摘要 :
Sensors are based on principle of measuring quantities of changing in media such as sound wave, light or radio wave. Ultrasonic range sensor is a primitive sensor based on the simple idea of measuring the speed of sound echoed bac...
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Sensors are based on principle of measuring quantities of changing in media such as sound wave, light or radio wave. Ultrasonic range sensor is a primitive sensor based on the simple idea of measuring the speed of sound echoed back from the target. The proposed sensor is aimed at sensing robots. The robots are different from normal objects since we can equip the former with any deivces. The fact that we can modify the target to be sensed makes it possible to use a different approach in sensing. Instead of trying to sense echoed signals from the target, we make the target to emit signals. This approach facilitates the complication of sensor system.
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摘要 :
Sensors are based on principle of measuring quantities of changing in media such as sound wave, light or radio wave. Ultrasonic range sensor is a primitive sensor based on the simple idea of measuring the speed of sound echoed bac...
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Sensors are based on principle of measuring quantities of changing in media such as sound wave, light or radio wave. Ultrasonic range sensor is a primitive sensor based on the simple idea of measuring the speed of sound echoed back from the target. The proposed sensor is aimed at sensing robots. The robots are different from normal objects since we can equip the former with any deivces. The fact that we can modify the target to be sensed makes it possible to use a different approach in sensing. Instead of trying to sense echoed signals from the target, we make the target to emit signals. This approach facilitates the complication of sensor system.
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An autonomous robotic system is developed for performing optical observations of geosynchronous (GEO) satellites, determination of their angular positions in the sky, and the improvement of their orbits. Each of the images, taken ...
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An autonomous robotic system is developed for performing optical observations of geosynchronous (GEO) satellites, determination of their angular positions in the sky, and the improvement of their orbits. Each of the images, taken with a CCD-camera attached to the telescope, contains several exposures of the satellite together with the trails of the background stars. A new method is presented to determine the stars positions in the images, based on the rotational algorithm. The automatic processing of the CCD image taken over the night results in a number of the sequence of precise satellite angular coordinates. Using these coordinates as measurements, the orbit defined by the relevant NORAD TLE set - as a preliminary one, and an adequate dynamical model of the satellite orbital motion, an improved orbit can be obtained by the least-squares differential correction algorithm. In this way, the post-fit angular positions of AMOS-2 and -3 GEO satellites were determined with the accuracy of about 0".5 (< 100 meters). Incorporating the radar ranging measurements provides insignificant improvement to the angular position estimates.
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We have collected an extensive winter autonomous driving data set consisting of over 4TB of data collected between November 2019 and March 2020. Our base configuration features two 16 channel LiDARs, forward facing color camera, w...
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We have collected an extensive winter autonomous driving data set consisting of over 4TB of data collected between November 2019 and March 2020. Our base configuration features two 16 channel LiDARs, forward facing color camera, wide field of view NIR camera, and an ADAS LWIR camera. RTK corrected GNSS positioning and IMU data is also available. Portions include data from four different HD LiDARs operating in a variety of winter driving conditions. The set highlights some of the unique aspects of operating in northern climates including changing landmarks due to snow accumulation, wildlife, and snowmobiles operating on local roadways.
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摘要 :
We have collected an extensive winter autonomous driving data set consisting of over 4TB of data collected between November 2019 and March 2020. Our base configuration features two 16 channel LiDARs, forward facing color camera, w...
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We have collected an extensive winter autonomous driving data set consisting of over 4TB of data collected between November 2019 and March 2020. Our base configuration features two 16 channel LiDARs, forward facing color camera, wide field of view NIR camera, and an ADAS LWIR camera. RTK corrected GNSS positioning and IMU data is also available. Portions include data from four different HD LiDARs operating in a variety of winter driving conditions. The set highlights some of the unique aspects of operating in northern climates including changing landmarks due to snow accumulation, wildlife, and snowmobiles operating on local roadways.
