A Practical Comparison of Three Robot Learning from Demonstration Algorithm

Suay, Halit Bener; Toris, Russell; Chernova, Sonia

doi:10.1007/s12369-012-0158-7

Cited by 34 publications

(24 citation statements)

References 10 publications

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“…Programming by Demonstration (PbD), also known as Learning from Demonstration, has been studied within robotics for the last three decades [4], with recent work focusing more and more on human interaction problems in PbD [5,2,19,12,21,15]. The design choices for the dialog interface of our PbD system are influenced by work on spoken interactions with robots within the human-robot interaction (HRI) literature [7,8,21].…”

Section: Related Workmentioning

confidence: 99%

Teaching people how to teach robots

Çakmak

Takayama

2014

Proceedings of the 2014 ACM/IEEE International Conference on Human-Robot Interaction

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Allowing end-users to harness the full capability of general purpose robots, requires giving them powerful tools. As the functionality of these tools increase, learning how to use them becomes more challenging. In this paper we investigate the use of instructional materials to support the learnability of a Programming by Demonstration tool. We develop a system that allows users to program complex manipulation skills on a two-armed robot through a spoken dialog interface and by physically moving the robot's arms. We present a user study (N=30) in which participants are left alone with the robot and a user manual, without any prior instructions on how to program the robot. Instead, they are asked to figure it out on their own. We investigate the effect of providing users with an additional written tutorial or an instructional video. We find that videos are most effective in training the user; however, this effect might be superficial and ultimately trial-and-error plays an important role in learning to program the robot. We also find that tutorials can be problematic when the interaction has uncertainty due to speech recognition errors. Overall, the user study demonstrates the effectiveness and learnability of the our system, while providing useful feedback about the dialog design.

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Section: Related Workmentioning

confidence: 99%

Teaching people how to teach robots

Çakmak

Takayama

2014

Proceedings of the 2014 ACM/IEEE International Conference on Human-Robot Interaction

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“…Within the field of HRI, convincing research is typically strongly supported by user studies to help prove the effectiveness of new techniques (Lee et al, 2012;Cakmak & Thomaz, 2012;Kahn et al, 2012;Pantofaru, Takayama, Foote, & Soto, 2012;Morales Saiki et al, 2012). Integration of user studies into the design, development and evaluation of new techniques has been shown to result in more useable methods (Suay, Toris, & Chernova, 2012), whereas development of algorithms in isolation risks biasing usability towards expert users.…”

Section: Introductionmentioning

confidence: 99%

The Robot Management System: A Framework for Conducting Human-Robot Interaction Studies Through Crowdsourcing

Toris¹,

Kent²,

Chernova³

2014

Journal of Human-Robot Interaction

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Human-Robot Interaction (HRI) is a rapidly expanding field of study that focuses on allowing nonroboticist users to naturally and effectively interact with robots. The importance of conducting extensive user studies has become a fundamental component of HRI research; however, due to the nature of robotics research, such studies often become expensive, time consuming, and limited to constrained demographics. In this work, we present the Robot Management System (RMS), a novel framework for bringing robotic experiments to the web. We present a detailed description of our open-source system and describe an initial trial of the RMS as a means of conducting user studies. Using a series of navigation and manipulation tasks with a PR2 robot, we compare three user study conditions: users that are co-present with the robot, users that are recruited to the university laboratory but control the robot from a different room, and remote web-based users. Our findings show little statistical differences between usability patterns across these groups, validating the use of web-based crowdsourcing techniques for certain types of HRI evaluations.

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“…In the third scenario, where both arrival and departure zones were occupied (Figure 4 (c)), almost half of the users expected Baxter to consider the occupied position, even though it was not mentioned in the Baxter's action model. This is a common problem in PbD solutions as there is a difference in the perception of the robot's intelligence perceived by its teacher [13]. This can be easily addressed by reproducing the learned task in a new context and verifying the robot's knowledge base as we did throughout the experiment.…”

Section: Resultsmentioning

confidence: 99%

A Framework for Robot Programming in Cobotic Environments

Liang

Pellier

Fiorino

et al. 2017

Proceedings of the 3rd International Conference on Mechatronics and Robotics Engineering

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The increasing presence of robots in industries has not gone unnoticed. Large industrial players have incorporated them into their production lines, but smaller companies hesitate due to high initial costs and the lack of programming expertise. In this work we introduce a framework that combines two disciplines, Programming by Demonstration and Automated Planning, to allow users without any programming knowledge to program a robot. The user teaches the robot atomic actions together with their semantic meaning and represents them in terms of preconditions and effects. Using these atomic actions the robot can generate action sequences autonomously to reach any goal given by the user. We evaluated the usability of our framework in terms of user experiments with a Baxter Research Robot and showed that it is well-adapted to users without any programming experience.

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A Practical Comparison of Three Robot Learning from Demonstration Algorithm

Cited by 34 publications

References 10 publications

Teaching people how to teach robots

Teaching people how to teach robots

The Robot Management System: A Framework for Conducting Human-Robot Interaction Studies Through Crowdsourcing

A Framework for Robot Programming in Cobotic Environments

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