Publications

Carmichael, MG, Tran, A, Aldini, S & Liu, D 2024, 'Methodologies in Physical Human–Robot Collaboration for Infrastructure Maintenance', Wiley, pp. 105-126.
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Hassan, M & Liu, D 2024, 'Coverage Planning and Motion Planning of Intelligent Robots for Civil Infrastructure Maintenance', Wiley, pp. 81-103.
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Huang, S, Pan, K & Dissanayake, G 2024, 'Perception in Complex and Unstructured Infrastructure Environments', Wiley, pp. 33-58.
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Isaac, G, Nicholas, P, Paul, G, Pietroni, N, Vidal Calleja, T, Xie, M & Schork, T 2024, 'Automated Shotcrete: A More Sustainable Construction Technology' in Green Energy and Technology, Springer International Publishing, pp. 331-345.
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Kodagoda, S, Kumar Viswanathan, V, Thiyagarajan, K, Tran, A, Wickramanayake, S, Barclay, S & Vitanage, D 2024, 'Robotics and Sensing for Condition Assessment of Wastewater Pipes', Wiley, pp. 243-261.
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Kodagoda, S, Kumar Viswanathan, V, Thiyagarajan, K, Tran, A, Wickramanayake, S, Barclay, S & Vitanage, D 2024, 'Robotics and Sensing for Condition Assessment of Wastewater Pipes' in Liu, D, Balaguer, C, Dissanayake, G & Kovac, M (eds), Infrastructure Robotics: Methodologies, Robotic Systems and Applications, Wiley, pp. 243-261.
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The text also presents many case studies of robotic systems developed for real-world applications in maintaining various civil infrastructures, including steel bridges, tunnels, underground water mains, underwater structures, and sewer ...

Liu, D & Dissanayake, G 2024, 'Infrastructure Robotics: An Introduction', Wiley, pp. 3-18.
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Sankaran, S 2024, 'Narrative inquiry in project management research' in Design Methods and Practices for Research of Project Management, Routledge, UK, pp. 157-168.

Sankaran, S & Dick, B 2024, 'Action research and project management' in Design Methods and Practices for Research of Project Management, Routledge, UK, pp. 101-118.

Valls Miro, J 2024, 'Robots for Underground Pipe Condition Assessment', Wiley, pp. 221-242.
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Wing Keung To, A, Le, K & Liu, D 2024, 'Underwater Robots for Cleaning and Inspection of Underwater Structures', Wiley, pp. 161-183.
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Ali, U, Wu, L, Müller, A, Sukkar, F, Kaupp, T & Vidal-Calleja, T 2024, 'Interactive Distance Field Mapping and Planning to Enable Human-Robot Collaboration', IEEE Robotics and Automation Letters, vol. 9, no. 12, pp. 10850-10857.
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Bailey, SM, Christensen, P, Sankaran, S & Millington, M 2024, 'Building person-centred homes: a case study of a cluster-designed home for adults with intellectual disability in Australia', Journal of Housing and the Built Environment, vol. 39, no. 1, pp. 345-369.
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AbstractA case study of 20 families investigated a cluster design of new homes for 15 adults with intellectual disabilities in Australia. It explored how families created a cluster home model for adults to live in their own homes with paid support in a modern context by answering three research questions: What type of home did parents choose for their children with intellectual disabilities and why? What type of home did they achieve? How did they overcome challenges to accomplish building the home? Families adopted a participatory design approach, collaborating as learning partners to secure government funding for purchasing land and constructing their cluster design. However, it was a complex project requiring many stakeholders with conflicting interests and priorities. Specifically, families rejected the group home model preferred by government agency staff, shifted the focus from technical building rules and design standards to prioritise each adult’s needs and preferences for their home, rejected institution-like fixtures/fittings when installed and used family governance to choose key support workers directly. Ultimately, the families created security of place through tenancy in attractive homes with government funding, welcoming neighbours and chosen support workers.

