65 citations · 302 across the 20 of their papers we have counts for
7 papers · 1 filter
Simulation of Dynamic Environments for SLAM
Elia Bonetto, Chenghao Xu, Aamir Ahmad
Simulation engines are widely adopted in robotics. However, they lack either full simulation control, ROS integration, realistic physics, or photorealism. Recently, synthetic data…
Learning from synthetic data generated with GRADE
Elia Bonetto, Chenghao Xu, Aamir Ahmad
Recently, synthetic data generation and realistic rendering has advanced tasks like target tracking and human pose estimation. Simulations for most robotics applications are obtain…
Synthetic Data-based Detection of Zebras in Drone Imagery
Elia Bonetto, Aamir Ahmad
Nowadays, there is a wide availability of datasets that enable the training of common object detectors or human detectors. These come in the form of labelled real-world images and…
Multi-Task Reinforcement Learning in Continuous Control with Successor Feature-Based Concurrent Composition
Yu Tang Liu, Aamir Ahmad
Deep reinforcement learning (DRL) frameworks are increasingly used to solve high-dimensional continuous control tasks in robotics. However, due to the lack of sample efficiency, ap…
GRADE: Generating Realistic And Dynamic Environments for Robotics Research with Isaac Sim
Elia Bonetto, Chenghao Xu, Aamir Ahmad
Synthetic data and novel rendering techniques have greatly influenced computer vision research in tasks like target tracking and human pose estimation. However, robotics research h…
Accelerated Video Annotation driven by Deep Detector and Tracker
Eric Price, Aamir Ahmad
Annotating object ground truth in videos is vital for several downstream tasks in robot perception and machine learning, such as for evaluating the performance of an object tracker…
Reinforcement Learning based Autonomous Multi-Rotor Landing on Moving Platforms
Pascal Goldschmid, Aamir Ahmad
Multi-rotor UAVs suffer from a restricted range and flight duration due to limited battery capacity. Autonomous landing on a 2D moving platform offers the possibility to replenish…