Robot Basketball: Ball Dribbling — A Modified Juggling Task

Bätz, Georg; Sobotka, Marion; Wollherr, Dirk; Buss, Martin

doi:10.1007/978-3-642-01213-6_29

Cited by 13 publications

(15 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The ball-dribbling system presented in [1] is controlled by intermittent contact of the manipulator with the ball. We want to modify it by adding a compression spring to the manipulator as illustrated in Fig.…”

Section: A Coupled Ball-spring-manipulator Dynamicsmentioning

confidence: 99%

“…An example of robot dribbling was presented in [7] for experimental evaluation of a high-speed vision system. A comparison between juggling and dribbling is discussed in [1] with respect to local stability and parameter sensitivity. Furthermore, experimental tests were shown with and industrial robot dribbling a basketball for multiple periods of a desired cycle.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Ball dribbling with an underactuated continuous-time control phase

Mettin

Shiriaev

Bätz

et al. 2010

2010 IEEE International Conference on Robotics and Automation

Self Cite

View full text Add to dashboard Cite

Ball dribbling is a central element of basketball. One main challenge for realizing basketball robots is to stabilize periodic motions of the ball. This task is nontrivial due to the discrete-continuous nature of the corresponding dynamics. The ball can be only controlled during ball-manipulator contact and moves freely otherwise. We propose a manipulator equipped with a spring that gets compressed when the ball bounces against it. Hence, we can have continuous-time control over this underactuated Ball-Spring-Manipulator system until the spring releases its accumulated energy back to the ball. This paper illustrates a systematic way of planning such a modified dribbling motion, computing an analytical transverse linearization and achieving orbital stabilization.

show abstract

Section: A Coupled Ball-spring-manipulator Dynamicsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Ball dribbling with an underactuated continuous-time control phase

Mettin

Shiriaev

Bätz

et al. 2010

2010 IEEE International Conference on Robotics and Automation

Self Cite

View full text Add to dashboard Cite

show abstract

“…As expected, the contact time increases with decreasing stiffness. This is a significant benefit one obtains from the elastic properties: more time to control the robot during hand contact 7 . The experimental performance of this approach can be found in [15].…”

Section: Energy Based Analysismentioning

confidence: 99%

“…This experiment was used to evaluate high-speed vision for ball tracking. The work [7] introduced a dribbling industrial robot, utilizing a solid plate as hand. The control mainly relies on the ball tracking vision system and achieves stability of the cycle.…”

Section: Introductionmentioning

confidence: 99%

Exploiting Elastic Energy Storage for “Blind” Cyclic Manipulation: Modeling, Stability Analysis, Control, and Experiments for Dribbling

Haddadin

Krieger²,

Albu‐Schäffer

et al. 2018

IEEE Trans. Robot.

View full text Add to dashboard Cite

Abstract-For creating robots that are capable of human like performance in terms of speed, energetic properties and robustness, intrinsic compliance is a promising design element. In this paper we investigate the principle effects of elastic energy storage and release for basketball dribbling in terms of open-loop cycle stability. We base the analysis, which is performed for the 1-degree-of-freedom (DoF) case, on error propagation, peak power performance during hand contact and robustness with respect to varying hand stiffness. As the ball can only be controlled during contact, an intrinsically elastic hand extends the contact time and improves the energetic characteristics of the process. To back up our basic insights, we extend the 1-DoF controller to 6-DoFs and show how passive compliance can be exploited for a 6-DoF cyclic ball dribbling task with a 7-DoF articulated Cartesian impedance controlled robot. As a human is able to dribble blindly, we decided to focus on the case of contact force sensing only, i.e. no visual information is used in our approach. We show via simulation and experiment that it is possible to achieve a stable dynamic cycle based on the 1 DoF analysis for the primary vertical axis together with control strategies for the secondary translations and rotations of the task. The scheme allows also the continuous tracking of a desired dribbling height and horizontal position. The approach is also used to hypothesize about human dribbling and is validated with captured data.

show abstract

“…There are other cyclic tasks involving the manipulation of a ball such as juggling and dribbling which have received a lot of attention in robotics [1], [2], [3]. The fundamental difference between ball manipulation and yoyo playing is that juggling and dribbling have free flying phases where (a) Human yoyo playing motion recorded via motion capture technology (left), is used to teach the humanoid HRP-2 (right) (b) HRP-2 grasps the yoyo in its hand, and inset shows the same yoyo with the reflective motion capture markers used in the motion capture experiments the ball and the hand move independently, while the yoyo always remains connected to the hand by the string.…”

Section: Introductionmentioning

confidence: 99%

HRP-2 plays the yoyo: From human to humanoid yoyo playing using optimal control

Mombaur

Sreenivasa

2010

2010 IEEE International Conference on Robotics and Automation

View full text Add to dashboard Cite

Yoyo playing may seem easy for a human, but it is a challenging problem for a humanoid robot. This paper presents an approach to generate yoyo motions for the humanoid robot, HRP-2, based on motion recorded from human yoyo playing, dynamical models and numerical optimal control techniques. We recorded vertical yoyo playing of 4 subjects measuring yoyo height and rotation angle as well as the corresponding hand motions. A detailed multi-phase yoyo model with impact collisions and control patterns of human yoyo playing were identified from these measurements. Based on this knowledge, reliable yoyo motions within the feasibility ranges of HRP-2 were generated using optimal control. The resulting motions have been implemented on the robot using open-loop and event-based quasi open-loop control strategies. Abstract-Yoyo playing may seem easy for a human, but it is a challenging problem for a humanoid robot. This paper presents an approach to generate yoyo motions for the humanoid robot, HRP-2, based on motion recorded from human yoyo playing, dynamical models and numerical optimal control techniques. We recorded vertical yoyo playing of 4 subjects measuring yoyo height and rotation angle as well as the corresponding hand motions. A detailed multi-phase yoyo model with impact collisions and control patterns of human yoyo playing were identified from these measurements. Based on this knowledge, reliable yoyo motions within the feasibility ranges of HRP-2 were generated using optimal control. The resulting motions have been implemented on the robot using open-loop and event-based quasi open-loop control strategies.

show abstract

Robot Basketball: Ball Dribbling — A Modified Juggling Task

Cited by 13 publications

References 25 publications

Ball dribbling with an underactuated continuous-time control phase

Ball dribbling with an underactuated continuous-time control phase

Exploiting Elastic Energy Storage for “Blind” Cyclic Manipulation: Modeling, Stability Analysis, Control, and Experiments for Dribbling

HRP-2 plays the yoyo: From human to humanoid yoyo playing using optimal control

Contact Info

Product

Resources

About