A tale of two explanations: Enhancing human trust by explaining robot behavior

2019 ◽  
Vol 4 (37) ◽  
pp. eaay4663 ◽  
Author(s):  
Mark Edmonds ◽  
Feng Gao ◽  
Hangxin Liu ◽  
Xu Xie ◽  
Siyuan Qi ◽  
...  
Keyword(s):  
Sensory Feedback ◽  
Task Execution ◽  
Robot System ◽  
Integrate Model ◽  
General Acceptance ◽  
Robot Behavior ◽  
Robot Systems ◽  
Parsing Algorithm ◽  
Model Components ◽  
Grammar Model

The ability to provide comprehensive explanations of chosen actions is a hallmark of intelligence. Lack of this ability impedes the general acceptance of AI and robot systems in critical tasks. This paper examines what forms of explanations best foster human trust in machines and proposes a framework in which explanations are generated from both functional and mechanistic perspectives. The robot system learns from human demonstrations to open medicine bottles using (i) an embodied haptic prediction model to extract knowledge from sensory feedback, (ii) a stochastic grammar model induced to capture the compositional structure of a multistep task, and (iii) an improved Earley parsing algorithm to jointly leverage both the haptic and grammar models. The robot system not only shows the ability to learn from human demonstrators but also succeeds in opening new, unseen bottles. Using different forms of explanations generated by the robot system, we conducted a psychological experiment to examine what forms of explanations best foster human trust in the robot. We found that comprehensive and real-time visualizations of the robot’s internal decisions were more effective in promoting human trust than explanations based on summary text descriptions. In addition, forms of explanation that are best suited to foster trust do not necessarily correspond to the model components contributing to the best task performance. This divergence shows a need for the robotics community to integrate model components to enhance both task execution and human trust in machines.

scholarly journals Simulation and Analysis of Self-Replicating Robot Decision-Making Systems

Computers ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 9
Author(s):  
Andrew Jones ◽  
Jeremy Straub
Keyword(s):  
Lower Risk ◽  
System Construction ◽  
System Configuration ◽  
Operating Environment ◽  
Robot System ◽  
Robotic Exploration ◽  
Mission Success ◽  
Robot Systems ◽  
System Configurations

Self-replicating robot systems (SRRSs) are a new prospective paradigm for robotic exploration. They can potentially facilitate lower mission costs and enhance mission capabilities by allowing some materials, which are needed for robotic system construction, to be collected in situ and used for robot fabrication. The use of a self-replicating robot system can potentially lower risk aversion, due to the ability to potentially replenish lost or damaged robots, and may increase the likelihood of mission success. This paper proposes and compares system configurations of an SRRS. A simulation system was designed and is used to model how an SRRS performs based on its system configuration, attributes, and operating environment. Experiments were conducted using this simulation and the results are presented.

scholarly journals Research Progress on Synergistic Technologies of Agricultural Multi-Robots

2021 ◽  
Vol 11 (4) ◽  
pp. 1448
Author(s):  
Wenju Mao ◽  
Zhijie Liu ◽  
Heng Liu ◽  
Fuzeng Yang ◽  
Meirong Wang
Keyword(s):  
Path Planning ◽  
Formation Control ◽  
Research Progress ◽  
Hybrid Architecture ◽  
Labor Costs ◽  
Robot System ◽  
System Architectures ◽  
Research Results ◽  
Robot Systems ◽  
Multi Robot

Multi-robots have shown good application prospects in agricultural production. Studying the synergistic technologies of agricultural multi-robots can not only improve the efficiency of the overall robot system and meet the needs of precision farming but also solve the problems of decreasing effective labor supply and increasing labor costs in agriculture. Therefore, starting from the point of view of an agricultural multiple robot system architectures, this paper reviews the representative research results of five synergistic technologies of agricultural multi-robots in recent years, namely, environment perception, task allocation, path planning, formation control, and communication, and summarizes the technological progress and development characteristics of these five technologies. Finally, because of these development characteristics, it is shown that the trends and research focus for agricultural multi-robots are to optimize the existing technologies and apply them to a variety of agricultural multi-robots, such as building a hybrid architecture of multi-robot systems, SLAM (simultaneous localization and mapping), cooperation learning of robots, hybrid path planning and formation reconstruction. While synergistic technologies of agricultural multi-robots are extremely challenging in production, in combination with previous research results for real agricultural multi-robots and social development demand, we conclude that it is realistic to expect automated multi-robot systems in the future.

