Learning from Demonstration with State Based Obstacle Avoidance for Mobile Service Robots

2013 ◽  
Vol 394 ◽  
pp. 448-455 ◽  
Author(s):  
A.A. Nippun Kumaar ◽  
T.S.B. Sudarshan
Keyword(s):  
Obstacle Avoidance ◽  
Service Robots ◽  
Service Robot ◽  
Mobile Service ◽  
Learning From Demonstration ◽  
Service Robotics ◽  
Mobile Service Robots ◽  
Novel Approaches ◽  
User Friendly ◽  
Mobile Service Robot

Learning from Demonstration (LfD) is a technique for teaching a system through demonstration. In areas like service robotics the robot should be user friendly in terms of coding, so LfD techniques will be of greater advantage in this domain. In this paper two novel approaches, counter based technique and encoder based technique is proposed for teaching a mobile service robot to navigate from one point to another with a novel state based obstacle avoidance technique. The main aim of the work is to develop an LfD Algorithm which is less complex in terms of hardware and software. Both the proposed methods along with obstacle avoidance have been implemented and tested using Player/Stage robotics simulator.

Control of a Mobile Service Robot Using Human Evaluations of Task-related Movement Patterns

2000 ◽  
Vol 12 (6) ◽  
pp. 689-701
Author(s):  
John Travis Butler ◽  
◽  
Arvin Agah ◽  
Keyword(s):  
Human Subjects ◽  
Service Robots ◽  
Service Robot ◽  
Future Application ◽  
Mobile Service ◽  
Body Design ◽  
Mobile Service Robots ◽  
User Friendly ◽  
New Generation ◽  
Robot Body

An important future application of robotics will be the utilization of mobile service robots in homes and offices, assisting people with their daily chores. Above all, these robots must be safe to use. In addition, service robots must be designed to be effective, productive, and user-friendly. In order for people to accept and use these robots, the robots must behave in a manner acceptable to humans. The intelligent control of service robots must take into. account the effects of robot behaviors on people. This paper focuses on the interactions between humans and mobile service robots, studying how people respond to a variety of robot behaviors as the robot performs certain tasks. Since different people could react differently to service robots, this paper reports on the effects of users' gender, age, technical background, and robot body preference on the responses to robot behaviors. The robot behaviors include the robot approaching a human, the robot avoiding a human while passing, and the robot performing non-interactive behaviors. The level of comfort the robot caused human subjects was analyzed according to the effects of robot speed, robot distance, and robot body design. It is hoped that information gained from human factor studies can be used to obtain a better understanding of acceptability of service robots by different people, resulting in the design and development of more effective intelligent controllers for service robots in the coming new generation.

Automatically Annotated Mapping for Indoor Mobile Robot Applications

2012 ◽  
Author(s):  
Ali Gürcan Özkil ◽  
Thomas Howard
Keyword(s):  
Mobile Robot ◽  
Practical Method ◽  
Service Robots ◽  
Service Robot ◽  
Mobile Service ◽  
Indoor Environments ◽  
And Topology ◽  
Localization And Mapping ◽  
Indoor Mobile Robot ◽  
Mobile Service Robots

This paper presents a new and practical method for mapping and annotating indoor environments for mobile robot use. The method makes use of 2D occupancy grid maps for metric representation, and topology maps to indicate the connectivity of the ‘places-of-interests’ in the environment. Novel use of 2D visual tags allows encoding information physically at places-of-interest. Moreover, using physical characteristics of the visual tags (i.e. paper size) is exploited to recover relative poses of the tags in the environment using a simple camera. This method extends tag encoding to simultaneous localization and mapping in topology space, and fuses camera and robot pose estimations to build an automatically annotated global topo-metric map. It is developed as a framework for a hospital service robot and tested in a real hospital. Experiments show that the method is capable of producing globally consistent, automatically annotated hybrid metric-topological maps that is needed by mobile service robots.

scholarly journals Iterative learning control for path tracking of service robot in perspective dynamic system with uncertainties

2020 ◽  
Vol 17 (6) ◽  
pp. 172988142096852
Author(s):  
Wang Yugang ◽  
Zhou Fengyu ◽  
Zhao Yang ◽  
Li Ming ◽  
Yin Lei
Keyword(s):  
Dynamic System ◽  
Iterative Learning Control ◽  
Learning Control ◽  
Path Tracking ◽  
Iterative Learning ◽  
Service Robots ◽  
Service Robot ◽  
Mobile Service ◽  
Motion Information ◽  
Mobile Service Robots

A novel iterative learning control (ILC) for perspective dynamic system (PDS) is designed and illustrated in detail in this article to overcome the uncertainties in path tracking of mobile service robots. PDS, which transmits the motion information of mobile service robots to image planes (such as a camera), provides a good control theoretical framework to estimate the robot motion problem. The proposed ILC algorithm is applied in accordance with the observed motion information to increase the robustness of the system in path tracking. The convergence of the presented learning algorithm is derived as the number of iterations tends to infinity under a specified condition. Simulation results show that the designed framework performs efficiently and satisfies the requirements of trajectory precision for path tracking of mobile service robots.

scholarly journals Avoiding blind leading the blind

2016 ◽  
Vol 13 (6) ◽  
pp. 172988141666608 ◽  
Author(s):  
Abhijeet Ravankar ◽  
Ankit A Ravankar ◽  
Yukinori Kobayashi ◽  
Takanori Emaru
Keyword(s):  
Real World ◽  
Service Robots ◽  
Service Robot ◽  
Mobile Service ◽  
Multiple Robots ◽  
Robot System ◽  
Collective Goal ◽  
Position And Orientation ◽  
Mobile Service Robot ◽  
Multi Robot

