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Quadrupeds are strong candidates for navigating challenging environments because of their agile and dynamic designs. This paper presents a methodology that extends the range of exploration for quadrupedal robots by creating an end-to-end…

We study the problem of devising a closed-loop strategy to control the position of a robot that is tracking a possibly moving target. The robot is capable of obtaining noisy measurements of the target's position. The key idea in active…

Robotics · Computer Science 2016-11-09 Zhonghshun Zhang , Pratap Tokekar

Class imbalance and label noise are pervasive in large-scale datasets, yet much of machine learning research assumes well-labeled, balanced data, which rarely reflects real world conditions. Existing approaches typically address either…

Machine Learning · Computer Science 2025-01-16 John Brandon Graham-Knight , Jamil Fayyad , Nourhan Bayasi , Patricia Lasserre , Homayoun Najjaran

Legged locomotion is a challenging task for learning algorithms, especially when the task requires a diverse set of primitive behaviors. To solve these problems, we introduce a hierarchical framework to automatically decompose complex…

Machine Learning · Computer Science 2019-05-23 Deepali Jain , Atil Iscen , Ken Caluwaerts

The Central Pattern Generator (CPG) is adept at generating rhythmic gait patterns characterized by consistent timing and adequate foot clearance. Yet, its open-loop configuration often compromises the system's control performance in…

Robotics · Computer Science 2023-10-11 Xinyu Zhang , Zhiyuan Xiao , Qingrui Zhang , Wei Pan

Recent advancements in legged robot locomotion have facilitated traversal over increasingly complex terrains. Despite this progress, many existing approaches rely on end-to-end deep reinforcement learning (DRL), which poses limitations in…

Navigating toward a known target in a noisy environment is a fundamental problem shared across biological, physical, and engineered systems. Although optimal strategies are often framed in terms of continuous, fine-grained feedback, we show…

Statistical Mechanics · Physics 2025-12-24 Abhijit Sinha , Sandeep Jangid , Tridib Sadhu , Shankar Ghosh

As all physical adaptive quantum-enhanced metrology schemes operate under noisy conditions with only partially understood noise characteristics, so a practical control policy must be robust even for unknown noise. We aim to devise a test to…

Quantum Physics · Physics 2019-07-18 Pantita Palittapongarnpim , Barry C. Sanders

Quadruped animal locomotion emerges from the interactions between the spinal central pattern generator (CPG), sensory feedback, and supraspinal drive signals from the brain. Computational models of CPGs have been widely used for…

Robotics · Computer Science 2023-02-28 Milad Shafiee , Guillaume Bellegarda , Auke Ijspeert

We propose Audio Noise Awareness using Visuals of Indoors for NAVIgation for quieter robot path planning. While humans are naturally aware of the noise they make and its impact on those around them, robots currently lack this awareness. A…

Robotics · Computer Science 2024-10-25 Vidhi Jain , Rishi Veerapaneni , Yonatan Bisk

Skateboards offer a compact and efficient means of transportation as a type of personal mobility device. However, controlling them with legged robots poses several challenges for policy learning due to perception-driven interactions and…

Robotics · Computer Science 2026-04-22 Minsung Yoon , Jeil Jeong , Sung-Eui Yoon

This paper aims to develop distributed feedback control algorithms that allow cooperative locomotion of quadrupedal robots which are coupled to each other by holonomic constraints. These constraints can arise from collaborative manipulation…

Optimization and Control · Mathematics 2019-10-03 Kaveh Akbari Hamed , Vinay R. Kamidi , Abhishek Pandala , Wen-Loong Ma , Aaron D. Ames

Previous studies have successfully demonstrated agile and robust locomotion in challenging terrains for quadrupedal robots. However, the bipedal locomotion mode for quadruped robots remains unverified. This paper explores the adaptation of…

Existing quadrupedal locomotion learning paradigms usually rely on extensive domain randomization to alleviate the sim2real gap and enhance robustness. It trains policies with a wide range of environment parameters and sensor noises to…

Robotics · Computer Science 2025-09-23 Wei Xiao , Shangke Lyu , Zhefei Gong , Renjie Wang , Donglin Wang

Animals possess a remarkable ability to navigate challenging terrains, achieved through the interplay of various pathways between the brain, central pattern generators (CPGs) in the spinal cord, and musculoskeletal system. Traditional…

Robotics · Computer Science 2024-04-30 Ge Sun , Milad Shafiee , Peizhuo Li , Guillaume Bellegarda , Auke Ijspeert , Guillaume Sartoretti

Dynamic quadrupedal locomotion over rough terrains reveals remarkable progress over the last few decades. Small-scale quadruped robots are adequately flexible and adaptable to traverse uneven terrains along sagittal direction, such as…

Robotics · Computer Science 2021-10-27 Hongwu Zhu , Dong Wang , Nathan Boyd , Ziyi Zhou , Lecheng Ruan , Aidong Zhang , Ning Ding , Ye Zhao , Jianwen Luo

Can a quadrupedal robot perform bipedal motions like humans? Although developing human-like behaviors is more often studied on costly bipedal robot platforms, we present a solution over a lightweight quadrupedal robot that unlocks the…

Robotics · Computer Science 2024-03-05 Yunfei Li , Jinhan Li , Wei Fu , Yi Wu

Quadrupedal robots show great potential for valuable real-world applications such as fire rescue and industrial inspection. Such applications often require urgency and the ability to navigate agilely, which in turn demands the capability to…

Robotics · Computer Science 2026-03-16 Zunzhi You , Haolan Guo , Yunke Wang , Chang Xu

This paper proposes an adaptive near-hover position controller for quadcopters, which can be deployed to quadcopters of very different mass, size and motor constants, and also shows rapid adaptation to unknown disturbances during runtime.…

Robotics · Computer Science 2023-05-04 Dingqi Zhang , Antonio Loquercio , Xiangyu Wu , Ashish Kumar , Jitendra Malik , Mark W. Mueller

Generating dynamic motions for legged robots remains a challenging problem. While reinforcement learning has achieved notable success in various legged locomotion tasks, producing highly dynamic behaviors often requires extensive reward…

Robotics · Computer Science 2026-01-01 Dongyun Kang , Min-Gyu Kim , Tae-Gyu Song , Hajun Kim , Sehoon Ha , Hae-Won Park
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