The research foci of the More Than One Robotics laboratory are in intersection of three research themes: Multi-Robot Systems, Human-Robot Interaction and Collaboration, and Modular Robotics

We exploit communication and interaction of human and robotic agents to develop systems theory and algorithms for the complex intelligent systems that can be evaluated through mathematical modelling, simulation, and real-world experiments. 

Our research works has been funded by NSERC (DG, Engage, Connect), MITACS, DND-IDEAS and in collaboration with industrial partners such as A&K Robotics, Quanser, and Clearpath Robotics. 


A Heterogeneous Swarm of Mobile Robots as the First Responder for Search and Rescue in Hazardous Environments

Sponsored by DND-IDEaS program 

The main objective of this collaborative project between University of Prince Edward Island (UPEI), University of Ottawa (uOttawa) and Clearpath Robotics Inc. is to design and develop a heterogeneous swarm of mobile robots with capacities of fast deployment and displacement as the first responder in hazardous environments. The heterogeneous swarm consists of a mothership and numerous child robots that are capable of fast deploying and dispersing from the mother’s deck for exploration and victim identification and self-organizing an ad-hoc network for data gathering and communication. To achieve this goal, we are going to develop a novel hierarchical distributed control method for controlling global network integrity preservation of the heterogeneous swarm of mobile robots (SWARM). A hierarchical distributed control (HDC) is an integration of distributed node control and distributed connectivity control. The distributed node control is developed under a mobility constraint to guarantee global network integrity preservation of SWARM while the distributed connectivity control is built up for local connectivity minimization allowing SWARM to expand its global network coverage.

Towards A Unified Framework of Socially Aware Mobile Robot Navigation: From Human Physical Safety and Psychological Comfort to Robots’ Contextual and Cultural Awareness

Sponsored by NSERC-DG

The ability to autonomously navigate in unknown dynamic environments becomes crucial for mobile service robots when employed in human-robot shared workplaces such as shopping malls, airports, and offices. If we wish to deploy a mobile service robot in a social environment, the first and most important issue beyond any applicable service is that the robot must safely and socially avoid not only regular obstacles but also humans while navigating to a given destination. Towards a society of human and robot co-workers where mobile service robots work with humans on cooperative tasks, such robots should possess human-like characteristics at the security level consisting of human physical safety and psychological comfort, and at the cognitive level consisting of contextual and cultural awareness. Human physical safety - the first and most obvious issue - is about maintaining a minimum physical distance between the robot and humans. Human psychological comfort implies that the mobile robot is not allowed to cause stress and discomfort to humans during its navigation and interaction. Contextual awareness emphasizes how the robot’s behaviours are socially adaptable to different social contexts, e.g., approaching dynamic human group and human-object interaction, or navigating in chaotic and crowded environments. Cultural awareness stresses the robot’s situational awareness capability of human culture, e.g., polite and respectful behaviours. Such security and cognitive levels set the milestones on the roadmap of developing mobile service robots to become robotic co-workers in human-robot interactive environments. My long-term vision of this research program is to develop a unified framework of socially aware robot navigation enabling mobile service robots to guarantee not only (1) human physical safety and (2) psychological comfort but also to enhance robot’s (3) contextual and (4) cultural awareness in human-robot interactive environments. Mobile service robots equipped with such a unified framework will play the key role as human counterparts and caregivers for various complex tasks in either industrial or daily-life settings.

Advanced Sensor Fusion for Visual Inertial Odometry and Object Identification in Dynamic Indoor Environments

Sponsored by NSERC, MITACS and A&K Robotics Inc. 

The A&K Robotics Inc. – R&D company – is designing and building mobile robots for light industrial work. They focus on developing intelligent mobile robots for multimodal service tasks in dynamic indoor environments. During the technological development of mobile robot systems, A&K robotics has incorporated cutting edge robotics research into their newest systems. However, due to the growing need for more intelligent decision making in increasingly dynamic environments and general demand for decreased cost, new methodologies that push the boundaries of techniques that exist in literature must be developed. At present, few complete works exist in navigating a mobile robot and identifying popular objects in a dynamic indoor environment using inexpensive sensors. Hence, the primary aim of this collaborative research project between the UPEI team and the A&K Robotics is to produce advanced sensor fusion methods for high accuracy visual inertial odometry applied for robot navigation systems and object detection and identification used environment monitoring, object manipulation and handling. We expect that the developed ROS-based software packages of visual inertial odometry and object identification will help to accelerate the A&K Robotics’s system integration, promotion and commercialization plans.

