Mobile roboticsystems serve as versatile platforms for diverse indoor applications, ranging from warehousing and manufacturing to test benches dedicated to evaluating automated driving (AD) functions. In AD systems, ...
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Mobile roboticsystems serve as versatile platforms for diverse indoor applications, ranging from warehousing and manufacturing to test benches dedicated to evaluating automated driving (AD) functions. In AD systems, the path following (PF) layer is responsible for defining steering commands to follow the reference path. Recently explored approaches involve artificial intelligence-based methods, such as Deep Reinforcement Learning (DRL). Despite their promising performance, these controllers still suffer from time-consuming training phases and may experience performance degradation when deviating from training conditions. To address these challenges, this paper proposes novel DRL controllers addressing the simulation-to-reality gap in unknown scenarios by: (i) training via an expert demonstrator which also speed up the learning phase;and (ii) a weight adaptation strategy for the resulting neural network (NN) to strengthen controller robustness and enhance PF performance. In addition, an experimentally validated vehicle model is used for training the proposed DRL algorithm and as a model for a federated extended Kalman filter (FEKF) system employed for sensorfusion in vehicle localisation. The proposed DRL-based PF controllers are experimentally evaluated through key performance indicators across multiple maneuvers not considered during training, and it is shown that they outperform benchmarking model-based controllers from the literature. Note to Practitioners-This paper presents a comprehensive toolchain for controlling mobile robots, which includes: (i) a simple yet effective two-stage least-square approach for parameter identification of the longitudinal and lateral dynamics of scaled robotic vehicles;(ii) the utilisation of a no-reset FEKF to enhance positioning leveraging all sensors commonly available on scaled robotic vehicles;(iii) the inclusion of an expert demonstrator to expedite the training phase and address the simulation-to-reality gap resulting from
This Volume 3523 of the conference proceedings contains 28 papers. Topics discussed include sensorfusion and decentralizedcontrol in roboticsystems, multiagents and hierachial architectures, sensor-fused navigation...
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This Volume 3523 of the conference proceedings contains 28 papers. Topics discussed include sensorfusion and decentralizedcontrol in roboticsystems, multiagents and hierachial architectures, sensor-fused navigation and perception, interfaces for augmented reality, action selection, motion coordination and control and robotic workspace and calibration.
The proceedings contain 30 papers. The topics discussed include: a collaboration strategy for autonomous, highly specialized agents;an extended Kalman filter for frequent local and infrequent global sensor data fusion...
The proceedings contain 30 papers. The topics discussed include: a collaboration strategy for autonomous, highly specialized agents;an extended Kalman filter for frequent local and infrequent global sensor data fusion;analyzing the multiple-target-agent scenario using optimal assignment algorithms;target specification error optimal camera configuration for vision-based robotics;a vision-guided, semi-autonomous system applied to a robotic coating application;a unique sensorfusion system for coordinate measuring machine tasks;multiple target tracking across reliable multicast wireless networks;grid-based framework for sensorial data integration in mobile robots;a modular planning/control architecture for the semi-autonomous control of telerobots in a hazardous environment;underwater robot society doing internal inspection and leak monitoring of water systems;and dynamic Bayes net approach to multimodal sensorfusion.
作者：
Leonard, JJMIT
Dept Ocean Engn Cambridge MA 02139 USA
The goal of concurrent mapping and localization (CML) is to enable a mobile robot to build a map of an unknown environment, while simultaneously using this map to navigate. This paper discusses some of the challenges ...
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ISBN:
(纸本)0819438618
The goal of concurrent mapping and localization (CML) is to enable a mobile robot to build a map of an unknown environment, while simultaneously using this map to navigate. This paper discusses some of the challenges that are encountered in the development of practical real-time implementations of CML for one or more autonomous mobile robots operating in large-scale environments.
This article proposes a behavioral control formalism to explain situations often encountered in complex sensor/data fusion (eventually decentralized) information acquisition, command and controlsystems, it involves m...
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This article proposes a behavioral control formalism to explain situations often encountered in complex sensor/data fusion (eventually decentralized) information acquisition, command and controlsystems, it involves making the input-output relations of each actor involved in the fusion process conditional on selected behavioral classes, with error creation and repair options. For each behavioral class, the input-output relations are modified by concurrent behavioral rules, while the class itself has visible and hidden attributes. A formalism is also given for interactions between actors. This approach allows to describe and analyze such situations as: indirect observations, ambiguous controls, hysterisis, deadlocks, initiation of attention mechanisms. Finally, the engineering use of this approach is illustrated by three concrete designs involving humans operating indoors.
We present a novel type of modular robotic system that has a capability of both autonomous shape reconfiguration and robotic motion generation. We have developed hardware modules and examined basic mechanical function...
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ISBN:
(纸本)0819438618
We present a novel type of modular robotic system that has a capability of both autonomous shape reconfiguration and robotic motion generation. We have developed hardware modules and examined basic mechanical functions and reconfiguration. A simulation system of the modular robotic system has also been developed to design the reconfiguration sequence and motion for a cluster of the modules.
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