Accomplishing high-level tasks with modular robots

被引:15
|
作者
Jing, Gangyuan [1 ]
Tosun, Tarik [3 ]
Yim, Mark [4 ]
Kress-Gazit, Hadas [2 ]
机构
[1] Cornell Univ, Verifiable Robot Res Grp, Ithaca, NY USA
[2] Cornell Univ, Sch Mech & Aerosp Engn, Ithaca, NY USA
[3] Univ Penn, Philadelphia, PA 19104 USA
[4] Univ Penn, Mech Engn & Appl Mech Dept, Philadelphia, PA 19104 USA
关键词
Modular robots; Formal methods; Controller synthesis; Reactive mission planning; DESIGN; LOCOMOTION; SYSTEMS; LOGIC;
D O I
10.1007/s10514-018-9738-1
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The advantage of modular self-reconfigurable robot systems is their flexibility, but this advantage can only be realized if appropriate configurations (shapes) and behaviors (controlling programs) can be selected for a given task. In this paper, we present an integrated system for addressing high-level tasks with modular robots, and demonstrate that it is capable of accomplishing challenging, multi-part tasks in hardware experiments. The system consists of four tightly integrated components: (1) a high-level mission planner, (2) a large design library spanning a wide set of functionality, (3) a design and simulation tool for populating the library with new configurations and behaviors, and (4) modular robot hardware. This paper builds on earlier work by Jing et al. (in: Robotics: science and systems, 2016), extending the original system to include environmentally adaptive parametric behaviors, which integrate motion planners and feedback controllers with the system.
引用
收藏
页码:1337 / 1354
页数:18
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