Multiple humanoid cooperative control system for heterogeneous humanoid team

Lim, Hee Chun; Kang, Yeonsik; Lee, Joongjae; Kim, Jong-Won; You, Bum-Jae

doi:10.1109/roman.2008.4600671

Cited by 1 publication

(1 citation statement)

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“…The entire process is broken down into subtasks that are assigned to the individual robots by underlying finite state machines. A similar approach was used to command a collection of humanoid robots to clean a table by picking up cans and dropping them into a trash box in Lim et al (2008).…”

Section: Figurementioning

confidence: 99%

Legged robots for object manipulation: A review

et al. 2023

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Legged robots can have a unique role in manipulating objects in dynamic, human-centric, or otherwise inaccessible environments. Although most legged robotics research to date typically focuses on traversing these challenging environments, many legged platform demonstrations have also included “moving an object” as a way of doing tangible work. Legged robots can be designed to manipulate a particular type of object (e.g., a cardboard box, a soccer ball, or a larger piece of furniture), by themselves or collaboratively. The objective of this review is to collect and learn from these examples, to both organize the work done so far in the community and highlight interesting open avenues for future work. This review categorizes existing works into four main manipulation methods: object interactions without grasping, manipulation with walking legs, dedicated non-locomotive arms, and legged teams. Each method has different design and autonomy features, which are illustrated by available examples in the literature. Based on a few simplifying assumptions, we further provide quantitative comparisons for the range of possible relative sizes of the manipulated object with respect to the robot. Taken together, these examples suggest new directions for research in legged robot manipulation, such as multifunctional limbs, terrain modeling, or learning-based control, to support a number of new deployments in challenging indoor/outdoor scenarios in warehouses/construction sites, preserved natural areas, and especially for home robotics.

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Section: Figurementioning

confidence: 99%