RUR53: an Unmanned Ground Vehicle for Navigation, Recognition and Manipulation
نویسندگان
چکیده
This paper describes RUR53, the unmanned mobile manipulator robot developed by the Desert Lion team of the University of Padova (Italy), and its experience in Challenge 2 and the Grand Challenge of the first Mohamed Bin Zayed International Robotics Challenge (Abu Dhabi, March 2017). According to the competition requirements, the robot is able to freely navigate inside an outdoor arena; locate and reach a panel; recognize and manipulate a wrench; use this wrench to physically operate a valve stem on the panel itself. RUR53 is able to perform these tasks both autonomously and in teleoperation mode. The paper details the adopted hardware and software architectures, focusing on its key aspects: modularity, generality, and the ability of exploiting sensor feedback. These features let the team rank third in the Gran Challenge in collaboration with the Czech Technical University in Prague, Czech Republic, the University of Pennsylvania, USA, and the University of Lincoln, UK. Tests performed both in the Challenge arena and in the lab are presented and discussed, focusing on the strengths and limitations of the proposed wrench and valve classification and recognition algorithms. Lessons learned are also detailed.
منابع مشابه
Vertical Dynamics Modeling and Simulation of a Six-Wheel Unmanned Ground Vehicle
Vertical dynamics modeling and simulation of a six-wheel unmanned military vehicle (MULE) studied in this paper. The Common Mobility Platform (CMP) chassis provided mobility, built around an advanced propulsion and articulated suspension system gave the vehicle ability to negotiate complex terrain, obstacles, and gaps that a dismounted squad would encounter. Aiming at modeling of vehicle vertic...
متن کاملMIMO Based Transceiver System for Unmanned Ground Vehicle for Surveillance In War Field
Unmanned ground vehicle is an autonomous vehicle that mainly capable to do tasks independent of humans. Automated vehicle works during off road navigation and mainly used in military operations. The radio environment on electrically small platforms is changing rapidly. In order to support high speed audio and video, processing needs higher data rates concerned with sending and receiving data pa...
متن کاملInformation-based intelligent unmanned ground vehicle navigation
Sensor-centric navigation of Unmanned Ground Vehicles (UGVs) operating in rugged and expansive terrains requires the competency to evaluate the utility of sensor information such that it results in intelligent behavior of the vehicles. In this paper, we propose an entropic information metric for the above purpose where entropy is used to quantify the probabilistic uncertainty in sensor measurem...
متن کاملVariety of research work has already been done to develop an effective navigation systems for unmanned ground vehicle
A smart Unmanned Ground Vehicle (UGV) is designed and developed for some application specific missions to operate predominantly in hazardous environments. In our work, we have developed a small and lightweight vehicle to operate in general crosscountry terrains in or without daylight. The UGV can send visual feedbacks to the operator at a remote location. Onboard infrared sensors can detect the...
متن کاملQuadrotor UAV Guidence For Ground Moving Target Tracking
The studies in aerial vehicles modeling and control have been increased rapidly recently. In this paper , a coordination of two types of heterogeneous robots , namely unmanned aerial vehicle (UAV) and unmanned ground vehicle (UGV) is considered. In this paper the UAV plays the role of a virtual leader for the UGVs. The system consists of a vision- based target detection algorithm that uses the ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- CoRR
دوره abs/1711.08764 شماره
صفحات -
تاریخ انتشار 2017