Socially Aware Mobile Robot Navigation System - An Open-source Software Platform 

Sponsored by NSERC and Quanser Inc. 

Quanser – a Canadian company specializing on advanced education and research equipment and toolsets – is currently expanding their production of robotic systems. During the technological development of the robotic systems, Quanser has incorporated cutting edge sensors and on-board computing systems on their mobile robot platforms. However, the software framework of the robots still relies on commercial platforms while open-source operating systems (e.g. Robot Operating System - ROS) and shared codes (e.g. Github) are widely used by robotics communities. An open-source software platform is urgently required for Quanser’s robot systems, especially towards their potential customers in education and research. The aim of this project is to design and develop an open-source software platform for socially aware mobile robot navigation. We expect that the developed ROS-based software platform will accelerate Quanser’s strategic plan in development and commercialization of this product. 


SENSAFE: Human Safety in Human-Robot Cooperation (UBD/PNC2/2/RG/1(259))
Researchers: Tung Xuan Truong, Trung Dung Ngo (PI)

A challenge of applying mobile robots to our daily life is safety: how to ensure that robots will reliably assist human, not harm them. In SENSAFE we suppose that human and service robots share the workspace, and implicitly or explicitly cooperate to finish assigned tasks. Risks of human in the workspace essentially come from the attack of robots caused by its functioning failures or misunderstanding between human and the robots. Based on the general close-loop-model of robotic 
systems, “sense-think-act”, “sense” is the first component that plays a role as perceptual, representational, and reasoning input to the sequence “think-act”, thus “sense” is the essential reason causing the malfunction of the robots due to uncertain conditions of the working environment and unpredictable actions of human co-workers.
         We propose a research method, called as experiment-based knowledge (empirical knowledge) on how to determine modes of operation and control of robots according to safeguarding and clearance between the robots and human in the human-life workspace based on the robot’s “sense”. The objective of SENSAFE is to develop experiments for assessing safety levels of human co-working in the shared workspace. The outcome of this project is to contribute to: 1) society in terms of deeper understanding of human risks in the manner of human protection and injury minimization when sharing workspace with service robots; 2) industry in terms of technological standards for development of service robots working in human shared workspace; 3) science in terms of techniques and algorithms for safe human-robot interaction/cooperation

Two-stage Optimisation of Communication Throughput in Large-scale Mobile Sensor Networks

Researchers: Adnan Fida, Pg. Jaidi Tuah, Trung Dung Ngo (PI)

We concern the development of algorithms for optimising the network topology and the information link capacity of large-scale mobile sensor networks. The bottlenek of the network must be found for the cooperative control of node mobility leading to improvement of the network capacity and communication throughputs. Both centralized and decentralised solutions are developed for comparative analysis. A simulator is built for implementation and validation of the proposed algorithms. The real-work experiments will be conducted on the mobile robot platforms available in the lab for real data analyses and demonstrations. 

Bio-inspired Heterogeneous Swarm of Mobile Robots for Fast Deployment and Exploration

We develop a swarm of mobile robots can be applied in many applications including exploration and mapping, surveillance and reconnaissance, patrol and monitoring, victim identification in hazardous environments. More advantageous than a single robot, a robot swarm should be sent into human impassible areas for cooperative exploration and data gathering. Such emergency response services require a strategy allowing fast deployment and exploration of mobile robots. This work presents a strategic method and technological solution to emergency response services by inspiration from the Kangaroo family. We describe a semi-autonomous system consisting of a Kangaroo “mother” robot carrying a number of “child” robots sitting on her “pouch”. Depending on situation, the mother allows the children to jump out exploration, data gathering, or call them back for data collection and displacement.