This paper uses the smoothing and mapping framework to solve the SLAM problem in indoor environments; focusing on how some key issues such as feature extraction and data association can be handled by applying probabilistic techniques. For feature extraction, an odds ratio approach to find multiple lines from laser scans is proposed, this criterion allows to decide which model must be merged and to output the best number of models. In addition, to solve the data association problem a method based on the segments of each line is proposed. Experimental results show that high quality indoor maps can be obtained from noisy data
Stevens Institute of Technology（史蒂文斯理工学院）；Amazon Robotics（亚马逊机器人）；Exyn Technologies（Exyn科技）；SRI International（斯坦福国际研究院）
We consider the problem of autonomous mobile robot exploration in an unknown environment, taking into account a robot's coverage rate, map uncertainty, and state estimation uncertainty. This paper presents a novel exploration framework for underwater robots operating in cluttered environments, built upon simultaneous localization and mapping (SLAM) with imaging sonar. The proposed system comprises path generation, place recognition forecasting, belief propagation and utility evaluation using a virtual map, which estimates the uncertainty associated with map cells throughout a robot's workspace…
We present an open-source system for Micro-Aerial Vehicle autonomous navigation from vision-based sensing. Our system focuses on dense mapping, safe local planning, and global trajectory generation, especially when using narrow field of view sensors in very cluttered environments. In addition, details about other necessary parts of the system and special considerations for applications in real-world scenarios are presented. We focus our experiments on evaluating global planning, path smoothing, and local planning methods on real maps made on MAVs in realistic search and rescue and industrial i…
Safe Navigation in Unknown and Cluttered Environments via Direction-Aware Convex Free-Region Generation
Robotics and Autonomous Systems Thrust, The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州）机器人与自主系统方向）；Department of Electrical and Computer Engineering, National University of Singapore（新加坡国立大学电子与计算机工程系）
FRTree Planner: Robot Navigation in Cluttered and Unknown Environments with Tree of Free Regions
The Hong Kong University of Science and Technology（香港科技大学）；The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））；Great Bay University（大湾区大学）
RDA: An Accelerated Collision Free Motion Planner for Autonomous Navigation in Cluttered Environments
Southern University of Science and Technology（南方科技大学）；The University of Hong Kong（香港大学）；Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences（中国科学院深圳先进技术研究院）；Harbin Institute of Technology, Shenzhen（哈尔滨工业大学（深圳））；Sifakis Research Institute for Trustworthy Autonomous Systems（可信自主系统西法克斯研究院）
ContactDexNet: Multi-fingered Robotic Hand Grasping in Cluttered Environments through Hand-object Contact Semantic Mapping
TAMS (Technical Aspects of Multimodal Systems), Department of Informatics, Universität Hamburg（乌尔姆大学信息学院技术多模态系统部门）；Agile Robots AG（敏捷机器人公司）；Technical University of Munich（慕尼黑技术大学）
Robust Dynamic Object Detection in Cluttered Indoor Scenes via Learned Spatiotemporal Cues
Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente（代尔夫特理工大学电子工程、数学与计算机科学学院）；Department of Electrical Engineering, Wright State University（怀特塞德大学电子工程系）；Massachusetts Institute of Technology（麻省理工学院）
This paper considers the problem of safe autonomous navigation in unknown environments, relying on local obstacle sensing. We consider a control-affine nonlinear robot system subject to bounded input noise and rely on feedback linearization to determine ellipsoid output bounds on the closed-loop robot trajectory under stabilizing control. A virtual governor system is developed to adaptively track a desired navigation path, while relying on the robot trajectory bounds to slow down if safety is endangered and speed up otherwise. The main contribution is the derivation of theoretical guarantees f…
Sampling-based model predictive control (MPC) optimization methods, such as Model Predictive Path Integral (MPPI), have recently shown promising results in various robotic tasks. However, it might produce an infeasible trajectory when the distributions of all sampled trajectories are concentrated within high-cost even infeasible regions. In this study, we propose a new method called log-MPPI equipped with a more effective trajectory sampling distribution policy which significantly improves the trajectory feasibility in terms of satisfying system constraints. The key point is to draw the trajec…