Best, G, Garg, R, Keller, J, Hollinger, GA & Scherer, S 2024, 'Multi-robot, multi-sensor exploration of multifarious environments with full mission aerial autonomy', The International Journal of Robotics Research, vol. 43, no. 4, pp. 485-512.
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We present a coordinated autonomy pipeline for multi-sensor exploration of confined environments. We simultaneously address four broad challenges that are typically overlooked in prior work: (a) make effective use of both range and vision sensing modalities, (b) perform this exploration across a wide range of environments, (c) be resilient to adverse events, and (d) execute this onboard teams of physical robots. Our solution centers around a behavior tree architecture, which adaptively switches between various behaviors involving coordinated exploration and responding to adverse events. Our exploration strategy exploits the benefits of both visual and range sensors with a generalized frontier-based exploration algorithm and an OpenVDB-based map processing pipeline. Our local planner utilizes a dynamically feasible trajectory library and a GPU-based Euclidean distance transform map to allow fast and safe navigation through both tight doorways and expansive spaces. The autonomy pipeline is evaluated with an extensive set of field experiments, with teams of up to three robots that fly up to 3 m/s and distances exceeding 1 km in confined spaces. We provide a summary of various field experiments and detail resilient behaviors that arose: maneuvering narrow doorways, adapting to unexpected environment changes, and emergency landing. Experiments are also detailed from the DARPA Subterranean Challenge, where our proposed autonomy pipeline contributed to us winning the “Most Sectors Explored” award. We provide an extended discussion of lessons learned, release software as open source, and present a video that illustrates our extensive field trials.

Chen, K, Bai, F, Huang, S & Sun, Y 2024, 'iMCB-PGO: Incremental Minimum Cycle Basis Construction and Application to Online Pose Graph Optimization', IEEE Robotics and Automation Letters, vol. 9, no. 11, pp. 10185-10192.
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Fan, Y, Yi, B & Liu, D 2024, 'An overview of stiffening approaches for continuum robots', Robotics and Computer-Integrated Manufacturing, vol. 90, pp. 102811-102811.
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Hernandez Moreno, V, Jansing, S, Polikarpov, M, Carmichael, MG & Deuse, J 2024, 'Obstacles and opportunities for learning from demonstration in practical industrial assembly: A systematic literature review', Robotics and Computer-Integrated Manufacturing, vol. 86, pp. 102658-102658.
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Huang, S, Hauser, K & Shell, DA 2024, 'Selected papers from RSS2022', The International Journal of Robotics Research, vol. 43, no. 4, pp. 387-388.
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Jamshir M, M, Vijayakumar, S, Das, S, Thiyagarajan, K & Kodagoda, S 2024, 'A Novel Direct Digitizer for Leaky Differential Capacitive Sensors Using Phase Sensitive Integration', IEEE Sensors Letters, vol. 8, no. 2, pp. 1-4.
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John, AR, Singh, AK, Gramann, K, Liu, D & Lin, C-T 2024, 'Prediction of cognitive conflict during unexpected robot behavior under different mental workload conditions in a physical human–robot collaboration', Journal of Neural Engineering, vol. 21, no. 2, pp. 026010-026010.
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Abstract Objective. Brain–computer interface (BCI) technology is poised to play a prominent role in modern work environments, especially a collaborative environment where humans and machines work in close proximity, often with physical contact. In a physical human robot collaboration (pHRC), the robot performs complex motion sequences. Any unexpected robot behavior or faulty interaction might raise safety concerns. Error-related potentials, naturally generated by the brain when a human partner perceives an error, have been extensively employed in BCI as implicit human feedback to adapt robot behavior to facilitate a safe and intuitive interaction. However, the integration of BCI technology with error-related potential for robot control demands failure-free integration of highly uncertain electroencephalography (EEG) signals, particularly influenced by the physical and cognitive state of the user. As a higher workload on the user compromises their access to cognitive resources needed for error awareness, it is crucial to study how mental workload variations impact the error awareness as it might raise safety concerns in pHRC. In this study, we aim to study how cognitive workload affects the error awareness of a human user engaged in a pHRC. Approach. We designed a blasting task with an abrasive industrial robot and manipulated the mental workload with a secondary arithmetic task of varying difficulty. EEG data, perceived workload, task and physical performance were recorded from 24 participants moving the robot arm. The error condition was achieved by the unexpected stopping of the robot in 33% of trials. Main results. We observed a diminished amplitude for the prediction error negativity (PEN) and error positivity (Pe), indicating reduced error awareness with increasing mental workload. We further observed a...

