13 accepted papers
Categorical Distributional Reinforcement Learning (CDRL) has demonstrated superior sample efficiency in learning complex tasks compared to conventional Reinforcement Learning (RL) approaches. However, the practical application of CDRL is encumbered by challenging projection steps, detailed parameter…
Monocular depth estimation is a rudimentary problem for robotic perception systems and downstream applications. However, depth estimation from a single image is an inherently ill-posed problem due to data loss related to projection from 3D to 2D. Recent studies address the discrepancy between camera
Cane pruning grapevines is a complex manual task requiring expert vine assessment to determine which canes to prune. This paper presents Archie Jnr, which was developed to autonomously assess the structure of the vine and prune the lower-quality canes as an expert pruner would. The platform has been…
Apple fruitlet thinning is critical in cultivating high-quality apples, requiring an expert workforce to manage the orchard. The thinning process requires precise mapping of fruitlet clusters across the tree branches to manage the desired load for each tree. This paper presents Archie Snr, which was…
Reinforcement Learning (RL) has been widely used to solve tasks where the environment consistently provides a dense reward value. However, in real-world scenarios, rewards can often be poorly defined or sparse. Auxiliary signals are indispensable for discovering efficient exploration strategies and…
Over the last decade, a plethora of soft robotic devices have been proposed for the execution of complex grasping and dexterous manipulation tasks. Tasks requiring such increased dexterity are typically executed using fully-actuated, rigid end-effectors equipped with sophisticated sensing and contro…
Model Free Reinforcement Learning (MFRL) has shown significant promise for learning dexterous robotic manipulation tasks, at least in simulation. However, the high number of samples, as well as the long training times, prevent MFRL from scaling to complex real-world tasks. Model- Based Reinforcement…
Soft robotic devices have been popular in handling intricate grasping and dexterous manipulation tasks, serving as an alternative to conventional, rigid end-effectors. These devices are relatively simple, lightweight, and cost-effective. Recently, kirigami based structures have been used to create l…
Task-oriented dialogue system has a vital role in Human-Robot Interaction (HRI). However, it has been developed based on conventional pipeline approach which has several drawbacks; expensive, time-consuming, and so on. Based on this approach, developers manually define a robot's behaviour such as ge…
A robot cannot be warm and friendly - or can it? To explore whether a robot can be a medical receptionist, we developed a robotic system for interacting with patients at a doctor's clinic, including acting friendly. We designed the robot to interact naturally with patients at the start and finish of…
The motivation of the work presented here is to create a component of a safety system based on 3D lidar sensors, specifically for industrial environments where some rules can be set for people who will be in close proximity to working robots. Specifically, the operating procedure that is put in plac…
The motivation of the work presented here is to create a component of a safety system based on 3D lidar sensors, specifically for industrial environments where some rules can be set for people who will be in close proximity to working robots. Specifically, the operating procedure that is put in plac
Mobile service robots have the potential to improve the efficiency of fruit production in orchards. One of the key tasks that such robots must perform is traversing the rows. Many of the past implementations of row following in orchards have been developed for rows where the trees appear like walls…