Intel Labs（英特尔实验室）；Intel Tecnología de México（英特尔墨西哥技术公司）；Cinvestav（墨西哥国立理工学院高级研究中心）；Tecnologico de Monterrey（蒙特雷理工学院）；Escuela de Ingeniería y Ciencias（工程与科学学院）
This paper presents an autonomous navigation framework for reaching a goal in unknown 3D cluttered environments. The framework consists of three main components. First, a computationally efficient method for mapping the environment from the disparity measurements obtained from a depth sensor. Second, a stochastic method to generate a path to a given goal, taking into account field of view constraints on the space that is assumed to be safe for navigation. Third, a fast method for the online generation of motion plans, taking into account the robot's dynamic constraints, model, and environmenta…
Rectilinear forms of snake-like robotic locomotion are anticipated to be an advantage in obstacle-strewn scenarios characterizing urban disaster zones, subterranean collapses, and other natural environments. The elongated, laterally-narrow footprint associated with these motion strategies is well-suited to traversal of confined spaces and narrow pathways. Navigation and path planning in the absence of global sensing, however, remains a pivotal challenge to be addressed prior to practical deployment of these robotic mechanisms. Several challenges related to visual processing and localization ne…
Geometry-Aware Safety-Critical Local Reactive Controller for Robot Navigation in Unknown and Cluttered Environments
The Hong Kong University of Science and Technology（香港科技大学）；Hong Kong Baptist University（香港浸会大学）；The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））
Università degli studi di Milano（米兰大学）；Örebro Universitet（厄勒布鲁大学）；Aalto University（阿尔托大学）；Politecnico di Milano（米兰理工大学）
Identifying the environment's structure, i.e., to detect core components as rooms and walls, can facilitate several tasks fundamental for the successful operation of indoor autonomous mobile robots, including semantic environment understanding. These robots often rely on 2D occupancy maps for core tasks such as localisation and motion and task planning. However, reliable identification of structure and room segmentation from 2D occupancy maps is still an open problem due to clutter (e.g., furniture and movable object), occlusions, and partial coverage. We propose a method for the RObust Struct…
UC Berkeley（加州大学伯克利分校）；Seoul National University（首尔大学）
This paper introduces a collision avoidance system for navigating a multicopter in cluttered outdoor environments based on the recent memory-less motion planner, rectangular pyramid partitioning using integrated depth sensors (RAPPIDS). The RAPPIDS motion planner generates collision-free flight trajectories at high speed with low computational cost using only the latest depth image. In this work we extend it to improve the performance of the planner by taking the following issues into account. (a) Changes in the dynamic characteristics of the multicopter that occur during flight, such as chang…
Although, in the task of grasping via a data-driven method, closed-loop feedback and predicting 6 degrees of freedom (DoF) grasp rather than conventionally used 4DoF top-down grasp are demonstrated to improve performance individually, few systems have both. Moreover, the sequential property of that task is hardly dealt with, while the approaching motion necessarily generates a series of observations. Therefore, this paper synthesizes three approaches and suggests a closed-loop framework that can predict the 6DoF grasp in a heavily cluttered environment from continuously received vision observa…
Online coverage planning can be useful in applications like field monitoring and search and rescue. Without prior information of the environment, achieving resolution-complete coverage considering the non-holonomic mobility constraints in commonly-used vehicles (e.g., wheeled robots) remains a challenge. In this paper, we propose a hierarchical, hex-decomposition-based coverage planning algorithm for unknown, obstacle-cluttered environments. The proposed approach ensures resolution-complete coverage, can be tuned to achieve fast exploration, and plans smooth paths for Dubins vehicles to follow…
Modelling and Path Planning of Snake Robot in cluttered environment
Visvesvaraya National Institute of Technology（维斯瓦拉亚国家理工学院）；Carnegie Mellon University（卡内基梅隆大学）；Inbitorobotics（Inbitorobotics公司）；Robotics Institute, Carnegie Mellon University（卡内基梅隆大学机器人研究所）
Delft University of Technology（代尔夫特理工大学）；University of Barcelona（巴塞罗那大学）；Harvard University（哈佛大学）
