21 accepted papers
Vision-based tactile sensors enable high-resolution tactile perception by capturing image-based contact data. However, their utility in tactile localization is limited by their inherently small and local sensing area, as well as their dependence on distinct object surface features. We propose TacTap…
Reinforcement learning (RL) is widely used for humanoid control, with on-policy methods such as Proximal Policy Optimization (PPO) enabling robust training via large-scale parallel simulation and, in some cases, zero-shot deployment to real robots. However, the low sample efficiency of on-policy alg…
Due to the widespread use of LLMs and the rising critical ethical and safety concerns, LLM unlearning methods have been developed to remove harmful knowledge and undesirable capabilities. In this context, evaluations are mostly based on single-value metrics such as QA accuracy. However, these metric…
Endowing the curved surfaces of rounded vision-based tactile fingers is essential for dexterous robotic manipulation, as they offer more sufficient contact with the environment. However, current rounded designs are constrained by a low sensing frequency (30–60 Hz) and the need for recalibration when
This paper proposes an informative trajectory planning approach, namely, adaptive particle filter tree with sigma point-based mutual information reward approximation (ASPIRe), for mobile target search and tracking (SAT) in cluttered environments with limited sensing field of view. We develop a novel…
Performing acrobatic maneuvers like dynamic jumping in bipedal robots presents significant challenges in terms of actuation, motion planning, and control. Traditional approaches to these tasks often simplify dynamics to enhance computational efficiency, potentially overlooking critical factors such
This paper presents a Genetic Algorithm (GA) designed to reconfigure a large group of modular Unmanned Aerial Vehicles (UAVs), each with different weights and inertia parameters, into an over-actuated flight structure with improved dynamic properties. Previous research efforts either utilized expert…
Vision-based Tactile Sensors (VBTSs) show significant promise in that they can leverage image measurements to provide high-spatial-resolution human-like performance. However, current VBTS designs, typically confined to the fingertips of robotic grippers, prove somewhat inadequate, as many grasping a
Visual planning simulates how humans make decisions to achieve desired goals in the form of searching for visual causal transitions between an initial visual state and a final visual goal state. It has become increasingly important in egocentric vision with its advantages in guiding agents to perfor…
Existing motion planning approaches for over-actuated unmanned aerial vehicle (UAV) platforms can achieve online planning without considering dynamics. However, in many envisioned application areas such as aerial manipulation, payload delivery, and moving target tracking, it is critical to ensure dy…
This paper presents a novel modular robot system that can self-reconfigure to achieve omnidirectional movements for collaborative object transportation. Each robotic module is equipped with a steerable omni-wheel for navigation and is shaped as a regular icositetragon with a permanent magnet install…
The performance of over-actuated Unmanned Aerial Vehicles (UAVs) is significantly influenced by aerodynamic effects, as they are subject to different airflow conditions. For those aerodynamic effects that are difficult to model but could occur repeatedly, Iterative Learning Control (ILC) has great p
GelSight sensors that estimate contact geometry and force by reconstructing the deformation of their soft elastomer from images would yield poor force measurements when the elastomer deforms uniformly or reaches deformation saturation. Here we present an L <inline-formula xmlns:mml="http://www.w3.or
We investigate the sequential manipulation planning problem for unmanned aerial manipulators (UAMs). Unlike prior work that primarily focuses on one-step manipulation tasks, sequential manipulations require coordinated motions of a UAM's floating base, the manipulator, and the object being manipulat…
Overactuated multirotor unmanned aerial vehicles (UAVs) usually consist of multiple tiltable thrust actuators. The controllers are mostly designed by regarding the thrust forces and actuator tilting angles as inputs of outer-loop position and attitude controllers, while formulating an inner-loop con
Tracking position and orientation independently affords more agile maneuver for over-actuated multirotor Unmanned Aerial Vehicles (UAVs) while introducing undesired downwash effects; downwash flows generated by thrust generators may counteract others due to close proximity, which significantly threa…
We devise a cooperative planning framework to generate optimal trajectories for a robot duo tethered by a flexible net to gather scattered objects spread in a large area. Specifically, the proposed planning framework first produces a set of dense waypoints for each robot, serving as the initializati
Fully-actuated multi-rotor aerial platforms are receiving increasing research interests for the capability of six degree-of-freedom (DOF) motions such as hovering at non-horizontal attitude angles. Existing real world hardware and experiments have demonstrated such capability for a limited range of
Overhead manipulation tasks often require collaborations between two operators, which becomes challenging in confined spaces such as in a compartment. Supernumerary Robotic Limb (SuperLimb), as a promising wearable robotic solution, can provide assistance in terms of broader workspace, wider manipul
Multirotor copters with full six Degree of Freedom (DoF) maneuvering are often overactuated. The control allocation of overactuated UAV platforms can have an infinite number of solutions due to their redundancy. The most common allocation framework is based on Force Decomposition (FD), which provide
This paper presents a technique to model statically indeterminate forces based on stiffness matrices for multi-limbed climbing robots. Current wall climbing robots in literature overlook statically indeterminate forces, causing an incapability to estimate climbing failure under certain circumstances…