Taskin Padir
Tactile sensing allows robots to gather detailed geometric information about objects through physical interaction, complementing vision-based approaches. However, efficiently acquiring useful tactile data remains challenging due to the…
Autonomous driving requires reasoning about interactions with surrounding traffic. A prevailing approach is large-scale imitation learning on expert driving datasets, aimed at generalizing across diverse real-world scenarios. For online…
The presentation of a robot's capability and identity directly influences a human collaborator's perception and implicit trust in the robot. Unlike humans, a physical robot can simultaneously present different identities and have them…
Successful navigation in outdoor environments requires accurate prediction of the physical interactions between the robot and the terrain. Many prior methods rely on geometric or semantic labels to classify traversable surfaces. However,…
Recent large-scale Vision Language Action (VLA) models have shown superior performance in robotic manipulation tasks guided by natural language. However, current VLA models suffer from two drawbacks: (i) generation of massive tokens leading…
Object 6D pose estimation is a critical challenge in robotics, particularly for manipulation tasks. While prior research combining visual and tactile (visuotactile) information has shown promise, these approaches often struggle with…
The inspection of confined critical infrastructure such as attics or crawlspaces is challenging for human operators due to insufficient task space, limited visibility, and the presence of hazardous materials. This paper introduces a…
Recent advances in quadrupedal locomotion have focused on improving stability and performance across diverse environments. However, existing methods often lack adequate safety analysis and struggle to adapt to varying payloads and complex…
Traditional approaches to motion modeling for skid-steer robots struggle with capturing nonlinear tire-terrain dynamics, especially during high-speed maneuvers. In this paper, we tackle such nonlinearities by enhancing a dynamic unicycle…
Platooning of autonomous vehicles has the potential to increase safety and fuel efficiency on highways. The goal of platooning is to have each vehicle drive at a specified speed (set by the leader) while maintaining a safe distance from its…
Autonomous vehicle platoons present near- and long-term opportunities to enhance operational efficiencies and save lives. The past 30 years have seen rapid development in the autonomous driving space, enabling new technologies that will…
Shared control can ease and enhance a human operator's ability to teleoperate robots, particularly for intricate tasks demanding fine control over multiple degrees of freedom. However, the arbitration process dictating how much autonomous…
This paper presents a distributed model predictive control (DMPC) algorithm for a heterogeneous platoon using arbitrary communication topologies, provided each vehicle can communicate with a preceding vehicle in the platoon. The proposed…
Accurate identification of complex terrain characteristics, such as soil composition and coefficient of friction, is essential for model-based planning and control of mobile robots in off-road environments. Spectral signatures leverage…
Visual navigation has received significant attention recently. Most of the prior works focus on predicting navigation actions based on semantic features extracted from visual encoders. However, these approaches often rely on large datasets…
Objective: For transradial amputees, robotic prosthetic hands promise to regain the capability to perform daily living activities. Current control methods based on physiological signals such as electromyography (EMG) are prone to yielding…
Learning for robot navigation presents a critical and challenging task. The scarcity and costliness of real-world datasets necessitate efficient learning approaches. In this letter, we exploit Euclidean symmetry in planning for 2D…
The ANA Avatar XPRIZE was a four-year competition to develop a robotic "avatar" system to allow a human operator to sense, communicate, and act in a remote environment as though physically present. The competition featured a unique…
Enabling humans and robots to collaborate effectively requires purposeful communication and an understanding of each other's affordances. Prior work in human-robot collaboration has incorporated knowledge of human affordances, i.e., their…
Addressing the challenge of roadside litter in the United States, which has traditionally relied on costly and ineffective manual cleanup methods, this paper presents an autonomous multi-robot system for highway litter monitoring and…