Service robot for the elderly

For the past ten years, the Intelligent Robotics Laboratory (IRL) at Vanderbilt University has been developing service robots that interact naturally, closely and safely with human beings. Two main issues for research have arisen from this prior work. The first is how to achieve a high level of interaction between the human and robot. The result has been the philosophy of human directed local autonomy (HuDL), a guiding principle for research, design, and implementation of service robots. The human‐robot relationship we seek to achieve is symbiotic in the sense that both the human and the robot work together to achieve goals, for example as aids to the elderly or disabled. The second issue is the general problem of system integration, with a specific focus on integrating humans into the service robotic system. This issue has led to the development of the Intelligent Machine Architecture (IMA), a novel software architecture specifically designed to simplify the integration of the many diverse algorithms, sensors, and actuators necessary for intelligent interactive service robots.

In the Intelligent Robotics Laboratory at Vanderbilt University, we seek to develop service robots with a high level of social intelligence and interactivity. In order to achieve this goal, we have identified two main issues for research. The first issue is how to achieve a high level of interaction between the human and the robot. This has lead to the formulation of our philosophy of Human Directed Local Autonomy (HuDL), a guiding principle for research, design, and implementation of service robots. The motivation for integrating humans into a service robot system is to take advantage of human intelligence and skill. Human intelligence can be used to interpret robot sensor data, eliminating computationally expensive and possibly error-prone automated analyses. Human skill is a valuable resource for trajectory and path planning as well as for simplifying the search process. In this article, we present our plans for integrating humans into a service robot system. We present our paradigm for human-robot interaction, HuDL. The second issue is the general problem of system integration, with a specific focus on integrating humans into the service robotic system. This work has lead to the development of the Intelligent Machine Architecture (IMA), a novel software architecture that has been specifically designed to simplify the integration of the many diverse algorithms, sensors, and actuators necessary for socially intelligent service robots. Our testbed system is described, and some example applications of HuDL for aids to the physically disabled are given. An evaluation of the effectiveness of the IMA is also presented.

Service robot has its challenge to adapt on new tasks based on instruction or environment. Such conditions need to reconfigure or reorganize to obtain new system capabilities. However, most common service robot, especially the one that gives services to help human to deliver food or non medical stuffs in an elderly house, suffers on its task flexibility. Unlike a human, robot system needs to be reconfigured to have a new task which may interrupt its services because of this event. To this, we need a technique to handle adaptive tasks that is flexible to change the robot tasks that do not create delay. Dynamic software product line provides a mechanism to reconfigure a system to have different capabilities based on the core assets of the system, such as software that supports and controls the hardware components in a robotic system. In this work, we make use of the dynamic software product line to create a flexible method that enables a service robot to adapt on its new tasks. In order to define the change of tasks, we model the transformation of task using a transition state which has constraints as a trigger. Other than that, the request of change may also have resulted by forcing an interrupt mechanism. To demonstrate the capability of our approach, the proof of concept using Robotic Operating System will be presented.

The construction of a smart autonomous mobile robot system that can operate in an anonymous environment can be difficult. Building an autonomous mobile robot requires collecting data from sensors and cameras in order to recognize the surrounding environment, get knowledge of existing landmarks, and figure out its position and orientation. Many research studies have been carried out in recent years providing algorithms for achieving autonomous motion of mobile robot systems and object detection. The most common platform utilized for robot motion design is ROS (Robot Operating System) and for object detection YOLO (You Only Look Once) is a common choice. Additionally, the autonomous system needs motion planning in a systematic way to avoid obstacles by using LIDAR or other sensing methods generating the feedback signals required for control of motion around occupied spaces. One of the most effective and versatile feedback systems for mobile robot control can be constructed using visual feedback, which relies on a high-resolution camera that processes the image in real-time and the result is fed back to the control system for decision making. Visual feedback can be employed alone without sensors for feedback control of autonomous mobile robots, and it can be used for multiple tasks like path planning, obstacle avoidance, object detection, object recognition in addition to motion control. In this research, results of design and construction of an autonomous mobile rescue robot for finding victims through video data are presented. It is aimed to find victims via applying video as a data collection and feedback generation tool in the autonomous mobile robot control system. The visual feedback and YOLO v3 are used not only for finding victims but also for motion control. Our autonomous mobile robot is designed to move smoothly to the victim's direction and avoids obstacles by using ROS Global Planner. The robot is tested in multiple scenarios in different locations, various obstacle and victim numbers, and satisfactory results with good performances are obtained.

