The use of blockchain in cyber-physical systems, such as robotics, is an area with immense potential to address many shortcomings in robotic coordination and control. In traditional swarm robotic applications, where homogeneous robots are utilized, it is possible to replace a robot if it malfunctions, and it can be assumed that all robots are interchangeable. However, in many real-world applications spanning from search and rescue missions to future household robotic appliances, heterogeneous robots will need to work together with the other robots and human agents to achieve specific tasks. Nevertheless, no such system exists. Therefore, we propose a system that utilizes a token economy for robotic agents that makes agents responsive to token acquisition as an incentive for collaboration in achieving a given task. The economy enables the system to self-govern, even under Byzantine and adversarial settings. We further incorporate a novel subcontracting framework within a blockchain environment to allow the robotic agents to efficiently and cost-effectively perform complex jobs requiring multiple agents with various capabilities. We conducted a thorough evaluation of the system in a prototype warehouse application scenario, and the results are promising. 
                        more » 
                        « less   
                    
                            
                            Managing Collaborative Tasks within Heterogeneous Robotic Swarms using Swarm Contracts
                        
                    
    
            The growing number of applications in Cyber-Physical Systems (CPS) involving different types of robots while maintaining interoperability and trust is an ongoing challenge faced by traditional centralized systems. This paper presents what is, to the best of our knowledge, the first integration of the Robotic Operating System (ROS) with the Ethereum blockchain using physical robots. We implement a specialized smart contract framework called “Swarm Contracts” that rely on blockchain technology in real-world applications for robotic agents with human interaction to perform collaborative tasks while ensuring trust by motivating the agents with incentives using a token economy with a self-governing structure. The use of open-source technologies, including robot hardware platforms such as TurtleBot3, Universal Robot arm, and ROS, enables the ability to connect a wide range of robot types to the framework we propose. Going beyond simulations, we demonstrate the robustness of the proposed system in real-world conditions with actual hardware robots. 
        more » 
        « less   
        
    
    
                            - PAR ID:
- 10388865
- Date Published:
- Journal Name:
- IEEE International Conference on Decentralized Applications and Infrastructures (DAPPS)
- Page Range / eLocation ID:
- 48 to 55
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
- 
            
- 
            Long-term deployment of a fleet of mobile robots requires reliable and secure two-way communication channels between individual robots and remote human operators for supervision and tasking. Existing open-source solutions to this problem degrade in performance in challenging real-world situations such as intermittent and low-bandwidth connectivity, do not provide security control options, and can be computationally expensive on hardware-constrained mobile robot platforms. In this paper, we present Robofleet, a lightweight open-source system which provides inter-robot communication, remote monitoring, and remote tasking for a heterogenous fleet of ROS-enabled service-mobile robots that is designed with the practical goals of resilience to network variance and security control in mind.Robofleet supports multi-user, multi-robot communication via a central server. This architecture deduplicates network traffic between robots, significantly reducing overall network load when compared with native ROS communication. This server also functions as a single entrypoint into the system, enabling security control and user authentication. Individual robots run the lightweight Robofleet client, which is responsible for exchanging messages with the Robofleet server. It automatically adapts to adverse network conditions through backpressure monitoring as well as topic-level priority control, ensuring that safety-critical messages are successfully transmitted. Finally, the system includes a web-based visualization tool that can be run on any internet-connected, browser-enabled device to monitor and control the fleet.We compare Robofleet to existing methods of robotic communication, and demonstrate that it provides superior resilience to network variance while maintaining performance that exceeds that of widely-used systems.more » « less
- 
            This paper proposes a Priority-driven Accelerator Access Management (PAAM) framework for multi-process robotic applications built on top of the Robot Operating System (ROS) 2 middleware platform. The framework addresses the issue of predictable execution of time- and safety-critical callback chains that require hardware accelerators such as GPUs and TPUs. PAAM provides a standalone ROS executor that acts as an accelerator resource server, arbitrating accelerator access requests from all other callbacks at the application layer. This approach enables coordinated and priority-driven accelerator access management in multi-process robotic systems. The framework design is directly applicable to all types of accelerators and enables granular control over how specific chains access accelerators, making it possible to achieve predictable real-time support for accelerators used by safety-critical callback chains without making changes to underlying accelerator device drivers. The paper shows that PAAM also offers a theoretical analysis that can upper bound the worst-case response time of safety-critical callback chains that necessitate accelerator access. This paper also demonstrates that complex robotic systems with extensive accelerator usage that are integrated with PAAM may achieve up to a 91% reduction in end-to-end response time of their critical callback chains.more » « less
- 
            In social robotics, a pivotal focus is enabling robots to engage with humans in a more natural and seamless manner. The emergence of advanced large language models (LLMs) has driven significant advancements in integrating natural language understanding capabilities into social robots. This paper presents a system for speech-guided sequential planning in pick and place tasks, which are found across a range of application areas. The proposed system uses Large Language Model Meta AI (Llama3) to interpret voice commands by extracting essential details through parsing and decoding the commands into sequential actions. These actions are sent to DRL-VO, a learning-based control policy built on the Robot Operating System (ROS) that allows a robot to autonomously navigate through social spaces with static infrastructure and crowds of people. We demonstrate the effectiveness of the system in simulation experiment using Turtlebot 2 in ROS1 and Turtlebot 3 in ROS2. We conduct hardware trials using a Clearpath Robotics Jackal UGV, highlighting its potential for real-world deployment in scenarios requiring flexible and interactive robotic behaviors.more » « less
- 
            This paper describes two exemplary projects on physical ROS-compatible robots (i.e., Turtlebot3 Burger and Waffle PI) for an undergraduate robotics course, aiming to foster students’ problem-solving skills through project-based learning. The context of the study is a senior-level technical elective course in the Department of Computer Engineering Technology at a primarily undergraduate teaching institution. Earlier courses in the CET curriculum have prepared students with programming skills in several commonly used languages, including Python, C/C++, Java, and MATLAB. Students’ proficiency in programming and hands-on skills makes it possible to implement advanced robotic control algorithms in this robotics course, which has a 3-hour companion lab session each week. The Robot Operating System (ROS) is an open-source framework that helps developers build and reuse code between robotic applications. Though mainly used as a research platform, instructors in higher education take action in bringing ROS and its recent release of ROS 2 into their classrooms. Our earlier work controlled a simulated robot via ROS in a virtual environment on the MATLAB-ROS-Gazebo platform. This paper describes its counterparts by utilizing physical ROS-compatible autonomous ground robots on the MATLAB-ROS2-Turtlebot3 platform. The two exemplary projects presented in this paper cover sensing, perception, and control which are essential to any robotic application. Sensing is via the robot’s onboard 2D laser sensor. Perception involves pattern classification and recognition. Control is shown via path planning. We believe the physical MATLAB-ROS2-Turtlebot3 platform will help to enhance robotics education by exposing students to realistic situations. It will also provide opportunities for educators and students to explore AI-facilitated solutions when tackling everyday problems.more » « less
 An official website of the United States government
An official website of the United States government 
				
			 
					 
					
 
                                    