A Novel Approach With Bayesian Networks to Multi-Robot Task Allocation in Dynamic Environments

2021 ◽  
Author(s):  
Ching-Wei Chuang ◽  
Harry H. Cheng
Keyword(s):  
Bayesian Networks ◽  
Task Allocation ◽  
Low Cost ◽  
Dynamic Environments ◽  
Modern World ◽  
Robot System ◽  
Novel Approach ◽  
Robot Systems ◽  
Robot Task ◽  
Multi Robot

Abstract In the modern world, building an autonomous multi-robot system is essential to coordinate and control robots to help humans because using several low-cost robots becomes more robust and efficient than using one expensive, powerful robot to execute tasks to achieve the overall goal of a mission. One research area, multi-robot task allocation (MRTA), becomes substantial in a multi-robot system. Assigning suitable tasks to suitable robots is crucial in coordination, which may directly influence the result of a mission. In the past few decades, although numerous researchers have addressed various algorithms or approaches to solve MRTA problems in different multi-robot systems, it is still difficult to overcome certain challenges, such as dynamic environments, changeable task information, miscellaneous robot abilities, the dynamic condition of a robot, or uncertainties from sensors or actuators. In this paper, we propose a novel approach to handle MRTA problems with Bayesian Networks (BNs) under these challenging circumstances. Our experiments exhibit that the proposed approach may effectively solve real problems in a search-and-rescue mission in centralized, decentralized, and distributed multi-robot systems with real, low-cost robots in dynamic environments. In the future, we will demonstrate that our approach is trainable and can be utilized in a large-scale, complicated environment. Researchers might be able to apply our approach to other applications to explore its extensibility.

Development of master-slave magnetic anchoring vision robotic system for single-port laparoscopy (SPL) surgery

2018 ◽  
Vol 45 (4) ◽  
pp. 458-468
Author(s):  
Haibo Feng ◽  
Yanwu Zhai ◽  
Yili Fu
Keyword(s):  
Single Port ◽  
Robotic System ◽  
Surgical Robot ◽  
Distribution Analysis ◽  
Robot System ◽  
Content Type ◽  
Blind Area ◽  
Robot Systems ◽  
Single Port Laparoscopy ◽  
And Performance

Purpose Surgical robot systems have been used in single-port laparoscopy (SPL) surgery to improve patient outcomes. This study aims to develop a vision robot system for SPL surgery to effectively improve the visualization of surgical robot systems for relatively complex surgical procedures. Design/methodology/approach In this paper, a new master-slave magnetic anchoring vision robotic system for SPL surgery was proposed. A lighting distribution analysis for the imaging unit of the vision robot was carried out to guarantee illumination uniformity in the workspace during SPL surgery. Moreover, cleaning force for the lens of the camera was measured to assess safety for an abdominal wall, and performance assessment of the system was performed. Findings Extensive experimental results for illumination, control, cleaning force and functionality test have indicated that the proposed system has an excellent performance in providing the visual feedback. Originality/value The main contribution of this paper lies in the development of a magnetic anchoring vision robot system that successfully improves the ability of cleaning the lens and avoiding the blind area in a field of view.

