Iteratively Refined Feasibility Checks in Robotic Assembly Sequence Planning

Rodríguez, Ismael Pablo; Nottensteiner, Korbinian; Leidner, Daniel; Kasecker, Michael; Stulp, Freek; Albu‐Schäffer, Alin

doi:10.1109/lra.2019.2895845

Cited by 50 publications

(28 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…They mostly use pick-and-place problems as test cases, which have a reduced complexity compared to an assembly process involving several steps and tasks. On the other hand, in our previous works [19], [20], we intrinsically include the robots in the planning loop. We tested our approach in a more complex assembly domain, creating structures with modular aluminum profiles, thus proving the capabilities of our system to adapt not only to different assembly tasks, but also to different skill sets of the robot.…”

Section: Hybrid Plannersmentioning

confidence: 99%

Autonomous Robot Planning System for In-Space Assembly of Reconfigurable Structures

Rodríguez

Bauer

Nottensteiner

et al. 2021

2021 IEEE Aerospace Conference (50100)

Self Cite

View full text Add to dashboard Cite

Section: Hybrid Plannersmentioning

confidence: 99%

Autonomous Robot Planning System for In-Space Assembly of Reconfigurable Structures

Rodríguez

Bauer

Nottensteiner

et al. 2021

2021 IEEE Aerospace Conference (50100)

Self Cite

View full text Add to dashboard Cite

“…The deliberative task planning unit selects robotic skills, which are in principle capable of solving the tasks under the constraints that arise from the goal specification and the assumed world state. For this, we are using a sequence planner that automatically decomposes the assembly of a desired product into a sequence of tasks and selects using representations of the parts and the system on multiple abstraction levels [56]. The knowledge base provides information about properties of objects and grounds them in physical quantities as far as possible.…”

Section: Components Of the Autonomous Assembly Systemmentioning

confidence: 99%

“…It is capable of assembling unique products with parts from an aluminum profile construction set [52]. Assembly sequencing at task level is performed automatically using multiple abstraction levels [56]. Furthermore, a reliable task execution is required for similar but different product variants.…”

Section: Introductionmentioning

confidence: 99%

Towards Autonomous Robotic Assembly: Using Combined Visual and Tactile Sensing for Adaptive Task Execution

Nottensteiner

Sachtler

Albu‐Schäffer

2021

J Intell Robot Syst

Self Cite

View full text Add to dashboard Cite

Robotic assembly tasks are typically implemented in static settings in which parts are kept at fixed locations by making use of part holders. Very few works deal with the problem of moving parts in industrial assembly applications. However, having autonomous robots that are able to execute assembly tasks in dynamic environments could lead to more flexible facilities with reduced implementation efforts for individual products. In this paper, we present a general approach towards autonomous robotic assembly that combines visual and intrinsic tactile sensing to continuously track parts within a single Bayesian framework. Based on this, it is possible to implement object-centric assembly skills that are guided by the estimated poses of the parts, including cases where occlusions block the vision system. In particular, we investigate the application of this approach for peg-in-hole assembly. A tilt-and-align strategy is implemented using a Cartesian impedance controller, and combined with an adaptive path executor. Experimental results with multiple part combinations are provided and analyzed in detail.

show abstract

“…A promising direction is to combine the auditory, visual and haptic information to achieve the multimodal interaction between the operator and F I G U R E 1 Illustrative examples of different contact tasks. (a) Assembly [1]. (b) Cleaning an arbitrary surface [9].…”

Section: Introductionmentioning

confidence: 99%

A review on manipulation skill acquisition through teleoperation‐based learning from demonstration

Wang

Yang

2021

Cognitive Comp and Systems

View full text Add to dashboard Cite

Manipulation skill learning and generalisation have gained increasing attention due to the wide applications of robot manipulators and the spurt of robot learning techniques. Especially, the learning from demonstration method has been exploited widely and successfully in the robotic community, and it is regarded as a promising direction to realise the manipulation skill learning and generalisation. In addition to the learning techniques, the immersive teleoperation enables the human to operate a remote robot with an intuitive interface and achieve the telepresence. Thus, it is a promising way to transfer manipulation skills from humans to robots by combining the learning methods and teleoperation, and adapting the learned skills to different tasks in new situations. This review, therefore, aims to provide an overview of immersive teleoperation for skill learning and generalisation to deal with complex manipulation tasks. To this end, the key technologies, for example, manipulation skill learning, multimodal interfacing for teleoperation and telerobotic control, are introduced. Then, an overview is given in terms of the most important applications of immersive teleoperation platform for robot skill learning. Finally, this survey discusses the remaining open challenges and promising research topics. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

show abstract

Iteratively Refined Feasibility Checks in Robotic Assembly Sequence Planning

Cited by 50 publications

References 14 publications

Autonomous Robot Planning System for In-Space Assembly of Reconfigurable Structures

Autonomous Robot Planning System for In-Space Assembly of Reconfigurable Structures

Towards Autonomous Robotic Assembly: Using Combined Visual and Tactile Sensing for Adaptive Task Execution

A review on manipulation skill acquisition through teleoperation‐based learning from demonstration

Contact Info

Product

Resources

About