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You searched for subject:(Modular reinforcement learning). Showing records 1 – 2 of 2 total matches.

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1. Heikkilä, Filip. Autonomous Mapping of Unknown Environments Using a UAV .

Degree: Chalmers tekniska högskola / Institutionen för matematiska vetenskaper, 2020, Chalmers University of Technology

URL: http://hdl.handle.net/20.500.12380/300894 

Automatic object search in a bounded area can be accomplished using cameracarrying autonomous aerial robots. The system requires several functionalities to solve the task in a safe and efficient way, including finding a navigation and exploration strategy, creating a representation of the surrounding environment and detecting objects visually. Here we create a modular framework and provide solutions to the different subproblems in a simulated environment. The navigation and exploration subproblems are tackled using deep reinforcement learning (DRL). Object and obstacle detection is approached using methods based on the scale-invariant feature transform and the pinhole camera model. Information gathered by the system is used to build a 3D voxel map. We further show that the object detection system is capable of detecting certain target objects with high recall. The DRL approach is able to achieve navigation that avoids collisions to a high degree, but the performance of the exploration policy is suboptimal. Due to the modular character of the solution further improvements of each subsystems can easily be developed independently.

Subjects/Keywords: Deep reinforcement learning; autonomous exploration and navigation; feature extraction; object detection; voxel map; UAV; modular framework.

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Heikkilä, F. (2020). Autonomous Mapping of Unknown Environments Using a UAV . (Thesis). Chalmers University of Technology. Retrieved from http://hdl.handle.net/20.500.12380/300894

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Heikkilä, Filip. “Autonomous Mapping of Unknown Environments Using a UAV .” 2020. Thesis, Chalmers University of Technology. Accessed January 17, 2021. http://hdl.handle.net/20.500.12380/300894.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Heikkilä, Filip. “Autonomous Mapping of Unknown Environments Using a UAV .” 2020. Web. 17 Jan 2021.

Vancouver:

Heikkilä F. Autonomous Mapping of Unknown Environments Using a UAV . [Internet] [Thesis]. Chalmers University of Technology; 2020. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/20.500.12380/300894.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Heikkilä F. Autonomous Mapping of Unknown Environments Using a UAV . [Thesis]. Chalmers University of Technology; 2020. Available from: http://hdl.handle.net/20.500.12380/300894

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

2. Sodhani, Shagun. Learning competitive ensemble of information-constrained primitives.

Degree: 2019, Université de Montréal

URL: http://hdl.handle.net/1866/22537 

Subjects/Keywords: Reinforcement Learning; Hierarchical Reinforcement Learning; Information Bottleneck; Compositionality; Modular network; Apprentissage par renforcement; Apprentissage par renforcement hiérarchique; Goulot d'étranglement de l'information; Compositionnalité; Réseaux modulaires; Applied Sciences - Artificial Intelligence / Sciences appliqués et technologie - Intelligence artificielle (UMI : 0800)

…beyond Hierarchical Reinforcement Learning and is studied under the paradigm of Neural Modular… …HRL Hierarchical Reinforcement Learning LSTM Long-Short Term Memory MDP Markov Decision… …Process NMN Neural Module Network PVF Proto-Value Functions RL Reinforcement Learning RNN… …reinforcement learning algorithms that can quickly adapt to new tasks by obtaining a structured… …Hierarchical Reinforcement Learning. We review this body of literature in section 1.3 and describe… 

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Sodhani, S. (2019). Learning competitive ensemble of information-constrained primitives. (Thesis). Université de Montréal. Retrieved from http://hdl.handle.net/1866/22537

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Sodhani, Shagun. “Learning competitive ensemble of information-constrained primitives.” 2019. Thesis, Université de Montréal. Accessed January 17, 2021. http://hdl.handle.net/1866/22537.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Sodhani, Shagun. “Learning competitive ensemble of information-constrained primitives.” 2019. Web. 17 Jan 2021.

Vancouver:

Sodhani S. Learning competitive ensemble of information-constrained primitives. [Internet] [Thesis]. Université de Montréal; 2019. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/1866/22537.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Sodhani S. Learning competitive ensemble of information-constrained primitives. [Thesis]. Université de Montréal; 2019. Available from: http://hdl.handle.net/1866/22537

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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