A Multi-Robot System Using Mobile Agents with Ant Colony Clustering

2010 ◽  
pp. 174-192
Author(s):  
Yasushi Kambayashi ◽  
Yasuhiro Tsujimura ◽  
Hidemi Yamachi ◽  
Munehiro Takimoto
Keyword(s):  
Communication Networks ◽  
Mobile Agents ◽  
Software Agents ◽  
Ant Colony ◽  
Multiple Robots ◽  
Robot System ◽  
Mobile Software ◽  
Robot Systems ◽  
Ant Colony Clustering ◽  
Multi Robot

This chapter presents a framework using novel methods for controlling mobile multiple robots directed by mobile agents on a communication networks. Instead of physical movement of multiple robots, mobile software agents migrate from one robot to another so that the robots more efficiently complete their task. In some applications, it is desirable that multiple robots draw themselves together automatically. In order to avoid excessive energy consumption, we employ mobile software agents to locate robots scattered in a field, and cause them to autonomously determine their moving behaviors by using a clustering algorithm based on the Ant Colony Optimization (ACO) method. ACO is the swarm-intelligence-based method that exploits artificial stigmergy for the solution of combinatorial optimization problems. Preliminary experiments have provided a favorable result. Even though there is much room to improve the collaboration of multiple agents and ACO, the current results suggest a promising direction for the design of control mechanisms for multi-robot systems. In this chapter, we focus on the implementation of the controlling mechanism of the multi-robot system using mobile agents.

Velocity workspace analysis for multiple arm robot systems

Robotica ◽  
2001 ◽  
Vol 19 (5) ◽  
pp. 581-591 ◽  
Author(s):  
Jihong Lee
Keyword(s):  
Null Space ◽  
Inequality Constraint ◽  
Space Velocity ◽  
Velocity Space ◽  
Robot System ◽  
Slack Variables ◽  
Workspace Analysis ◽  
Robot Systems ◽  
Articulated Robot ◽  
Joint Velocity

In this paper, the analysis of manipulability of robotic systems comprised of multiple cooperating arms is considered. Given bounds on the capabilities of joint actuators for each robot, the purpose of this study is to derive the bounds for task velocity achievable by the system. Since bounds on each joint velocity form a polytope in joint-velocity space and the task space velocity is connected with joint velocity through Jacobian matrices of each robot, the allowable task velocity space, i.e. velocity workspace, for multiple cooperating robot system is also represented as a polytope which is called manipulability polytope throughout this paper. Based on the fact that the boundaries of the manipulability polytope are mapped from the boundaries of allowable joint-velocity space, slack variables are introduced in order to transform given inequality constraint given on joint velocities into a set of normal linear equalities in which the unknowns of the equation are composed of the vertices of manipulability polytope, vectors spanning the null space of the Jacobian matrix, and the slack variables. Either redundant or nonredundant cooperating robot systems can be handled with the proposed technique. Several different application examples including simple SCARA-type robots as well as complex articulated robot manipulators are included, and, under the assumption of firm grip, it will be shown that the calculated manipulability polytope for cooperating robot system is actually the intersection of all the manipulability polytopes of every single robot which is hard to be derived through geometrical manipulation.

Dynamic model based formation control and obstacle avoidance of multi-robot systems

Robotica ◽  
2008 ◽  
Vol 26 (3) ◽  
pp. 345-356 ◽  
Author(s):  
Celso De La Cruz ◽  
Ricardo Carelli
Keyword(s):  
Dynamic Model ◽  
Obstacle Avoidance ◽  
Formation Control ◽  
Inverse Dynamics ◽  
Single Equation ◽  
Model Parameters ◽  
Robot System ◽  
System A ◽  
Robot Systems ◽  
Multi Robot

SUMMARYThis work presents, first, a complete dynamic model of a unicycle-like mobile robot that takes part in a multi-robot formation. A linear parameterization of this model is performed in order to identify the model parameters. Then, the robot model is input-output feedback linearized. On a second stage, for the multi-robot system, a model is obtained by arranging into a single equation all the feedback linearized robot models. This multi-robot model is expressed in terms of formation states by applying a coordinate transformation. The inverse dynamics technique is then applied to design a formation control. The controller can be applied both to positioning and to tracking desired robot formations. The formation control can be centralized or decentralized and scalable to any number of robots. A strategy for rigid formation obstacle avoidance is also proposed. Experimental results validate the control system design.