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We have developed the automatic garbage collecting system using mobile robot CAMPUS. In this paper, we have described following new functions. One is automatic charging subsystem. Using this subsystem, the autonomous mobile robot ...
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We have developed the automatic garbage collecting system using mobile robot CAMPUS. In this paper, we have described following new functions. One is automatic charging subsystem. Using this subsystem, the autonomous mobile robot can charge its battery automatically and can detect the residual quantity of its battery. Another is the reservation system of collecting garbage. By using this subsystem, users can specify time and room of collecting garbage task.
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The design of gaits for underactuated robots is often unintuitive, with many results derived from either trial and error or simplification of system structure. Recent advances in deep reinforcement learning have yielded results fo...
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The design of gaits for underactuated robots is often unintuitive, with many results derived from either trial and error or simplification of system structure. Recent advances in deep reinforcement learning have yielded results for systems continuous in either states or actions, which may extend to a variety of locomoting robots. In this work we employ reinforcement learning to derive efficient and novel gaits for both terrestrial and aquatic multi-link snake robots. Although such systems operate in different environments, we show that their shared geometric structure allows us to utilize the same learning techniques in both cases to find gaits without any human input. We present results learned and rolled out in simulation, and we describe preliminary efforts to implement the entire learning process on a physical system.
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In this paper, a method to achieve smooth transitions between sequential reachability tasks for a continuous time mobile robotic system is presented. Control barrier functions provide formal guarantees of forward invariance of saf...
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In this paper, a method to achieve smooth transitions between sequential reachability tasks for a continuous time mobile robotic system is presented. Control barrier functions provide formal guarantees of forward invariance of safe sets and finite-time reachability and are able to enforce task execution. Barrier functions used in quadratic programs result in implementation of controllers with real-time performance guarantees. Existing approaches for multi-objective task execution using control barrier functions leverage discretely switched, sequential quadratic programs to achieve successive tasks. However, discrete switching can lead to control input discontinuities which can affect a robot's performance. Hence, we propose a method which ensures continuous transitions between sequential quadratic programs. In particular, a time varying component to the barrier function constraint is introduced which allows for a smooth transition between objectives. Robotic implementation results are also provided.
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This paper presents the robot constructing contest called RobonAUT, where teams of three have to design and compete against each other using their robot. During the course of the contest students can learn how to do the mechanics,...
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This paper presents the robot constructing contest called RobonAUT, where teams of three have to design and compete against each other using their robot. During the course of the contest students can learn how to do the mechanics, electronics and programming of an autonomous mobile robot. The event takes place on two fields. The first is a field where robots have to complete certain stager in less than five minutes to score. On the second field speed is essential and the units have to speed up to score. They have to detect different obstacles with sensor systems that teams connected to a certain type of robot kit. In 2013 the field got more difficult obstacles, like the finish, which was a horizontal surface, but now it is a slope where robots have to stop. Obstacle avoidance is the other obstacle where one side of the object is corded and the other is smooth, the robot have to detect the pattern on the wall.
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Unmanned systems simultaneously reduce risk and magnify the impact of soldier-operators. For example, in Afghanistan UAVs routinely provide overwatch to manned units while UGVs support IED identification and disposal roles. Expand...
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Unmanned systems simultaneously reduce risk and magnify the impact of soldier-operators. For example, in Afghanistan UAVs routinely provide overwatch to manned units while UGVs support IED identification and disposal roles. Expanding these roles requires greater autonomy with a coherent unmanned "system of systems" approach that leverages one platform's strengths against the weakness of another. Specific collaborative unmanned systems such as shared sensing, communication relay, and distributed computing to achieve greater autonomy are often presented as possible solutions. By surveying currently deployed systems, this paper shows that the spectrum of air and ground systems provide an important mixture of range, speed, payload, and endurance with significant implications on mission structure. Rather than proposing UxV teams collaborating towards specific autonomous capabilities, this paper proposes that basic physical and environmental constraints will drive tactics towards a layered, unmanned battlespace that provides force protection and reconnaissance in depth to a manned core.
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