The share of service robots is increasing. Large number of those robots are the professional service robots such as customer service and logistics robots. One of the main requirements of these robots is the ability to navigate in an environment where a GPS system cannot be used. This article investigates existing methods for indoor localization and navigation. It proposes a new complete approach. This approach does not require the integration of a new indoor navigation system. Instead, the existing 24/7 video surveillance infrastructure, as well as the capabilities of the service robot, are considered. The proposed approach can reduce both the initial cost of integrating the robotic system as well as the maintenance costs. Subsequent maintenance can be done entirely remotely. The suggested approach is validated experimentally on a mobile robot.

Path planning aims to enable autonomous robots to navigate safely and efficiently from a starting point to a target point in challenging and dynamic environments. Path planning in robotics is highly significant and still an ongoing subject of research. The increasing use of robots in various applications such as industrial automation, service robotics, and autonomous vehicles has brought forth the need for reliable and efficient path planning algorithms. The inherent capability of Voronoi diagrams to partition space based on proximity makes them an effective framework for research in path planning. Ant colony optimization, a bio-inspired optimization technique, is based on the foraging behavior of ants and is commonly employed to address the traveling salesman problem and various other combinatorial optimization problems. A hybrid method was adopted in this study by combining a Voronoi diagram and an ant colony algorithm. To create paths for the robot where it can stay as far away from obstacles as possible, a Voronoi diagram was utilized. Additionally, to find the shortest path from the starting point to the destination among these paths, ant colony optimization was employed. The main contribution of the study lies in the combination of the Voronoi diagram for obstacle avoidance and ant colony optimization for finding the optimal path. The combination of these techniques makes an effective contribution to robotic path planning by focusing on ensuring safety by avoiding obstacles while optimizing the shortest path. Experimental studies show that the hybrid method produces successful results for the desired purpose.

A* algorithm is a simple, scalable, and high reliable algorithm in the path planning algorithm. For the problem that service robots have high real-time characteristic and have short calculating time for algorithm, the A* algorithm is applied to the local path planning of service robots. To further improve the response speed of the algorithm, A* algorithm is improved by adjusting selection mechanism of the open update node choice and introducing the weight of Heuristics. The simulation and experimental results show that this new method has good planning performance. Adopting this new method can significantly reduce the searching time of algorithm and meet the high real-time need of service robots.

Purpose This review paper aims to provide a comprehensive review of Dubins robot path planning, which has become increasingly important in mobile robotics, autonomous vehicles and industrial applications. The authors identify key developments, analyze existing approaches and highlight the fundamental constraints, algorithms and future opportunities involving curvature-constrained, forward-only path planning. Design/methodology/approach The review consists of three parts: basic Dubins theory, seven decades of development and future opportunities. In the first part, the authors summarize problem formulations and representative computational strategies/algorithms. In the second part, the seventy years of development are divided into four stages, with each stage summarizing developments in important topics such as point-to-point planning, obstacle avoidance and variable speed planning. In addition, the authors analyze current challenges and evaluate recent extensions in cooperative, real-time and learning-based planning frameworks. Findings Dubins path planning has evolved from simple analytical models to complex multirobot and dynamic scenarios. While exact solutions exist for basic tasks, the scalability, obstacle constraints and real-time responsiveness remain active challenges. Promising future directions include integrating machine learning for adaptive planning, and extending to Reeds–Shepp and nonholonomic systems in three-dimensional environments. Originality/value This review offers a structured and in-depth overview of path planning for Dubins robots, connecting core theoretical concepts with the latest developments and real-world implementations. Unlike prior surveys that roughly treat general nonholonomic planning or sampling-based methods, this paper for the first time emphasizes the curvature-constrained planning, especially under the Dubins constraints. By identifying underexplored areas such as dynamic environments, real-time applications, this review offers actionable insights and future research directions valuable to both researchers and practitioners in mobile and industrial robots.

