Sethu Vijayakumar
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View article: Human-in-the-loop Optimisation in Robot-assisted Gait Training
Human-in-the-loop Optimisation in Robot-assisted Gait Training Open
Wearable robots offer a promising solution for quantitatively monitoring gait and providing systematic, adaptive assistance to promote patient independence and improve gait. However, due to significant interpersonal and intrapersonal varia…
View article: Assist-as-needed Control for FES in Foot Drop Management
Assist-as-needed Control for FES in Foot Drop Management Open
Foot drop is commonly managed using Functional Electrical Stimulation (FES), typically delivered via open-loop controllers with fixed stimulation intensities. While users may manually adjust the intensity through external controls, this ap…
View article: ENHANCED FALL DETECTION IN ELDERLY CARE USING MOTION HISTORY IMAGE AND CORRELATION FACTOR
ENHANCED FALL DETECTION IN ELDERLY CARE USING MOTION HISTORY IMAGE AND CORRELATION FACTOR Open
Falls are a significant concern within the senior care system, often leading to serious injuries and health complications. This article introduces a novel approach for detecting falls using Motion History Image (MHI) and a correlation fact…
View article: Few-Shot Transfer of Tool-Use Skills Using Human Demonstrations With Proximity and Tactile Sensing
Few-Shot Transfer of Tool-Use Skills Using Human Demonstrations With Proximity and Tactile Sensing Open
Tools extend the manipulation abilities of robots, much like they do for humans. Despite human expertise in tool manipulation, teaching robots these skills faces challenges. The complexity arises from the interplay of two simultaneous poin…
View article: Model-based optimisation for the personalisation of robot-assisted gait training
Model-based optimisation for the personalisation of robot-assisted gait training Open
Personalised rehabilitation can be key to promoting gait independence and quality of life. Robots can enhance therapy by systematically delivering support in gait training, but often use one-size-fits-all control methods, which can be subo…
View article: Perceptive Locomotion Through Whole-Body MPC and Optimal Region Selection
Perceptive Locomotion Through Whole-Body MPC and Optimal Region Selection Open
Real-time synthesis of legged locomotion maneuvers in challenging industrial settings is still an open problem, requiring simultaneous determination of footsteps locations several steps ahead while generating whole-body motions close to th…
View article: Learning Visuotactile Estimation and Control for Non-prehensile Manipulation under Occlusions
Learning Visuotactile Estimation and Control for Non-prehensile Manipulation under Occlusions Open
Manipulation without grasping, known as non-prehensile manipulation, is essential for dexterous robots in contact-rich environments, but presents many challenges relating with underactuation, hybrid-dynamics, and frictional uncertainty. Ad…
View article: Efficient Learning of Object Placement with Intra-Category Transfer
Efficient Learning of Object Placement with Intra-Category Transfer Open
Efficient learning from demonstration for long-horizon tasks remains an open challenge in robotics. While significant effort has been directed toward learning trajectories, a recent resurgence of object-centric approaches has demonstrated …
View article: An Efficient Representation of Whole-body Model Predictive Control for Online Compliant Dual-arm Mobile Manipulation
An Efficient Representation of Whole-body Model Predictive Control for Online Compliant Dual-arm Mobile Manipulation Open
Dual-arm mobile manipulators can transport and manipulate large-size objects with simple end-effectors. To interact with dynamic environments with strict safety and compliance requirements, achieving whole-body motion planning online while…
View article: Explicit Contact Optimization in Whole-Body Contact-Rich Manipulation
Explicit Contact Optimization in Whole-Body Contact-Rich Manipulation Open
Humans can exploit contacts anywhere on their body surface to manipulate large and heavy items, objects normally out of reach or multiple objects at once. However, such manipulation through contacts using the whole surface of the body rema…
View article: Learning Precise Affordances from Egocentric Videos for Robotic Manipulation
Learning Precise Affordances from Egocentric Videos for Robotic Manipulation Open
Affordance, defined as the potential actions that an object offers, is crucial for embodied AI agents. For example, such knowledge directs an agent to grasp a knife by the handle for cutting or by the blade for safe handover. While existin…
View article: Learning Deep Dynamical Systems using Stable Neural ODEs
Learning Deep Dynamical Systems using Stable Neural ODEs Open
Learning complex trajectories from demonstrations in robotic tasks has been effectively addressed through the utilization of Dynamical Systems (DS). State-of-the-art DS learning methods ensure stability of the generated trajectories; howev…
View article: Learning Goal-Directed Object Pushing in Cluttered Scenes With Location-Based Attention
Learning Goal-Directed Object Pushing in Cluttered Scenes With Location-Based Attention Open
In complex scenarios where typical pick-and-place techniques are insufficient, often non-prehensile manipulation can ensure that a robot is able to fulfill its task. However, non-prehensile manipulation is challenging due to its underactua…
View article: Impact-Aware Bimanual Catching of Large-Momentum Objects
Impact-Aware Bimanual Catching of Large-Momentum Objects Open
This paper investigates one of the most challenging tasks in dynamic manipulation -- catching large-momentum moving objects. Beyond the realm of quasi-static manipulation, dealing with highly dynamic objects can significantly improve the r…
View article: Latent Object Characteristics Recognition with Visual to Haptic-Audio Cross-modal Transfer Learning
Latent Object Characteristics Recognition with Visual to Haptic-Audio Cross-modal Transfer Learning Open
Recognising the characteristics of objects while a robot handles them is crucial for adjusting motions that ensure stable and efficient interactions with containers. Ahead of realising stable and efficient robot motions for handling/transf…
