24 accepted papers
This letter proposes a mole-inspired scratch-digging robot to investigate four-limb subsurface locomotion in granular media. The robot integrated a conical head, a rigid torso, a hybrid crank-rocker and crank-slider forelimb that reproduces scratch-digging strokes, and a two-degree-of-freedom (DOF)
Hybrid representation Visual Simultaneous Localization and Mapping (VSLAM) systems combine the inherent strengths of both discrete and field representations. They promise high-precision tracking and photo-realistic dense mapping. However, current keyframe selection methods in hybrid representation V…
Although the LiDAR SLAM technique has been already widely deployed on various robots, it may still suffers from degeneracy caused by inadequate constraints in scenes with sparse geometric features. If the degeneracy is not detected and properly processed, the accuracy of localization and mapping wil
Keyframe selection plays a crucial role in balancing computational efficiency and localization accuracy in Visual Simultaneous Localization and Mapping (VSLAM) systems. Existing keyframe selection methods often struggle to capture high-level semantic information in environments where multiple semant
Although Bayesian interaction primitives exhibit strong capabilities in skill learning and reproduction for physical human–robot interactions, they require extensive demonstrations and fail to adequately address the inherent geometric constraints. In this study, we propose the iRie-ProMPs method, ba
Limited by the working principles, LiDAR-SLAM systems suffer from the degeneration phenomenon in environments such as long corridors and tunnels, due to the lack of sufficient geometric features for frame-to-frame matching. The accuracy and sensitivity of existing degeneracy detection methods need t…
Conventional mobile robots typically include a single locomotion mode and require additional arms to transport objects. To address the challenges of traversing in diverse environments and transporting objects, a novel transformable multi-mode Mecanum-wheeled mobile robot is proposed in this paper. O
Large-scale point cloud consists of a multitude of individual objects, thereby encompassing rich structural and underlying semantic contextual information, resulting in a challenging problem in efficiently segmenting a point cloud. Most existing researches mainly focus on capturing intricate local f…
Visual relocalization is a fundamental problem in computer vision and robotics. Recently, regression-based methods become popular and they can be categorized into two classes: absolute pose regression and scene coordinate regression. In this work, we present a combined regression network that jointl…
With the development of the global marine industry, the demand to investigate underwater environments using robots is increasing. Inspired by the unique structure and excellent swimming ability of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Aurel
As a hard high-altitude work, power transmission line inspection increasingly demands robots to conduct in place of the human being. A variety of robots have been developed to this end, with basic locomotion and inspection implemented on the lines. However, most current line inspection robots (LIRs)…
Loop closure detection is a key technology for long-term robot navigation in complex environments. In this paper, we present a global descriptor, named Normal Distribution Descriptor (NDD), for 3D point cloud loop closure detection. The descriptor encodes both the probability density score and entro…
"Current polarimetric 3D reconstruction methods, including those in the well-established shape from polarization literature, are all developed under the orthographic projection assumption. In the case of a large field of view, however, this assumption does not hold and may result in significant reco…
Spatio-temporal information is key to resolve occlusion and depth ambiguity in 3D human pose estimation. Previous methods have focused on either temporal contexts or local-to-global architectures that embed fixed-length spatiotemporal information. To date, there have not been effective proposals to…
Soft climbing robots have been attracting increasing attention in soft robotics community, and a lot of prototypes been proposed with basic climbing function implemented. Climbing on poles is a challenge with soft robots, and the capability of current pole-climbing soft robots needs to be improved i…
Policy optimization in reinforcement learning requires the selection of numerous hyperparameters across different environments. Fixing them incorrectly may negatively impact optimization performance leading notably to insufficient or redundant learning. Insufficient learning (due to convergence to l
Robot motion control aims to generate control inputs for a robotic system to track a planned trajectory. Feedback provided by sensors plays an essential role in motion control by improving system performance when external disturbances and/or initial errors exist. However, feedback signals, such as i…
Recent works on semantic Simultaneous Localization and Mapping (SLAM) utilizing object landmarks have shown superiority in terms of robustness and accuracy in tracking and localization. 3D object landmarks represented by a cubic or quadric surface are inferred from 2D object bounding boxes which are…
Deep Reinforcement Learning (RL) is a promising approach for adaptive robot control, but its current application to robotics is currently hindered by high sample requirements. To alleviate this issue, we propose to exploit the symmetries present in robotic tasks. Intuitively, symmetries from observe
Climbing or crawling robots may be widely applied in agriculture, forestry, military, construction industry, disaster searching and rescuing, and so on. Soft robots possess better safety, flexibility, dexterity, portability, and adaption to complex environments than traditional robots. However, ther…
For VSLAM (Visual Simultaneous Localization and Mapping), localization is a challenging task, especially for some challenging situations: textureless frames, motion blur, etc. To build a robust exploration and localization system in a given space, a submap-based VSLAM system is proposed in this pape…
For VSLAM (Visual Simultaneous Localization and Mapping), localization is a challenging task, especially for some challenging situations: textureless frames, motion blur, etc. To build a robust exploration and localization system in a given space, a submap-based VSLAM system is proposed in this pape
Re-configurable modular robotic (RMR) systems are advantageous for their reconfigurability and versatility. A new modular robot can be built for a specific task by using modules as building blocks. However, constructing a kinematic model for a newly conceived robot requires significant work. Due to…