Kim, S, Corah, M, Keller, J, Best, G & Scherer, S 2024, 'Multi-Robot Multi-Room Exploration With Geometric Cue Extraction and Circular Decomposition', IEEE Robotics and Automation Letters, vol. 9, no. 2, pp. 1190-1197.
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Krishnan, A, Thiyagarajan, K, Kodagoda, S & Bhattacharjee, M 2024, 'Wearable Flexible Temperature Sensor Suite for Thermal Tactile Perception', IEEE Sensors Journal, pp. 1-1.
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Larpruenrudee, P, Bennett, NS, Fitch, R, Sauret, E, Gu, Y & Islam, MS 2024, 'Investigation of metal hydride hydrogen storage performance using phase change materials', International Journal of Hydrogen Energy, vol. 60, pp. 996-1019.
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Le Gentil, C, Ouabi, O-L, Wu, L, Pradalier, C & Vidal-Calleja, T 2024, 'Accurate Gaussian-Process-Based Distance Fields With Applications to Echolocation and Mapping', IEEE Robotics and Automation Letters, vol. 9, no. 2, pp. 1365-1372.
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Li, T, Walker, P, Khonasty, R, van de Graaf, VA, Yelf, E, Zhao, L & Huang, S 2024, 'Robotic‐assisted burring in total hip replacement: A new surgical technique to optimise acetabular preparation', The International Journal of Medical Robotics and Computer Assisted Surgery, vol. 20, no. 1.
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AbstractBackgroundIn Total Hip replacement (THR) surgery, a critical step is to cut an accurate hemisphere into the acetabulum so that the component can be fitted accurately and obtain early stability. This study aims to determine whether burring rather than reaming the acetabulum can achieve greater accuracy in the creation of this hemisphere.MethodsA preliminary robotic system was developed to demonstrate the feasibility of burring the acetabulum using the Universal Robot (UR10). The study will describe mechanical design, robot trajectory optimisation, control algorithm development, and results from phantom experiments compared with both robotic reaming and conventional reaming. The system was also tested in a cadaver experiment.ResultsThe proposed robotic burring system can produce a surface in 2 min with an average error of 0.1 and 0.18 mm, when cutting polyurethane bone block #15 and #30, respectively. The performance was better than robotic reaming and conventional hand reaming.ConclusionThe proposed robotic burring system outperformed robotic and conventional reaming methods to produce an accurate acetabular cavity. The findings show the potential usage of a robotic‐assisted burring in THR for acetabular preparation.

Liu, D, Balaguer, C, Dissanayake, G & Kovac, M 2024, 'Preface', Infrastructure Robotics: Methodologies, Robotic Systems and Applications, p. xix.

Ma, W, Huang, S & Sun, Y 2024, 'Triplet-Graph: Global Metric Localization Based on Semantic Triplet Graph for Autonomous Vehicles', IEEE Robotics and Automation Letters, vol. 9, no. 4, pp. 3155-3162.
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Ninan, J, Clegg, S, Mahalingam, A & Sankaran, S 2024, 'Governance Through Trust: Community Engagement in an Australian City Rebuilding Precinct', Project Management Journal, vol. 55, no. 1, pp. 16-30.
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City rebuilding precincts are embedded in, surrounded by, and sometimes resisted or celebrated by stakeholders they impact. These projects require long-lasting relationships and loyalty from the community they serve, making trust a crucial factor. This article employs a case study approach and draws from both social exchange and circuit of power theories to understand the complex relationship between trust and governance. Three strategies emerged from the analysis: employing resources, building legitimacy, and creating a brand. These strategies and their interactions highlight how trust can act as a governance mechanism for more effective engagement with the project community.

Piyathilaka, L, Kodagoda, S, Thiyagarajan, K, Piccardi, M, Preethichandra, DMG & Izhar, U 2024, 'Learning Spatial Affordances From 3D Point Clouds for Mapping Unseen Human Actions in Indoor Environments', IEEE Access, vol. 12, pp. 868-877.
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Sankaran, S, Clegg, SR, Killen, CP, Smyth, H & Scales, J 2024, 'Enabling Collaborative Research in Project Management by Creating Gioia Data Structures as a Boundary Object', Project Management Journal, vol. 55, no. 3, pp. 281-296.
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This process article reports on the use of Gioia data structures as a visual boundary object in project management research. Gioia data structures work as effective boundary objects that span a research team’s geographical distance in a virtual setting as an artifact for promoting visual collaboration in project management research. We demonstrate the use of boundary objects as generative tools for cross-disciplinary teams to share a common design method. While boundary objects have been used in project management studies, we extend their use to support collaborative research in project management.