View article: Adaptive Control for Triadic Human-Robot-FES Collaboration in Gait Rehabilitation: A Pilot Study
Adaptive Control for Triadic Human-Robot-FES Collaboration in Gait Rehabilitation: A Pilot Study Open
The hybridisation of robot-assisted gait training and functional electrical stimulation (FES) can provide numerous physiological benefits to neurological patients. However, the design of an effective hybrid controller poses significant cha…
View article: Online Multicontact Receding Horizon Planning via Value Function Approximation
Online Multicontact Receding Horizon Planning via Value Function Approximation Open
Planning multicontact motions in a receding horizon fashion requires a value function to guide the planning with respect to the future, e.g., building momentum to traverse large obstacles. Traditionally, the value function is approximated …
View article: Safe and compliant control of redundant robots using superimposition of passive task-space controllers
Safe and compliant control of redundant robots using superimposition of passive task-space controllers Open
Animals are capable of robust and reliable control in unstructured environments, where they effortlessly overcome the uncertainty of interaction and are capable of exploiting singularities. These conditions are a well-known challenge for r…
View article: RoLoMa: robust loco-manipulation for quadruped robots with arms
RoLoMa: robust loco-manipulation for quadruped robots with arms Open
Deployment of robotic systems in the real world requires a certain level of robustness in order to deal with uncertainty factors, such as mismatches in the dynamics model, noise in sensor readings, and communication delays. Some approaches…
View article: Online Estimation of Articulated Objects with Factor Graphs using Vision and Proprioceptive Sensing
Online Estimation of Articulated Objects with Factor Graphs using Vision and Proprioceptive Sensing Open
From dishwashers to cabinets, humans interact with articulated objects every day, and for a robot to assist in common manipulation tasks, it must learn a representation of articulation. Recent deep learning learning methods can provide pow…
View article: Few-Shot Learning of Force-Based Motions From Demonstration Through Pre-training of Haptic Representation
Few-Shot Learning of Force-Based Motions From Demonstration Through Pre-training of Haptic Representation Open
In many contact-rich tasks, force sensing plays an essential role in adapting the motion to the physical properties of the manipulated object. To enable robots to capture the underlying distribution of object properties necessary for gener…
View article: Nonprehensile Planar Manipulation through Reinforcement Learning with Multimodal Categorical Exploration
Nonprehensile Planar Manipulation through Reinforcement Learning with Multimodal Categorical Exploration Open
Developing robot controllers capable of achieving dexterous nonprehensile manipulation, such as pushing an object on a table, is challenging. The underactuated and hybrid-dynamics nature of the problem, further complicated by the uncertain…
View article: A behavioural transformer for effective collaboration between a robot and a non-stationary human
A behavioural transformer for effective collaboration between a robot and a non-stationary human Open
A key challenge in human-robot collaboration is the non-stationarity created by humans due to changes in their behaviour. This alters environmental transitions and hinders human-robot collaboration. We propose a principled meta-learning fr…
View article: Online Multi-Contact Receding Horizon Planning via Value Function Approximation
Online Multi-Contact Receding Horizon Planning via Value Function Approximation Open
Planning multi-contact motions in a receding horizon fashion requires a value function to guide the planning with respect to the future, e.g., building momentum to traverse large obstacles. Traditionally, the value function is approximated…
View article: POS0397 SHORT-TERM (2 YEARS) FRACTURE RISK PREDICTION: A MACHINE LEARNING APPROACH
POS0397 SHORT-TERM (2 YEARS) FRACTURE RISK PREDICTION: A MACHINE LEARNING APPROACH Open
View article: Adaptive assistive robotics: a framework for triadic collaboration between humans and robots
Adaptive assistive robotics: a framework for triadic collaboration between humans and robots Open
Robots and other assistive technologies have a huge potential to help society in domains ranging from factory work to healthcare. However, safe and effective control of robotic agents in these environments is complex, especially when it in…
View article: Learning Personalised Human Sit-to-Stand Motion Strategies via Inverse Musculoskeletal Optimal Control
Learning Personalised Human Sit-to-Stand Motion Strategies via Inverse Musculoskeletal Optimal Control Open
Physically assistive robots and exoskeletons have great potential to help humans with a wide variety of collaborative tasks. However, a challenging aspect of the control of such devices is to accurately model or predict human behaviour, wh…
View article: Topology-Based MPC for Automatic Footstep Placement and Contact Surface Selection
Topology-Based MPC for Automatic Footstep Placement and Contact Surface Selection Open
State-of-the-art approaches to footstep planning assume reduced-order dynamics when solving the combinatorial problem of selecting contact surfaces in real time. However, in exchange for computational efficiency, these approaches ignore jo…
View article: RGB-D-Inertial SLAM in Indoor Dynamic Environments with Long-term Large Occlusion
RGB-D-Inertial SLAM in Indoor Dynamic Environments with Long-term Large Occlusion Open
This work presents a novel RGB-D-inertial dynamic SLAM method that can enable accurate localisation when the majority of the camera view is occluded by multiple dynamic objects over a long period of time. Most dynamic SLAM approaches eithe…
View article: OpTaS: An Optimization-based Task Specification Library for Trajectory Optimization and Model Predictive Control
OpTaS: An Optimization-based Task Specification Library for Trajectory Optimization and Model Predictive Control Open
This paper presents OpTaS, a task specification Python library for Trajectory Optimization (TO) and Model Predictive Control (MPC) in robotics. Both TO and MPC are increasingly receiving interest in optimal control and in particular handli…