Rancang Bangun Sistem Penjejakan Garis Berbasis Visi Komputer pada Indoor Patrolling Drone

Indoor Patrolling drone adalah drone yang beroprasi di dalam ruangan dan dapat berpatroli pada area yang ditentukan. Patrolling drone mampu melakukan navigasi di dalam ruangan tanpa bergantung pada GPS. Kemampuan patrolling drone untuk tidak bergantung pada GPS sangat diperlukan karena ketika drone berada di dalam ruangan, sistem navigasi menggunakan GPS tidak dapat dilakukan secara optimal. Indoor patrolling drone memadukan quadcopter drone dengan sistem navigasi penjejakan garis. Penjejakan garis dilakukan untuk menentukan rute pengawasan yang akan dilalui oleh drone. Patrolling drone diperlukan karena hingga saat ini sebagian besar metode pengawasan dalam ruangan masih dilakukan oleh agen manusia yang melakukan patroli pada waktu dan area yang ditentukan. Metode tersebut masih rentan akan adanya kesalahan yang ditimbulakan oleh manusia atau sering disebut dengan human error. Patrolling drone diharapkan dapat menjadi alternatif dan meningkatkan sistem kemanan tersebut. Patrolling drone yang dimaksud pada tugas akhir ini telah berhasil dibuat dan telah dilakukan berbagai pengujian. Berdasarkan hasil pengujian tersebut, patrolling drone memiliki rata – rata durasi terbang selama 6 menit 56 detik. Sistem penjejakan garis yang digunakan pada drone ini memiliki akurasi estimasi jarak sebesar 0.51cm dan akurasi kecepatan sebesar 15.66cm/s. Dengan membandingkan dengan performa sistem navigasi dalam ruangan menggunakan GPS yang memiliki akurasi sebesar 4.5 hingga 8 meter, sistem navigasi penjejakan garis pada drone ini menunjukkan peningkatan tingkat akurasi yang cukup signifikan. Selain itu, sistem navigasi penjejakan garis pada patrolling drone ini dapat dilakukan dengan optimal hingga kecepatan 48cm/s. =============================================================================================================================== Indoor patrolling drone is a drone which operate indoor and can automatically patrol in the designated area. Patrolling drone is capable of indoor navigation without relying on GPS system. The ability of indoor patrolling drone to navigate without relying on GPS system is very important, because any form of GPS basednavigation system can not be used effectively in indoor applications. Indoor patrolling drone combines quadcopter drone and line follower navigation system. Line follower system is used to determine drone’s surveillance route. Self-patrolling drone is needed because untill now, most of the surveillance method are still done by human. Human surveillance method are prone to error caused by human or frequently labeled as human error. Self-patrolling drone is expected to be an alternative and to improve conventional surveillance method that involve human in their system. Self-patrolling drone described in this final project have been successfully made and has undergone several test and observation. Based on the test and observation result, self-patrolling drone has 6 minutes and 56 seconds flight time. Line follower system used in this project has distance estimation with 0.51cm accuracy and cruise control with 15.66cm/s accuracy, in contrast with GPS based indoor navigation system that has 4.5-8m accuracy, line follower navigation system shows quite significant improvement in terms of accuracy. Moreover, line follower navigation in this project can be implemented effectively up to 48cm/s cruising speed

A Holistic Approach to Energy Harvesting for Indoor Robots:Theoretical Framework and Experimental Validations

Service robotics is a fast expanding market. Inside households, domestic robots can now accomplish numerous tasks, such as floor cleaning, surveillance, or remote presence. Their sales have considerably increased over the past years. Whereas 1.05 million domestic service robots were reportedly sold in 2009, at least 2.7 million units were sold in 2013. Consequently, this growth gives rise to an increase of the energy needs to power such a large and growing fleet of robots. However, the unique properties of mobile robots open some new fields of research. We must find technologies that are suitable for decreasing the energy requirements and thus further advance towards a sustainable development. This thesis tackles two fundamental goals based on a holistic approach of the global problem. The first goal is to reduce the energy needs by identifying key technologies in making energy-efficient robots. The second goal is to leverage innovative indoor energy sources to increase the ratio of renewable energies scavenged from the environment. To achieve our first goal, new energy-wise metrics are applied to real robotic hardware. This gives us the means to assess the impact of some technologies on the overall energy balance. First, we analysed seven robotic vacuum cleaners from a representative sample of the market that encompasses a wide variety of technologies. Simultaneous Localisation and Mapping (SLAM) was identified as a key technology to reduce energy needs when carrying out such tasks. Even if the instantaneous power is slightly increased, the completion time of the task is greatly reduced. We also analysed the needed sensors to achieve SLAM, as they are largely diversified. This work tested three sensors using three different technologies. We identified several important metrics. As of our second goal, potential energy sources are compared to the needs of an indoor robot. The sunshine coming through a building's apertures is identified as a promising source of renewable power. Numerical simulations showed how a mobile robot is mandatory to take full advantage of this previously unseen situation, as well as the influence of the geometric parameters on the yearly energy income under ideal sunny conditions. When considering a real system, the major difficulty to overcome is the tracking of the sunbeam along the day. The proposed algorithm uses a hybrid method. A high-level cognitive approach is responsible for the initial placement. Following realignments during the day are performed by a low-level reactive behaviour. A solar harvesting module was developed for our research robot. The tests conducted inside a controlled environment demonstrate the feasibility of this concept and the good performances of the aforementioned algorithm. Based on a realistic scenario and weather conditions, we computed that between 1 and 14 days of recharge could be necessary for a single cleaning task. In the future, our innovative technology could greatly lower the energy needs of service robots. However, it is not completely possible to abandon the recharge station due to occasional bad weather. The acceptance of this technology inside the user's home ecosystem remains to be studied