Sparse robot swarms: Moving swarms to real-world applications

Robot swarms are groups of robots that each act autonomously based on only local perception and coordination with neighbouring robots. While current swarm implementations can be large in size (e.g. 1000 robots), they are typically constrained to working in highly controlled indoor environments. Moreover, a common property of swarms is the underlying assumption that the robots act in close proximity of each other (e.g. 10 body lengths apart), and typically employ uninterrupted, situated, close-range communication for coordination. Many real-world applications, including environmental monitoring and precision agriculture, however, require scalable groups of robots to act jointly over large distances (e.g. 1000 body lengths), rendering the use of dense swarms impractical. Using a dense swarm for such applications would be invasive to the environment and unrealistic in terms of mission deployment, maintenance and post-mission recovery. To address this problem, we propose the sparse swarm concept, and illustrate its use in the context of four application scenarios. For one scenario, which requires a group of rovers to traverse, and monitor, a forest environment, we identify the challenges involved at all levels in developing a sparse swarm—from the hardware platform to communication-constrained coordination algorithms—and discuss potential solutions. We outline open questions of theoretical and practical nature, which we hope will bring the concept of sparse swarms to fruition

Collective Decision-Making on Task Allocation Feasibility

Robot swarms offer the potential to bring several advantages to the real-world applications but deploying them presents challenges in ensuring feasibility across diverse environments. Assessing the feasibility of new tasks for swarms is crucial to ensure the effective utilisation of resources, as well as to provide awareness of the suitability of a swarm solution for a particular task. In this paper, we introduce the concept of distributed feasibility, where the swarm collectively assesses the feasibility of task allocation based on local observations and interactions. We apply Direct Modulation of Majority-based Decisions as our collective decision-making strategy and show that, in a homogeneous setting, the swarm is able to collectively decide whether a given setup has a high or low feasibility as long as the robot-to-task ratio is not near one.Comment: 3 Pages, 3 Figures, Accepted to ICRA 2024 Workshop "Breaking Swarm Stereotypes

Environment classification in multiagent systems inspired by the adaptive immune system

The adaptive immune system in vertebrates is a complex, distributed, adaptive system capable of effecting collective mul-ticellular responses. Our study introduces many of the desirable properties of this biological system to decentralized multiagent systems. We adopt the crossregulation model of the adaptive immune system involving interactions between effector and regulatory cells. Effector cells can mount beneficial immune responses to microbial antigens as well as pathologic autoimmune responses to self-antigens. Deleterious autoimmunity is prevented by regulatory cells that suppress the effectors to tolerate the self-antigens. We redeploy the crossregulation model within a multiagent system by letting each agent run an ODE-based instance of the model. Results of extensive simulation-based experiments demonstrate that a distributed multiagent system can mount different responses to distinct objects in their environment. These responses are solely a result of the dynamics between virtual cells in each agent and interactions between neighboring agents. The collective dynamics gives rise to a meaningful "self"- "nonself" classification of the environment by individual agent, even if these categories were not prescribed a priori in the agents.info:eu-repo/semantics/publishedVersio

COMT Val 158 Met polymorphism is associated with post-traumatic stress disorder and functional outcome following mild traumatic brain injury

Mild traumatic brain injury (mTBI) results in variable clinical trajectories and outcomes. The source of variability remains unclear, but may involve genetic variations, such as single nucleotide polymorphisms (SNPs). A SNP in catechol-o-methyltransferase (COMT) is suggested to influence development of post-traumatic stress disorder (PTSD), but its role in TBI remains unclear. Here, we utilize the Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot (TRACK-TBI Pilot) study to investigate whether the COMT Val158Met polymorphism is associated with PTSD and global functional outcome as measured by the PTSD Checklist - Civilian Version and Glasgow Outcome Scale Extended (GOSE), respectively. Results in 93 predominately Caucasian subjects with mTBI show that the COMT Met158 allele is associated with lower incidence of PTSD (univariate odds ratio (OR) of 0.25, 95% CI [0.09-0.69]) and higher GOSE scores (univariate OR 2.87, 95% CI [1.20-6.86]) 6-months following injury. The COMT Val158Met genotype and PTSD association persists after controlling for race (multivariable OR of 0.29, 95% CI [0.10-0.83]) and pre-existing psychiatric disorders/substance abuse (multivariable OR of 0.32, 95% CI [0.11-0.97]). PTSD emerged as a strong predictor of poorer outcome on GOSE (multivariable OR 0.09, 95% CI [0.03-0.26]), which persists after controlling for age, GCS, and race. When accounting for PTSD in multivariable analysis, the association of COMT genotype and GOSE did not remain significant (multivariable OR 1.73, 95% CI [0.69-4.35]). Whether COMT genotype indirectly influences global functional outcome through PTSD remains to be determined and larger studies in more diverse populations are needed to confirm these findings