Virtual pheromone trailing has successfully been demonstrated for navigation of multiple robots to achieve a collective goal. Many previous works use a pheromone deposition scheme that assumes perfect localization of the robot, in which, robots precisely know their location in the map. Therefore, pheromones are always assumed to be deposited at the desired place. However, it is difficult to achieve perfect localization of the robot due to errors in encoders and sensors attached to the robot and the dynamics of the environment in which the robot operates. In real-world scenarios, there is always some uncertainty associated in estimating the pose (i.e. position and orientation) of the mobile service robot. Failing to model this uncertainty would result in service robots depositing pheromones at wrong places. A leading robot in the multi-robot system might completely fail to localize itself in the environment and be lost. Other robots trailing its pheromones will end up being in entirely wrong areas of the map. This results in a “blind leading the blind” scenario that reduces the efficiency of the multi-robot system. We propose a pheromone deposition algorithm, which models the uncertainty of the robot’s pose. We demonstrate, through experiments in both simulated and real environments, that modeling the uncertainty in pheromone deposition is crucial, and that the proposed algorithm can model the uncertainty well.

Obstacle Avoidance through Gesture Recognition: Business Advancement Potential in Robot Navigation Socio-Technology

Robotica ◽  
2019 ◽  
Vol 37 (10) ◽  
pp. 1663-1676 ◽  
Author(s):  
Xuan Liu ◽  
Kashif Nazar Khan ◽  
Qamar Farooq ◽  
Yunhong Hao ◽  
Muhammad Shoaib Arshad
Keyword(s):  
Literature Review ◽  
Obstacle Avoidance ◽  
Gesture Recognition ◽  
Robot Navigation ◽  
Service Robot ◽  
Mobile Service ◽  
Modern Age ◽  
High Level ◽  
Technological Implication ◽  
Mobile Service Robot

SummaryIn the present modern age, a robot works like human and is controlled in such a manner that its movements should not create hindrance in human activities. This characteristic involves gesture feat and gesture recognition. This article is aimed to describe the developments in algorithms devised for obstacle avoidance in robot navigation which can open a new horizon for advancement in businesses. For this purpose, our study is focused on gesture recognition to mean socio-technological implication. Literature review on this issue reveals that movement of robots can be made efficient by introducing gesture-based collision avoidance techniques. Experimental results illustrated a high level of robustness and usability of the Gesture recognition (GR) system. The overall error rate is almost 10%. In our subjective judgment, we assume that GR system is very well-suited to instruct a mobile service robot to change its path on the instruction of human.

Navigation of Semi-autonomous Service Robots Using Local Information and Anytime Motion Planners

Robotica ◽  
2020 ◽  
Vol 38 (11) ◽  
pp. 2080-2098
Author(s):  
Guilherme A. S. Pereira ◽  
Elias J. R. Freitas
Keyword(s):  
Obstacle Avoidance ◽  
Service Robots ◽  
Service Robot ◽  
Mobile Service ◽  
Global Localization ◽  
Time Coordinate ◽  
Local Path ◽  
Short Time ◽  
Autonomous Service ◽  
Localization Systems

SUMMARYThis paper deals with the problem of navigating semi-autonomous mobile robots without global localization systems in unknown environments. We propose a planning-based obstacle avoidance strategy that relies on local maps and a series of short-time coordinate frames. With this approach, simple odometry and range information are sufficient to make the robot to safely follow the user commands. Different from reactive obstacle avoidance strategies, the proposed approach chooses a good and smooth local path for the robot. The methodology is evaluated using a mobile service robot moving in an unknown corridor environment populated with obstacles and people.

scholarly journals Multi-Armed Bandit Algorithms for a Mobile Service Robot's Spare Time in a Structured Environment

10.29007/kg4r ◽  
2018 ◽  
Author(s):  
Max Korein ◽  
Manuela Veloso
Keyword(s):  
Low Cost ◽  
Office Building ◽  
Service Robots ◽  
Service Robot ◽  
Mobile Service ◽  
Thompson Sampling ◽  
Spare Time ◽  
Planning Algorithms ◽  
The Difference ◽  
Mobile Service Robot

We assume that service robots will have spare time in between scheduled user requests, which they could use to perform additional unrequested services in order to learn a model of users’ preferences and receive rewards. However, a mobile service robot is constrained by the need to travel through the environment to reach users in order to perform services for them, as well as the need to carry out scheduled user requests. We assume service robots operate in structured environments comprised of hallways and floors, resulting in scenarios where an office can be conveniently added to the robot’s plan at a low cost, which affects the robot’s ability to plan and learn.We present two algorithms, Planning Thompson Sampling and Planning UCB1, which are based on existing algorithms used in multi-armed bandit problems, but are modified to plan ahead considering the time and location constraints of the problem. We compare them to existing versions of Thompson Sampling and UCB1 in two environments representative of the types of structures a robot will encounter in an office building. We find that our planning algorithms outperform the original naive versions in terms of both reward received and the effectiveness of the model learned in a simulation. The difference in performance is partially due to the fact that the original algorithms frequently miss opportunities to perform services at a low cost for convenient offices along their path, while our planning algorithms do not.

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