scholarly journals Cost-efficient inter-robot delivery for resource-constrained and interdependent multi-robot schedules

2019 ◽  
Vol 16 (1) ◽  
pp. 172988141982804 ◽  
Author(s):  
Yin Chen ◽  
Xinjun Mao ◽  
Shuo Yang ◽  
Qiuzhen Wang
Keyword(s):  
Cost Efficiency ◽  
Resource Constrained ◽  
Task Execution ◽  
Robot System ◽  
Sequential Execution ◽  
Constrained Environments ◽  
Cost Efficient ◽  
The Cost ◽  
Multi Robot

A multi-robot system in resource-constrained environments needs to obtain resources for task execution. Typically, resources can be fetched from fixed stations, which, however, can be costly and even impossible when fixed stations are unavailable, depleted or distant from task execution locations. We present a method that allows robots to acquire urgently required resources from those robots with superfluous residual resources, by conducting rendezvouses with these robots. We consider a scenario where tasks are organised into a schedule on each robot for sequential execution, with cross-schedule dependencies for inter-robot collaboration. We design an algorithm to systematically generate such rendezvouses for entire multi-robot system to increase the proportion of tasks whose resource demands are satisfied. We also design an algorithm that periodically reallocates tasks among robots to improve the cost-efficiency of schedules. Our experiment shows the synergetic effectiveness of both algorithms, when fixed stations are unavailable and all resources are fetched through inter-robot delivery. We also investigate the effectiveness of inter-robot delivery in scenarios where fixed stations are existent but distant from the locations of tasks.

Fast and Robust Vision System for Shogi Robot

2015 ◽  
Vol 27 (2) ◽  
pp. 182-190
Author(s):  
Gou Koutaki ◽  
◽  
Keiichi Uchimura
Keyword(s):  
Image Processing ◽  
Vision System ◽  
Low Cost ◽  
Robot Arm ◽  
Image Processing Algorithm ◽  
Robot System ◽  
Cost System ◽  
Robot Systems ◽  
Web Camera ◽  
Lower Frame

<div class=""abs_img""> <img src=""[disp_template_path]/JRM/abst-image/00270002/08.jpg"" width=""150"" />Developed shogi robot system</div> The authors developed a low-cost, safety shogi robot system. A Web camera installed on the lower frame is used to recognize pieces and their positions on the board, after which the game program is played. A robot arm moves a selected piece to the position used in playing a human player. A fast, robust image processing algorithm is needed because a low-cost wide-angle Web camera and robot are used. The authors describe image processing and robot systems, then discuss experiments conducted to verify the feasibility of the proposal, showing that even a low-cost system can be highly reliable. </span>

A Method of Robot Behavior Evolution Based on Intelligent Composite Motion Control

2000 ◽  
Vol 12 (3) ◽  
pp. 202-208 ◽  
Author(s):  
Masakazu Suzuki ◽  
Keyword(s):  
Motion Control ◽  
Parameter Optimization ◽  
Basic Element ◽  
Complex Behavior ◽  
Empirical Knowledge ◽  
Joint Rotation ◽  
Robot Behavior ◽  
Robot Systems

Intelligent Composite Motion Control (ICMC) is a methodology for building up robot systems in which robots realize complex, and dexterous behavior autonomously and adaptively by parameter optimization and use of empirical knowledge only if the motion control for basic element motions is given. In this article, ICMC is first reviewed, mainly for the Method of Knowledge Array, which provides a tool for realizing suboptimal motions for new situations by use of empirical knowledge. Behavior evolution based upon ICMC is proposed, i.e., it is shown how robot motions are coordinated from the most basic motions such as joint rotation, and how they evolve into complex behavior such as dexterous ball throwing.

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