18], [16], where the agents with the same category will sort based only on their current energy (battery) levels at the initial positions, then divide into two parts with equal numbers. By selecting the high or low parts in each category to form the corresponding two heterogeneous sub-groups, we assign the higher energy group to the challenging task and the lower one to the easy one, respectively.…”

Section: Compared Methods From the Literaturementioning

confidence: 99%

“…To bridge this important gap, in this paper, we introduce a general agent-agent trust model based on Relative Needs Entropy (RNE). Here, we extend our previous work [16], where we defined needs hierarchy for robots similar to Maslow's law of human needs. Using the current state of the needs of the agents, it is possible to devise a relative needs entropy value, which can help measure social trust between agents.…”

Section: Introductionmentioning

confidence: 92%

“…In Robot Needs Hierarchy [16], [18], the agent's needs expressed as the Needs Expectation, which can be calculated through its behaviors' weight and corresponding safety probability based on the data of perception and communication. The individual safety needs (Eq.…”

Section: B Robot Needs Vectormentioning

confidence: 99%

See 2 more Smart Citations

How Can Robots Trust Each Other For Better Cooperation? A Relative Needs Entropy Based Robot-Robot Trust Assessment Model

Qin¹,

Parasuraman²

2021

Preprint

Self Cite

View full text Add to dashboard Cite

Cooperation in multi-agent and multi-robot systems can help agents build various formations, shapes, and patterns presenting corresponding functions and purposes adapting to different situations. Relationship between agents such as their spatial proximity and functional similarities could play a crucial role in cooperation between agents. Trust level between agents is an essential factor in evaluating their relationships' reliability and stability, much as people do. This paper proposes a new model called Relative Needs Entropy (RNE) to assess trust between robotic agents. RNE measures the distance of needs distribution between individual agents or groups of agents. To exemplify its utility, we implement and demonstrate our trust model through experiments simulating a heterogeneous multi-robot grouping task in a persistent urban search and rescue mission consisting of tasks at two levels of difficulty. The results suggest that RNE trust-Based grouping of robots can achieve better performance and adaptability for diverse task execution compared to the stateof-the-art energy-based or distance-based grouping models.

show abstract

Section: Compared Methods From the Literaturementioning

confidence: 99%

Section: Introductionmentioning

confidence: 92%

See 1 more Smart Citation

How Can Robots Trust Each Other For Better Cooperation? A Relative Needs Entropy Based Robot-Robot Trust Assessment Model

Qin¹,

Parasuraman²

2021

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…When it comes to grouping heterogeneous robots with various capabilities cooperating with each other to pursue certain common goals (rescue missions), the literature is thin with several gaps remaining to address the integration of organizing agents' behaviors, solving the conflicts, optimizing system utility and boosting system adaptability and robustness for the entire group [31], [3]. On the other hand, there is little research done from agent's needs perspective studying individual interaction and behaviours for system performance (group utility) and global behaviours in MRS, especially in disaster robotics [32], [5], [33].…”

Section: Related Work and Projectsmentioning

confidence: 99%

Needs-driven Heterogeneous Multi-Robot Cooperation in Rescue Missions

Yang

Parasuraman²

2020

Preprint

Self Cite

View full text Add to dashboard Cite

This paper focuses on the teaming aspects and the role of heterogeneity in a multi-robot system applied to robotaided urban search and rescue (USAR) missions. We specifically propose a needs-driven multi-robot cooperation mechanism represented through a Behavior Tree structure and evaluate the performance of the system in terms of the group utility and energy cost to achieve the rescue mission in a limited time.From the theoretical analysis, we prove that the needs-drive cooperation in a heterogeneous robot system enables higher group utility compared to a homogeneous robot system. We also perform simulation experiments to verify the proposed needsdriven cooperation and show that the heterogeneous multirobot cooperation can achieve better performance and increase system robustness by reducing uncertainty in task execution. Finally, we discuss the application to human-robot teaming.

show abstract

“…In a swarm of robots, each robot builds knowledge of the local world through its limited perception. However, robots exploit direct and indirect communication to increase their efficiency, such as groups by sharing information and making decisions together [2]. One well-researched example is the application of swarms for foraging [3], which is a behavior commonly observed in social animals.…”

Section: Introductionmentioning

confidence: 99%

Energy-Aware Multi-Robot Task Allocation in Persistent Tasks

Latif¹,

Gui²,

Munir³

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

The applicability of the swarm robots to perform foraging tasks is inspired by their compact size and cost. A considerable amount of energy is required to perform such tasks, especially if the tasks are continuous and/or repetitive. Real-world situations in which robots perform tasks continuously while staying alive (survivability) and maximizing production (performance) require energy awareness. This paper proposes an energy-conscious distributed task allocation algorithm to solve continuous tasks (e.g., unlimited foraging) for cooperative robots to achieve highly effective missions. We consider efficiency as a function of the energy consumed by the robot during exploration and collection when food is returned to the collection bin. Finally, the proposed energy-efficient algorithm minimizes the total transit time to the charging station and time consumed while recharging and maximizes the robot's lifetime to perform maximum tasks to enhance the overall efficiency of collaborative robots. We evaluated the proposed solution against a typical greedy benchmarking strategy (assigning the closest collection bin to the available robot and recharging the robot at maximum) for efficiency and performance in various scenarios. The proposed approach significantly improved performance and efficiency over the baseline approach.

show abstract

Self-Reactive Planning of Multi-Robots with Dynamic Task Assignments

Cited by 22 publications

References 15 publications

How Can Robots Trust Each Other For Better Cooperation? A Relative Needs Entropy Based Robot-Robot Trust Assessment Model

How Can Robots Trust Each Other For Better Cooperation? A Relative Needs Entropy Based Robot-Robot Trust Assessment Model

Needs-driven Heterogeneous Multi-Robot Cooperation in Rescue Missions

Energy-Aware Multi-Robot Task Allocation in Persistent Tasks

Contact Info

Product

Resources

About