Seiler, KM, Kong, FH & Fitch, R 2024, 'Multi-Horizon Multi-Agent Planning Using Decentralised Monte Carlo Tree Search', IEEE Robotics and Automation Letters, vol. 9, no. 9, pp. 7715-7722.
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Usayiwevu, M, Sukkar, F, Yoo, C, Fitch, R & Vidal-Calleja, T 2024, 'Continuous planning for inertial-aided systems', Autonomous Robots, vol. 48, no. 8.
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AbstractInertial-aided systems require continuous motion excitation among other reasons to characterize the measurement biases that will enable accurate integration required for localization frameworks. This paper proposes the use of informative path planning to find the best trajectory for minimizing the uncertainty of IMU biases and an adaptive traces method to guide the planner towards trajectories that aid convergence. The key contribution is a novel regression method based on Gaussian Process (GP) to enforce continuity and differentiability between waypoints from a variant of the $$\hbox {RRT}^*$$ RRT ∗ planning algorithm. We employ linear operators applied to the GP kernel function to infer not only continuous position trajectories, but also velocities and accelerations. The use of linear functionals enable velocity and acceleration constraints given by the IMU measurements to be imposed on the position GP model. The results from both simulation and real-world experiments show that planning for IMU bias convergence helps minimize localization errors in state estimation frameworks.

Wang, H, Zhao, X, Huang, S, Li, Q & Liu, Y 2024, 'A branch-and-bound based globally optimal solution to 2D multi-robot relative pose estimation problems', Automatica, vol. 164, pp. 111654-111654.
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Wang, J, He, Y, Su, D, Itoyama, K, Nakadai, K, Wu, J, Huang, S, Li, Y & Kong, H 2024, 'SLAM-Based Joint Calibration of Multiple Asynchronous Microphone Arrays and Sound Source Localization', IEEE Transactions on Robotics, vol. 40, pp. 4024-4044.
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Wang, K, Ke, Y & Sankaran, S 2024, 'How Socially Sustainable Is the Institutional Care Environment in China: A Content Analysis of Media Reporting', Buildings, vol. 14, no. 9, pp. 2953-2953.
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The multiple changes in population, economy, and social structure have significantly impacted China’s traditional home-based elderly care and social welfare. The importance of institutional care is becoming increasingly prominent. One of the critical considerations for the development of institutional care is its social sustainability, which pursues the realization of human well-being and aims to bring about good quality of life. However, this issue has not received due attention. The purpose of this paper is to investigate the social sustainability of the institutional care environment. Based on stakeholder theory and content analysis, this research identified and discussed the problems of the institutional care environment mentioned in the news coverage on eight major Chinese portal websites. The results indicate that seven of the eight problems that employees, the elderly, and their relatives encounter in providing and receiving elderly care services in the institutional environment are related to social sustainability. Employees’ health and safety is a concern; they lack education and training opportunities and have been unequally treated in the employment process. The elderly’s psychological, physical, and safety needs should also be further satisfied. Unequal access to institutional care and the inaccessibility of elderly care institutions is another problem that needs to be solved urgently. These findings will help government departments and investors become aware of the issues and implement countermeasures to create a successful, socially sustainable institutional care environment. They can also provide valuable insights for the elderly and their relatives in choosing appropriate elderly care institutions.

Wang, K, Ke, Y & Sankaran, S 2024, 'The social pillar of sustainable development: Measurement and current status of social sustainability of aged care projects in China', Sustainable Development, vol. 32, no. 1, pp. 227-243.
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AbstractSocial sustainability, the social pillar of sustainable development, has had increasing influences in recent years. It pursues the realisation of human well‐being and focuses on satisfying human needs and improving the quality of life. Unfortunately, there is a lack of social sustainability research in the aged care sector. The definition and indicators for social sustainability in aged care projects in the Chinese context are unclear, let alone the status of its realisation. This study aimed to establish a social sustainability indicator framework for aged care projects in China. Two focus group meetings and two online Delphi surveys were conducted to finalise and evaluate the indicators. Three stakeholders, 10 social impacts, and 21 indicators were identified. The realisation status of 19 indicators needs to be improved, nine of which need special attention. The indicator framework established in this study will be an effective tool to enhance the understanding and measure the social sustainability of aged care projects. As the world's most populous country, China's experience can provide insights to other countries. Moreover, the findings have implications for understanding the social sustainability of other public service projects with social impact.