Nano quadcopters are ideal for gas source localization (GSL) as they are safe, agile and inexpensive. However, their extremely restricted sensors and computational resources make GSL a daunting challenge. In this work, we propose a novel bug algorithm named `Sniffy Bug', which allows a fully autonomous swarm of gas-seeking nano quadcopters to localize a gas source in an unknown, cluttered and GPS-denied environments. The computationally efficient, mapless algorithm foresees in the avoidance of obstacles and other swarm members, while pursuing desired waypoints. The waypoints are first set for …
University of Toronto（多伦多大学）；Vector Institute for Artificial Intelligence（向量人工智能研究所）
Ultra-wideband (UWB) time difference of arrival (TDOA)-based localization has recently emerged as a promising indoor positioning solution. However, in cluttered environments, both the UWB radio positions and the obstacle-induced non-line-of-sight (NLOS) measurement biases significantly impact the quality of the position estimate. Consequently, the placement of the UWB radios must be carefully designed to provide satisfactory localization accuracy for a region of interest. In this work, we propose a novel algorithm that optimizes the UWB radio positions for a pre-defined region of interest in t…
The University of Hong Kong（香港大学）；Baidu Research（百度研究院）
In this paper, we introduce a generalized continuous collision detection (CCD) framework for the mobile robot along the polynomial trajectory in cluttered environments including various static obstacle models. Specifically, we find that the collision conditions between robots and obstacles could be transformed into a set of polynomial inequalities, whose roots can be efficiently solved by the proposed solver. In addition, we test different types of mobile robots with various kinematic and dynamic constraints in our generalized CCD framework and validate that it allows the provable collision ch…
Reactive Planning based Control for Mobile Robots in Obstacle-Cluttered Environments
Department of Automation, University of Science and Technology of China（自动化系，中国科学技术大学）；School of Intelligence Science and Engineering, Harbin Institute of Technology Shenzhen（智能科学与工程学院，哈尔滨工业大学深圳）；School of Control Science and Engineering, Dalian University of Technology（控制科学与工程学院，大连理工大学）
The autonomous operation of small quadcopters moving at high speed in an unknown cluttered environment is a challenging task. Current works in the literature formulate it as a Sense-And-Avoid (SAA) problem and address it by either developing new sensing capabilities or small form-factor processors. However, the SAA, with the high-speed operation, remains an open problem. The significant complexity arises due to the computational latency, which is critical for fast-moving quadcopters. In this paper, a novel Fast Obstacle Avoidance Motion (FOAM) algorithm is proposed to perform SAA operations. F…
Non-prehensile manipulation methods usually use a simple end effector, e.g., a single rod, to manipulate the object. Compared to the grasping method, such an end effector is compact and flexible, and hence it can perform tasks in a constrained workspace; As a trade-off, it has relatively few degrees of freedom (DoFs), resulting in an under-actuation problem with complex constraints for planning and control. This paper proposes a new non-prehensile manipulation method for the task of object retrieval in cluttered environments, using a rod-like pusher. Specifically, a candidate trajectory in a c…
Watch Your Step: Learning Semantically-Guided Locomotion in Cluttered Environment
School of Electrical and Electronic Engineering, Nanyang Technological University（南洋理工大学电气与电子工程学院）；School of Mechanical and Mining Engineering, The University of Queensland（昆士兰大学机械与采矿工程学院）
Carnegie Mellon University（卡内基梅隆大学）；Mitsubishi Heavy Industries（三菱重工）
In this work we tackle the path planning problem for a 21-dimensional snake robot-like manipulator, navigating a cluttered gas turbine for the purposes of inspection. Heuristic search based approaches are effective planning strategies for common manipulation domains. However, their performance on high dimensional systems is heavily reliant on the effectiveness of the action space and the heuristics chosen. The complex nature of our system, reachability constraints, and highly cluttered turbine environment renders naive choices of action spaces and heuristics ineffective. To this extent we have…
Collision avoidance in unknown obstacle-cluttered environments may not always be feasible. This paper focuses on an emerging paradigm shift in which potential collisions with the environment can be harnessed instead of being avoided altogether. To this end, we introduce a new sampling-based online planning algorithm that can explicitly handle the risk of colliding with the environment and can switch between collision avoidance and collision exploitation. Central to the planner's capabilities is a novel joint optimization function that evaluates the effect of possible collisions using a reflect…
