A.B.M.Toufique-UlIslam,
Md.AbdulBased,
Md.Imran HossainBhuiyan,
- Research Scholar, Department of CSE, Dhaka International University, Satarkul-Badda, Dhaka, Bangladesh
- Research Scholar, Department of CSE, Dhaka International University, Satarkul-Badda, Dhaka, Bangladesh
- Research Scholar, Department of CSE, Dhaka International University, Satarkul-Badda, Dhaka, Bangladesh
Abstract
An intelligent agent is a self-governing system that can take action to accomplish its goals based on how it perceives its surroundings. This paper introduces a newly designed humanoid robot that demonstrates significant advancements in performance, reliability, durability, energy efficiency, and environmental sustainability. The design emphasizes a bio-inspired musculoskeletal system, enabling natural and flexible motion while improving operational lifespan. A self-repair system is integrated to allow the robot to address minor damages autonomously, enhancing its robustness and reducing downtime. The relationship between precise actuator movements, advanced perception techniques ,and optimal sensor selection is analyzed to ensure accurate environmental interactions. A cognitive AI-system is embedded, enabling adaptive learning and improved decision-making in dynamic scenarios. The robot’s capabilities are further enhanced by its bio-inspired actuation, which combines efficiency with smooth, natural motion. This work explores the application of humanoid agents in diverse fields, including medical care, industrial production, vocational education and training, public services, and customer relations. The integrated approach outlined in this paper positions humanoid robots as versatile, efficient, and sustainable agents in complex human-centered environments.
Keywords: Intelligentagent,Humanoidrobot,Bio-inspireddesign,CognitiveAISystem,Human-Robot Collaboration
[This article belongs to Journal of Control & Instrumentation ]
A.B.M.Toufique-UlIslam, Md.AbdulBased, Md.Imran HossainBhuiyan. Designing Intelligent Agents for Effective Collaboration with Human in Complex Environment. Journal of Control & Instrumentation. 2025; 16(03):1-7.
A.B.M.Toufique-UlIslam, Md.AbdulBased, Md.Imran HossainBhuiyan. Designing Intelligent Agents for Effective Collaboration with Human in Complex Environment. Journal of Control & Instrumentation. 2025; 16(03):1-7. Available from: https://journals.stmjournals.com/joci/article=2025/view=232456
References
- Trieu NM, Thinh NT. A comprehensive review: Interaction of appearance and behavior, artificial skin, and humanoid robot. J Robot. 2023;2023:1–16. https://doi.org/10.1155/2023/5589845
- ALIFE2024template. https://arxiv.org/html/2406.11420v1
- Buschmann T, Lohmeier S, Ulbrich H. Humanoid robot Lola: Design and walking control. J Physiol Paris. 2009;103(3–5):141–8. https://doi.org/10.1016/j.jphysparis.2009.07.008
- Faisal M, Velazquez RAM, Laamarti F, Saddik AE. Underactuated digital twin’s robotic hands with tactile sensing capabilities for well-being. In: Elsevier eBooks. 2023. p.15–38. https://doi.org/10.1016/b978-0-32-399163-6.00007-x
- Tong Y, Liu H, Zhang Z. Advancements in humanoid robots: A comprehensive review and future prospects. IEEE/CAA J Autom Sin. 2024;11(2):301–28. https://doi.org/10.1109/jas.2023.124140
- Lillicrap TP, Hunt JJ, Pritzel A, Heess N, Erez T, Tassa Y, et al. Continuous control with deep reinforcement learning. arXiv. 2015. https://doi.org/10.48550/arxiv.1509.02971
- Belpaeme T, Kennedy J, Ramachandran A, Scassellati B, Tanaka F. Social robots for education: A review. Sci Robot. 2018;3(21). https://doi.org/10.1126/scirobotics.aat5954
- Polygerinos P, Wang Z, Galloway KC, Wood RJ, Walsh CJ. Soft robotic glove for combined assistance and at-home rehabilitation. Robot Auton Syst. 2014;73:135–43. https://doi.org/10.1016/j.robot.2014.08.014
- Pfeiffer M, Pfeil T. Deep learning with spiking neurons: Opportunities and challenges. Front Neurosci. 2018;12. https://doi.org/10.3389/fnins.2018.00774
- Apicella A, Donnarumma F, Isgrò F, Prevete R. A survey on modern trainable activation functions. Neural Netw. 2021;138:14–32. https://doi.org/10.1016/j.neunet.2021.01.026
- Brandli C, Berner R, Yang NM, Liu NS, Delbruck T. A 240 × 180 130 dB 3 µs latency global shutter spatiotemporal vision sensor. IEEE J Solid-State Circuits. 2014;49(10):2333–41. https://doi.org/10.1109/jssc.2014.2342715
- Zhao S, Zhu R. Electronic skin with multifunction sensors based on thermosensation. Adv Mater. 2017;29(15). https://doi.org/10.1002/adma.201606151
- Garcez ASD, Gabbay DM, Broda KB. Neural-symbolic learning systems: Foundations and applications. 2012.

Journal of Control & Instrumentation
| Volume | 16 |
| Issue | 03 |
| Received | 28/05/2025 |
| Accepted | 19/06/2025 |
| Published | 18/11/2025 |
| Publication Time | 174 Days |
Login
PlumX Metrics