Wang, X, Thiyagarajan, K, Kodagoda, S & Sharma, C 2024, 'PIPE-CovNet+: A Hyper-Dense CNN for Improved Pipe Abnormality Detection', IEEE Sensors Letters, vol. 8, no. 4, pp. 1-4.
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Xu, H, Liu, H, Huang, S & Sun, Y 2024, 'C2L-PR: Cross-modal Camera-to-LiDAR Place Recognition via Modality Alignment and Orientation Voting', IEEE Transactions on Intelligent Vehicles, pp. 1-17.
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Young, MW, Webster, C, Tanis, D, Schurr, AF, Hanna, CS, Lynch, SK, Ratkiewicz, AS, Dickinson, E, Kong, FH & Granatosky, MC 2024, 'What does climbing mean exactly? Assessing spatiotemporal gait characteristics of inclined locomotion in parrots', Journal of Comparative Physiology A, vol. 210, no. 1, pp. 19-33.
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Zhang, S, Zhao, L, Huang, S, Wang, H, Luo, Q, Hao, Q & Stoyanov, D 2024, 'SLAM-TKA: Simultaneously Localising X-ray Device and Mapping Pins in Conventional Total Knee Arthroplasty', IEEE Transactions on Medical Robotics and Bionics, pp. 1-1.
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Bourahmoune, K, Ishac, K & Carmichael, M 1970, 'Fitness Activity Recognition Using a Novel Pressure Sensing Mat and Machine Learning for the Future of Accessible Training', Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial Intelligence, Thirty-Third International Joint Conference on Artificial Intelligence {IJCAI-24}, International Joint Conferences on Artificial Intelligence Organization, pp. 7197-7205.
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Physical inactivity is still a major problem contributing to a growing public health crisis despite a fast-expanding body of technological solutions and wellness research around fitness training. The inaccessibility of professional fitness training remains a leading cause of this gap for reasons encompassing socioeconomic factors, cultural and demographic barriers, and more recently the threat of global pandemics that disrupt traditional modes of staying physically active. Previous lines of work have explored using AI for fitness activity recognition from various sensing modalities such as computer vision, wearable sensors, and force and pressure sensors. However, these works are limited by their feasibility, deployability, and accessibility in real-world scenarios, in addition to the technical challenges faced by each modality for accurate and reliable activity recognition. In this paper, we propose an accessible system for gym activity recognition and correction focusing on foundational fitness activities using ML and a novel pressure sensing mat, and validate its deployability in a real-world use case in a natural gym setting. We present the detailed and previously under-investigated Centre of Pressure (COP) profile of four main gym activities in terms of several COP-related metrics specifically as targets for ML-based recognition tasks. Based on this, we identify COP displacement and COP balance measures as important features for ML-based recognition of these fitness activities for future research in this area. Furthermore, we compare the performance of several ML models in the activity recognition task, achieving 98.5% recognition accuracy using ML models suitable for real-time deployment. Finally, we demonstrate the feasibility of our system in a live real-world with use case in a natural gym environment.