Trade-offs of Dynamic Control Structure in Human-swarm Systems

Swarm robotics is a study of simple robots that exhibit complex behaviour only by interacting locally with other robots and their environment. The control in swarm robotics is mainly distributed whereas centralised control is widely used in other fields of robotics. Centralised and decentralised control strategies both pose a unique set of benefits and drawbacks for the control of multi-robot systems. While decentralised systems are more scalable and resilient, they are less efficient compared to the centralised systems and they lead to excessive data transmissions to the human operators causing cognitive overload. We examine the trade-offs of each of these approaches in a human-swarm system to perform an environmental monitoring task and propose a flexible hybrid approach, which combines elements of hierarchical and decentralised systems. We find that a flexible hybrid system can outperform a centralised system (in our environmental monitoring task by 19.2%) while reducing the number of messages sent to a human operator (here by 23.1%). We conclude that establishing centralisation for a system is not always optimal for performance and that utilising aspects of centralised and decentralised systems can keep the swarm from hindering its performance.Comment: The International Symposium on Distributed Autonomous Robotic Systems (DARS 2024

COMT Val 158 Met polymorphism is associated with nonverbal cognition following mild traumatic brain injury

Mild traumatic brain injury (mTBI) results in variable clinical outcomes, which may be influenced by genetic variation. A single-nucleotide polymorphism in catechol-o-methyltransferase (COMT), an enzyme which degrades catecholamine neurotransmitters, may influence cognitive deficits following moderate and/or severe head trauma. However, this has been disputed, and its role in mTBI has not been studied. Here, we utilize the Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot (TRACK-TBI Pilot) study to investigate whether the COMT Val (158) Met polymorphism influences outcome on a cognitive battery 6 months following mTBI--Wechsler Adult Intelligence Test Processing Speed Index Composite Score (WAIS-PSI), Trail Making Test (TMT) Trail B minus Trail A time, and California Verbal Learning Test, Second Edition Trial 1-5 Standard Score (CVLT-II). All patients had an emergency department Glasgow Coma Scale (GCS) of 13-15, no acute intracranial pathology on head CT, and no polytrauma as defined by an Abbreviated Injury Scale (AIS) score of ≥3 in any extracranial region. Results in 100 subjects aged 40.9 (SD 15.2) years (COMT Met (158) /Met (158) 29 %, Met (158) /Val (158) 47 %, Val (158) /Val (158) 24 %) show that the COMT Met (158) allele (mean 101.6 ± SE 2.1) associates with higher nonverbal processing speed on the WAIS-PSI when compared to Val (158) /Val (158) homozygotes (93.8 ± SE 3.0) after controlling for demographics and injury severity (mean increase 7.9 points, 95 % CI [1.4 to 14.3], p = 0.017). The COMT Val (158) Met polymorphism did not associate with mental flexibility on the TMT or with verbal learning on the CVLT-II. Hence, COMT Val (158) Met may preferentially modulate nonverbal cognition following uncomplicated mTBI.Registry: ClinicalTrials.gov Identifier NCT01565551

Fingerprinting Agent-Environment Interaction via Information Theory

In this paper, we investigate by means of statistical and information-theoretic measures, to what extent sensory-motor coordinated activity can generate and structure information in the sensory channels of a simulated agent interacting with its surrounding environment. We show how the usage of correlation, entropy, and mutual information can be employed (a) to segment an observed behavior into distinct behavioral states, (b) to quantify (fingerprint) the agent-environment interaction, and (c) to analyze the informational relationship between the different components of the sensory-motor apparatus. We hypothesize that a deeper understanding of the information-theoretic implications of sensory-motor coordination can help us endow our robots with better sensory morphologies, and with better strategies for exploring their surrounding environment

Apolipoprotein E epsilon 4 (APOE-ε4) genotype is associated with decreased 6-month verbal memory performance after mild traumatic brain injury

Introduction: The apolipoprotein E (APOE) ε4 allele associates with memory impairment in neurodegenerative diseases. Its association with memory after mild traumatic brain injury (mTBI) is unclear. Methods: mTBI patients (Glasgow Coma Scale score 13–15, no neurosurgical intervention, extracranial Abbreviated Injury Scale score ≤1) aged ≥18 years with APOE genotyping results were extracted from the Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot (TRACK-TBI Pilot) study. Cohorts determined by APOE-ε4(+/−) were assessed for associations with 6-month verbal memory, measured by California Verbal Learning Test, Second Edition (CVLT-II) subscales: Immediate Recall Trials 1–5 (IRT), Short-Delay Free Recall (SDFR), Short-Delay Cued Recall (SDCR), Long-Delay F