Characterization of handover orientations used by humans for efficient robot to human handovers

Chan, Wesley P.; Pan, Matthew K. X. J.; Croft, Elizabeth A.; Inaba, Masayuki

doi:10.1109/iros.2015.7353106

Cited by 31 publications

(20 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Robots should also be able to quickly adapt their grip force during the handover. The design of solutions for human-to-robot handovers can be informed by the behavior of human-to-human interactions in handovers through models of the relationship between the amount of force applied on the object by each party (grip force) and the proportion of the object's weight carried by each party (load force) [10], [26]- [28]. When modelling the motions between parties, solutions either find a complete trajectory (plan-based) [29]- [31] or continuously optimize the control output given the current state (controller-based) [32], [33].…”

Section: B Handoversmentioning

confidence: 99%

Benchmark for Human-to-Robot Handovers of Unseen Containers With Unknown Filling

Sánchez-Matilla

Chatzilygeroudis

Modas

et al. 2020

IEEE Robot. Autom. Lett.

View full text Add to dashboard Cite

The real-time estimation through vision of the physical properties of objects manipulated by humans is important to inform the control of robots for performing accurate and safe grasps of objects handed over by humans. However, estimating the 3D pose and dimensions of previously unseen objects using only RGB cameras is challenging due to illumination variations, reflective surfaces, transparencies, and occlusions caused both by the human and the robot. In this letter, we present a benchmark for dynamic human-to-robot handovers that do not rely on a motion capture system, markers, or prior knowledge of specific objects. To facilitate comparisons, the benchmark focuses on cups with different levels of transparencies and with an unknown amount of an unknown filling. The performance scores assess the overall system as well as its components in order to help isolate modules of the pipeline that need improvements. In addition to the task description and the performance scores, we also present and distribute as open source a baseline implementation for the overall pipeline to enable comparisons and facilitate progress.

show abstract

Section: B Handoversmentioning

confidence: 99%

Benchmark for Human-to-Robot Handovers of Unseen Containers With Unknown Filling

Sánchez-Matilla

Chatzilygeroudis

Modas

et al. 2020

IEEE Robot. Autom. Lett.

View full text Add to dashboard Cite

show abstract

“…This is an example of an interaction that is mostly mediated by naturalistic, non-explicit cues. Important cues occurring during handovers that have been explored by CARIS include the forces acting on the object being handed over [3,4], gaze behaviors during the handover interaction [17], motion trajectories [9,10], and kinematic configurations [2].…”

Section: Human-robot Handoversmentioning

confidence: 99%

“…In a three condition, intra-participant design, 102 study participants were handed water bottles and asked which of three handovers they preferred. The robot indicated its gaze direction by tilting its head to either look down and away Additional work in conjunction with University of Tokyo went on to study how the orientation of an object interacts with how it is handed over [2]. Current work in CARIS investigates motion cues that can be exploited to detect the timing and location of handovers, for fluent human-to-robot handover behaviors [10].…”

Section: Human-robot Handoversmentioning

confidence: 99%

“…The CARIS Laboratory has invested significant effort in the development of natural, fluent human-robot handovers [2-4, 9, 10, 17]. Handover behaviors include not only visual cues [1,2,9,10,17,23], but also important force and haptic cues [3,4]. Other physical interaction studies, which have been carried out in conjunction with the Sensory Perception & INteraction (SPIN) Laboratory at UBC, include interactions in which participants tap and push on the robot to guide its behavior [5].…”

mentioning

confidence: 99%

See 1 more Smart Citation

Developing Robot Assistants with Communicative Cues for Safe, Fluent HRI

Hart

Sheikholeslami

Gleeson

et al. 2018

Foundations of Trusted Autonomy

View full text Add to dashboard Cite

“…Choice of automation level and location of the transfer point between the autonomous and collaborative/hand-guided robot operation must be made. Several methods on how to carry out the transfer can also be used [24]. Solutions that take advantage of the opportunities for effective component logistics must be developed.…”

Section: Layout For Production Cells and Production Linesmentioning

confidence: 99%

Safety Assessment Strategy for Collaborative Robot Installations

Grahn¹,

Johansen²,

Eriksson³

2017

Robots Operating in Hazardous Environments

View full text Add to dashboard Cite

Industrial resource efficiency can be improved if the safety barrier between humans and robots is removed, as this enables operators and robots to work side by side or in direct collaboration to solve a task, usually referred to as a collaborative robot installation. Even though technology development makes the barrier removal ever more feasible from a safety perspective, this still produces a possible hazardous working environment, and safety assessment strategies are crucial. A wide area of knowledge is required to assess all fields that can help ensure safe human-machine interaction. Here the focus is primarily on providing a description of the key fields identified, including how operators psychologically accept working with robots, and providing a cursory description of the research front for each individual field. In addition to covering a large number of parameters, the assessment strategy also needs to be cost-effective. A significant part of all parameters that can be considered when attempting to produce optimized and cost-effective collaborative robot installations will also have a direct impact on operator safety. Hence, assessments for safety, and assessments for cost-effectiveness, cannot be separated, and are treated as two objectives that need to be viewed in sync.

show abstract

Characterization of handover orientations used by humans for efficient robot to human handovers

Cited by 31 publications

References 13 publications

Benchmark for Human-to-Robot Handovers of Unseen Containers With Unknown Filling

Benchmark for Human-to-Robot Handovers of Unseen Containers With Unknown Filling

Developing Robot Assistants with Communicative Cues for Safe, Fluent HRI

Safety Assessment Strategy for Collaborative Robot Installations

Contact Info

Product

Resources

About