Bourahmoune, K, Ishac, K & Carmichael, M 1970, 'Towards Robot to Human Skill Coaching: A ML-powered IoT and HRI Platform for Martial Arts Training', 2024 IEEE International Conference on Robotics and Automation (ICRA), 2024 IEEE International Conference on Robotics and Automation (ICRA), IEEE, pp. 853-859.
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Heon Lee, JJ, Yoo, C, Anstee, S & Fitch, R 1970, 'Multi-query TDSP for Path Planning in Time-varying Flow Fields', 2024 IEEE International Conference on Robotics and Automation (ICRA), 2024 IEEE International Conference on Robotics and Automation (ICRA), IEEE, pp. 7005-7011.
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Hull, R, Moratuwage, D, Scheide, E, Fitch, R & Best, G 1970, 'Communicating Intent as Behaviour Trees for Decentralised Multi-Robot Coordination', 2024 IEEE International Conference on Robotics and Automation (ICRA), 2024 IEEE International Conference on Robotics and Automation (ICRA), IEEE, pp. 7215-7221.
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Jayasuriya, M, Hu, G, Le, DDK, Ang, K, Sankaran, S & Liu, D 1970, 'A 3D Vector Field and Gaze Data Fusion Framework for Hand Motion Intention Prediction in Human-Robot Collaboration', 2024 IEEE International Conference on Robotics and Automation (ICRA), 2024 IEEE International Conference on Robotics and Automation (ICRA), IEEE, pp. 5637-5643.
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Nguyen, DDK, Paul, G & Alempijevic, A 1970, 'Decentralized multi-phase formation control for cattle herding', 2024 IEEE International Conference on Robotics and Automation (ICRA), 2024 IEEE International Conference on Robotics and Automation (ICRA), IEEE, Yokohama, Japan, pp. 17948-17953.
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Rees, N, Thiyagarajan, K & Kodagoda, S 1970, 'Robotic Guide Dog for Real-time Indoor Object Detection and Classification with Localization', 2024 IEEE Applied Sensing Conference (APSCON), 2024 IEEE Applied Sensing Conference (APSCON), IEEE, pp. 1-4.
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Thiyagarajan, K & Kodagoda, S 1970, 'Sensing Acid Permeation Conditions of Wastewater Pipe Coatings for Long-term Quality Assurance', 2024 IEEE Applied Sensing Conference (APSCON), 2024 IEEE Applied Sensing Conference (APSCON), IEEE, pp. 1-4.
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Wang, Q, Wang, Z, Carmichael, MG, Liu, D & Lin, C-T 1970, 'Comparison of Rating Scale and Pairwise Comparison Methods for Measuring Human Co-worker Subjective Impression of Robot during Physical Human-Robot Collaboration', 2024 IEEE International Conference on Robotics and Automation (ICRA), 2024 IEEE International Conference on Robotics and Automation (ICRA), IEEE, pp. 907-913.
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Wang, Z & Carmichael, MG 1970, 'Exploring the Effect of Base Compliance on Physical Human-Robot Collaboration', 2024 IEEE International Conference on Robotics and Automation (ICRA), 2024 IEEE International Conference on Robotics and Automation (ICRA), IEEE, pp. 3198-3204.
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Yi, B, Fan, Y & Liu, D 1970, 'A Novel Model for Layer Jamming-based Continuum Robots', 2024 IEEE International Conference on Robotics and Automation (ICRA), 2024 IEEE International Conference on Robotics and Automation (ICRA), IEEE, pp. 12727-12733.
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Liu, D, Balaguer, C, Dissanayake, G & Kovac, M 2024, 'Infrastructure Robotics: Methodologies, Robotic Systems and Applications', pp. 1-404.
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Infrastructure Robotics Illuminating resource presenting commonly used robotic methodologies and technologies, with recent developments and clear application examples across different project types Infrastructure Robotics presents state-of-the-art research in infrastructure robotics and key methodologies that enable the development of intelligent robots for operation in civil infrastructure environments, describing sensing, perception, localization, map building, environmental and operation awareness, motion and task planning, design methodologies, robot assistance paradigms, and physical human-robot collaboration. The text also presents many case studies of robotic systems developed for real-world applications in maintaining various civil infrastructures, including steel bridges, tunnels, underground water mains, underwater structures, and sewer pipes. In addition, later chapters discuss lessons learned in deployment of intelligent robots in practical applications overall. Infrastructure Robotics provides a timely and thorough treatment of the subject pertaining to recent developments, such as computer vision and machine learning techniques that have been used in inspection and condition assessment of critical civil infrastructures, including bridges, tunnels, and more. Written by highly qualified contributors with significant experience in both academia and industry, Infrastructure Robotics covers topics such as: • Design methods for application of robots in civil infrastructure inspired by biological systems including ants, inchworms, and humans • Fundamental aspects of research on intelligent robotic co-workers for human-robot collaborative operations • The ROBO-SPECT European project and a robotized alternative to manual tunnel structural inspection and assessment • Wider context for the use of additive manufacturing techniques on construction sites Infrastructure Robotics is an essential resource for researchers, engineers, and graduate students i...

Pratt, S, Heggart, K, Christensen, PH & Sankaran, S 2024, 'Fostering Participatory Action Research in Higher Degree Research Settings through a Transdisciplinary Peer-mentoring Collaborative', Springer Science and Business Media LLC.
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Usayiwevu, M, Sukkar, F, Yoo, C, Fitch, R & Vidal-Calleja, T 2024, 'Continuous Planning for Inertial-Aided Systems', Research Square Platform LLC.
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Wang, J, He, Y, Su, D, Itoyama, K, Nakadai, K, Wu, J, Huang, S, Li, Y & Kong, H 2024, 'SLAM-based Joint Calibration of Multiple Asynchronous Microphone Arrays and Sound Source Localization'.

Zhao, L, Wang, Y & Huang, S 2024, 'Occupancy-SLAM: Simultaneously Optimizing Robot Poses and Continuous Occupancy Map'.