Michael X. Grey, Neil T. Dantam, D. Lofaro, A. Bobick, M. Egerstedt, P. Oh, Mike Stilman
{"title":"Multi-process control software for HUBO2 Plus robot","authors":"Michael X. Grey, Neil T. Dantam, D. Lofaro, A. Bobick, M. Egerstedt, P. Oh, Mike Stilman","doi":"10.1109/TePRA.2013.6556374","DOIUrl":"https://doi.org/10.1109/TePRA.2013.6556374","url":null,"abstract":"Humanoid robots require greater software reliability than traditional mechatronic systems if they are to perform useful tasks in typical human-oriented environments. This paper covers a software architecture which distributes the load of computation and control tasks over multiple processes, enabling fail-safes within the software. These fail-safes ensure that unexpected crashes or latency do not produce damaging behavior in the robot. The distribution also offers benefits for future software development by making the architecture modular and extensible. Utilizing a low-latency inter-process communication protocol (Ach), processes are able to communicate with high control frequencies. The key motivation of this software architecture is to provide a practical framework for safe and reliable humanoid robot software development. The authors test and verify this framework on a HUBO2 Plus humanoid robot.","PeriodicalId":102284,"journal":{"name":"2013 IEEE Conference on Technologies for Practical Robot Applications (TePRA)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121582840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"CUDA accelerated robot localization and mapping","authors":"H. Zhang, F. Martin","doi":"10.1109/TePRA.2013.6556350","DOIUrl":"https://doi.org/10.1109/TePRA.2013.6556350","url":null,"abstract":"We present a method to accelerate robot localization and mapping by using CUDA (Compute Unified Device Architecture), the general purpose parallel computing platform on NVIDIA GPUs. In robotics, the particle filter-based SLAM (Simultaneous Localization and Mapping) algorithm has many applications, but is computationally intensive. Prior work has used CUDA to accelerate various robot applications, but particle filter-based SLAM has not been implemented on CUDA yet. Because computations on the particles are independent of each other in this algorithm, CUDA acceleration should be highly effective. We have implemented the SLAM algorithm's most time consuming step, particle weight calculation, and optimized memory access by using texture memory to alleviate memory bottleneck and fully leverage the parallel processing power. Our experiments have shown the performance has increased by an order of magnitude or more. The results indicate that oftloading to GPU is a cost-effective way to improve SLAM algorithm performance.","PeriodicalId":102284,"journal":{"name":"2013 IEEE Conference on Technologies for Practical Robot Applications (TePRA)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124777142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jens-Steffen Gutmann, P. Fong, Lihu Chiu, Mario E. Munich
{"title":"Challenges of designing a low-cost indoor localization system using active beacons","authors":"Jens-Steffen Gutmann, P. Fong, Lihu Chiu, Mario E. Munich","doi":"10.1109/TePRA.2013.6556348","DOIUrl":"https://doi.org/10.1109/TePRA.2013.6556348","url":null,"abstract":"Localization is very helpful for goal-oriented navigation of a mobile robot. In this article, we describe the challenges we faced when designing a low-cost indoor localization system that can be employed on consumer and domestic robots for the systematic navigation in household environments. Our system uses active beacons that project a pair of infrared (IR) spots onto the ceiling and a sensor on the robot which observes them. In order to reduce cost, we designed a 3-diode sensor, i.e. a three pixel camera, that measures directions to the spots. In contrast to e.g. a typical camera with VGA or higher resolution that would allow for a precise tracking of the beacon spots, our low-cost sensor suffers from multi-path, i.e. light not only reaches the sensor directly but also through reflections from walls and other furniture. We tackle this problem by a localization method that learns the light distribution in the room through a simultaneous localization and mapping (SLAM) approach. Our experiments provide numbers on the accuracy and consistency of this method. The presented system is implemented on our Mint robot equipped with an ARM 7 processor and 64 kByte of RAM for the autonomous cleaning of floors.","PeriodicalId":102284,"journal":{"name":"2013 IEEE Conference on Technologies for Practical Robot Applications (TePRA)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131075521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}