PurposeThe purpose of this paper is to put forward a rolling assistant robot with two rolling modes, and the multi-mode rolling motion strategy with path planning algorithm, which is suitable to this multi-mode mobile robot, is proposed based on chessboard-shaped grid division (CGD).Design/methodology/approachBased on the kinematic analysis and motion properties of the mobile parallel robot, the motion strategy based on CGD path planning algorithm of a mobile robot with two rolling modes moving to a target position is divided into two parts, which are local self-motion planning and global path planning. In the first part, the mobile parallel robot can move by switching and combining the two rolling modes; and in the second part, the specific algorithm of the global path planning is proposed according to the CGD of the moving ground.FindingsThe assistant robot, which is a novel 4-RSR mobile parallel robot (where R denotes a revolute joint and S denotes a spherical joint) integrating operation and rolling locomotion (Watt linkage rolling mode and 6R linkage rolling mode), can work as a moving spotlight or worktable. A series of simulation and prototype experiment results are presented to verify the CGD path planning strategy of the robot, and the performance of the path planning experiments in simulations and practices shows the validation of the path planning analysis.Originality/valueThe work presented in this paper is a further exploration to apply parallel mechanisms with two rolling modes to the field of assistant rolling robots by proposing the CGD path planning strategy. It is also a new attempt to use the specific path planning algorithm in the field of mobile robots for operating tasks.

The paper discusses the potential of assistive service robots to support disabled and elderly people. It shows that they have considerable untapped potential in this area, but also that inappropriate implementations could increase isolation, reduce independence and lead to users feeling as though they are under surveillance. The main body of the paper presents an overview of existing applications and discusses their benefits and potential problems. This is organized by an extension of the common classification into socially and physically assistive robots by the two categories of sensory assistive and mixed assistance robots. Another more detailed classification is also presented. This discussion is introduced by an overview of many of the technological components of smart mobile robots. It is followed by a discussion of user acceptance. The problems of existing models based on either solely positive or solely negative factors are noted and a model containing both types of factors is proposed. The need for continuing research is noted and various proposals are made.

In recent years, not only industrial robot used in the manufacturing site, the use of a service robot for performing alternate or supplementary work of humans is increasingly robot. So we aim to build the system of mobile service robot with a seamless navigable sensor integrated system regardless of the indoor and outdoor for Large Scale facility using the internal sensor and external sensor, environment map information, the indoor positioning system. In this research, using the rotary encoder to the internal sensor, and using the LRF to external sensor, using the IMES for positioning system to develop an autonomous mobile robot system. We report the results of the evaluation by the running experiment.

Body activity interaction plays an essential role in the field of intelligent robots. In this paper, we design a body activity interaction system for a service robot. In order to realize body activity interaction, the Microsoft Kinect is utilized to capture owner body movements and provide input signals of the action recognition module. Based on the RGBD and skeleton information from Microsoft Kinect, action recognition module can analyze meaning of owner body movements effectively and send orders to service robot quickly. Besides, kinematics model of the service robotic arm is built and the motion planning on the joint space is also executed. Finally, service robot receives orders and conducts robotic arm to implement handshaking or hand waving. Extensive experiments illustrate the correctness and effectiveness of our developed body activity interaction system on the platform of service robot.

A robotic service framework supporting automated integration of ubiquitous sensors and devices

Aiming at the navigation of indoors autonomous mobile service robots, we propose a mobile robot coordinate positioning solution based on ultrasonic navigation with environment map. With the low cost sensor and simple algorithm, the service robot can obtain higher accuracy current position coordinate, and then reach the working position. This paper introduces the positioning principle and implementation of this method in detail.

Recently, stereovision has appeared in robotics as a source of information for real-time mapping and path planning. In this paper, an intelligent motion system for mobile robots is designed and implemented using stereovision. The proposed system uses stereovision as a primary method for sensing the environment, and the system is able to navigate intelligently in an indoor environment with varying degrees of obstacle complexity. It creates noiseless and high-confidence 3D point clouds and uses these point clouds as an input for the mapping and path-planning modules. The proposed system was built by developing, enhancing, and integrating various techniques, modules and algorithms. The Stereovision-based Path-planning module is the integration of three main enhanced techniques: (1) the multi-baseline multi-view stereovision filter (MMSVF), (2) accurate floor detection and segmentation (AFDS), and (3) the intelligent gazing module (IGM). This Stereovision-based Path planning (MMSVF, IGM, and AFDS) was integrated with the Fuzzy Logic Motion Controller (FLMC). All techniques, modules and algorithms are implemented using a multi-threaded and client---server-based architecture. To prove the viability and robustness of our proposed system, we have integrated all components of the system into a fully functional mobile robot navigation system. We compared the performance of the main modules with that of similar modules in the literatures, and showed that our modules had better performance. Testing the whole system is more important than just testing each module individually. To the best of our knowledge, the literatures lack such testing. Hence, in this paper we present the performance of our complete integrated system in different environments using different parameters and different architectures.