Human-inspired robot assistant for fast point-to-point movements

Corteville, Brecht; Aertbeliën, Erwin; Bruyninckx, Herman; Schutter, Joris De; Brussel, Hendrik Van

doi:10.1109/robot.2007.364036

Cited by 133 publications

(124 citation statements)

References 10 publications

Supporting

Mentioning

117

Contrasting

Unclassified

Order By: Relevance

“…The strategy generally aims at reducing the problem to the estimation of handful parameters that allows generating a complete motion. The most famous example is the minimum jerk model [5] [6]. However this model is always rather applied to point-to-point motion and does not fit for motions going beyond the reach of the arm or even to motion for which the target point is not well defined.…”

Section: Proactive Trajectory Plannermentioning

confidence: 99%

“…An other way to be proactive is to guess the human partner's intended trajectory. This is the approach chosen in [5] [6] and also the one we choose in this paper. Note that both approaches are not incompatible.…”

Section: Introductionmentioning

confidence: 99%

“…Relatively to existing work, our approach distinguishes in its capability to guess the human partner's intentions for a wide variety of motions, where [5] and [6] only consider point-to-point movements. Furthermore, we distinguish the recognition of the partner's intended trajectory from the action undertaken to help him/her.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Proactive behavior of a humanoid robot in a haptic transportation task with a human partner

Bussy

Gergondet

Kheddar

et al. 2012

2012 IEEE RO-MAN: The 21st IEEE International Symposium on Robot and Human Interactive Communication

View full text Add to dashboard Cite

Abstract-In this paper, we propose a control scheme that allows a humanoid robot to perform a complex transportation scenario jointly with a human partner. At first, the robot guesses the human partner's intentions to proactively participate to the task. In a second phase, the human-robot dyad switches roles: the robot takes over the leadership of the task to complete the scenario. During this last phase, the robot is remotely controlled with a joystick. The scenario is realized on a real HRP-2 humanoid robot to assess the overall approach.

show abstract

Section: Proactive Trajectory Plannermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Proactive behavior of a humanoid robot in a haptic transportation task with a human partner

Bussy

Gergondet

Kheddar

et al. 2012

2012 IEEE RO-MAN: The 21st IEEE International Symposium on Robot and Human Interactive Communication

View full text Add to dashboard Cite

show abstract

“…In order to plan the next robot action for assistance to the human, the next human action needs to be predicted. For simple motor tasks, findings from human motor behavior are considered for movement prediction, for example the well-known minimum jerk velocity profile for point to point movements [5], [8]. However, for more complex tasks there are not any such analytical models currently available.…”

Section: Introductionmentioning

confidence: 99%

An experience-driven robotic assistant acquiring human knowledge to improve haptic cooperation

Medina

Lawitzky

Mortl

et al. 2011

2011 IEEE/RSJ International Conference on Intelligent Robots and Systems

View full text Add to dashboard Cite

Abstract-Physical cooperation with humans greatly enhances the capabilities of robotic systems when leaving standardized industrial settings. Our novel cognition-enabled control framework presented in this paper enables a robotic assistant to enrich its own experience by acquisition of human task knowledge during joint manipulation. Our robot incrementally learns semantic task structures during joint task execution using hierarchically clustered Hidden Markov Models. A semantic labeling of recognized task segments is acquired from the human partner through speech. After a small number of repetitions, the robot uses an anticipated task progress to generate a feed-forward set point for an admittance feedback control scheme. This paper describes the framework and its implementation on a mobile bi-manual platform. The evolution of the robot's task knowledge is presented and discussed. Finally, the cooperation quality is measured in terms of the robot's task contribution.

show abstract

“…However, such a follower strategy implements merely a trolley for heavier loads rather than an actual cooperation partner and, while simple tasks can successfully be fulfilled, more complex tasks including environmental constraints typically require an active contribution to the task by the robot [4]. Active robotic assistance also reduces the effort applied by the human partner [5], [6], [7]. In order to plan the next robot action for assistance to the human, the next human action needs to be predicted.…”

Section: Introductionmentioning

confidence: 99%

An experience-driven robotic assistant acquiring human knowledge to improve haptic cooperation

Medina

Lawitzky

Mörtl

et al. 2011

2011 IEEE/RSJ International Conference on Intelligent Robots and Systems

View full text Add to dashboard Cite

show abstract

Human-inspired robot assistant for fast point-to-point movements

Cited by 133 publications

References 10 publications

Proactive behavior of a humanoid robot in a haptic transportation task with a human partner

Proactive behavior of a humanoid robot in a haptic transportation task with a human partner

An experience-driven robotic assistant acquiring human knowledge to improve haptic cooperation

An experience-driven robotic assistant acquiring human knowledge to improve haptic cooperation

Contact Info

Product

Resources

About