An Integrated System for Perception-Driven Autonomy with Modular Robots
Jonathan Daudelin, Gangyuan Jing, Tarik Tosun, Mark Yim, Hadas, Kress-Gazit, Mark Campbell

TL;DR
This paper introduces a modular robot system capable of autonomous perception, high-level planning, and reconfiguration to accomplish complex tasks in unknown environments, demonstrating practical real-world applications.
Contribution
It presents an integrated system combining perception, planning, and reconfigurable hardware for autonomous task execution in unstructured environments.
Findings
Successfully completed high-level tasks in unknown environments
Demonstrated reactive reconfiguration for task adaptation
Validated system through three hardware demonstrations
Abstract
The theoretical ability of modular robots to reconfigure in response to complex tasks in a priori unknown environments has frequently been cited as an advantage and remains a major motivator for work in the field. We present a modular robot system capable of autonomously completing high-level tasks by reactively reconfiguring to meet the needs of a perceived, a priori unknown environment. The system integrates perception, high-level planning, and modular hardware, and is validated in three hardware demonstrations. Given a high-level task specification, a modular robot autonomously explores an unknown environment, decides when and how to reconfigure, and manipulates objects to complete its task. The system architecture balances distributed mechanical elements with centralized perception, planning, and control. By providing an example of how a modular robot system can be designed to…
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