Warning: You are viewing this site with an outdated/unsupported browser.
Please update your browser or consider using a different one in order to view this site without issue.
For a list of browsers that this site supports, see our Supported Browsers page.
Events for August 2023 – Robotics Institute Carnegie Mellon UniversitySkip to content
Title: Multi-agent Multi-objective Ergodic Search Abstract: In order to find points of interest in a given domain, many planners use a priori information to guide the search to expedite the detection of targets. We present an approach to direct multiple agents (MA) to search a given domain subject to multiple objectives (MO), each characterized by its own information […]
Title: Stochastic Optimization for Autonomous Navigation, Leveraging Parallel Computation Abstract: Stochastic Optimal Control (SOC) is a framework that allows disturbances and uncertainty in system models to be accounted for in its optimization framework. Despite accounting for this uncertainty, many first and second order methods for solving SOC problems are subject to local minima and are […]
Title: Solving Multi-Agent Target Assignment and Path Finding with a Single Constraint Tree Abstract: Multi-Agent Path Finding (MAPF) and Combined Target-Assignment and Path-Finding problem (TAPF) arise in many applications such as robotics, computer gaming, warehouse automation and traffic management at road intersections. Combined Target-Assignment and Path-Finding problem (TAPF) requires simultaneously assigning targets to agents and [...]
Title: Learning Legged Robot Agility: Sim-to-Real and Beyond Abstract: Legged robotics has seen significant advancements in both manipulation and locomotion. However, there remain significant gaps compared to their biological counterparts, particularly in energy efficiency, natural motion, and the capacity for agile skills. This thesis primarily focuses on two aspects: the unified control of legged manipulators [...]
Title: Computer Vision-Based Phenotyping in Agriculture: Leveraging Semantic Information for Non-Destructive Small Crop Analysis Abstract: Fast and reliable non-destructive phenotyping of plants plays an important role in precision agriculture, as the information enables farmers to make real-time crop management decisions without affecting yield. To non-destructively phenotype crops, computer and stereo-vision based methods are commonly used, [...]
Title: Multi-Robot Control using Control Barrier Functions: Theory and Application Abstract: Control Barrier Functions (CBFs) have emerged as a powerful theoretical tool for designing controllers with provable safety guarantees. This work presents a novel methodology that leverages CBFs to synthesize controllers for multi-robot coordination. Two multi-agent use cases are explored, i.e., a) Non-Cooperative Herding and [...]
Title: A Learning Approach to Understand How Spinal Cord Learns Multiple Behaviors Abstract: The spinal cord plays a crucial role in the control of human locomotion, generating motor patterns and coordinating reflex responses to sensory signals. Although this spinal control is traditionally viewed as a simple relay system, more recent neurophysiological evidence points to a [...]
Title: Improving Robotic Ultrasound AI Using Optical Flow Abstract: Ultrasound is an important modality for medical intervention such as vascular access because it is safe, portable, and low-cost. However, ultrasound scanning requires trained sonographers who are scarce, and it can be challenging to perform ultrasound examinations in disaster or battlefield scenarios. This motivates us to automate [...]
Abstract: Soft robotic manipulators present many unique advantages in difficult manipulation tasks. The inherent compliance of soft robots' constituent deformable material makes them safe and reliable in delicate tasks such as harvesting fruit and assisting in household work. To address challenges in proprioceptive and tactile sensing for soft robots, we present a family of vision-based [...]
Title: SuperLoop: a LIDAR-based SLAM Back-end for Underground Exploration Abstract: Robots deployed in underground scenarios require a SLAM system that can handle a variety of challenges, such as the absence of GPS, large scale maps, bad illumination, and geometrically degenerate environments. It is nearly impossible for any SLAM solution to handle all these challenges perfectly, specially [...]
Abstract: Humans learn by interacting with their surroundings using all of their senses. The first of these senses to develop is touch, and it is the first way that young humans explore their environment, learn about objects, and tune their cost functions (via pain or treats). Yet, robots are often denied this highly informative and [...]
Title: PyCubed-Mini: A Low-Cost, Open-Source Satellite Research Platform Abstract: Satellite development has become more accessible with decreasing launch costs and shrinking hardware. However, the expenses associated with pre-built satellite kits remain high, making it difficult for student and hobbyist teams to participate. The lack of standardized satellite hardware and software further adds to the challenge, [...]
Abstract: We present a framework that acts as an "intuitive physics reasoner" which takes in strategies expressed in natural language (whether from a human or LLM), and assesses their validity based on a physics knowledge library. We believe the ability to quickly determine whether a strategy is worth considering and allocating further resources to planning […]
Title: Multi-Robot Information Gathering for Spatiotemporal Environment Modelling Abstract: Learning to predict or forecast spatiotemporal (ST) environmental processes from a sparse set of samples collected autonomously is a difficult task from both a sampling perspective (collecting the best sparse samples) and from a learning perspective (predicting unseen locations or forecasting the next timestep). We investigate […]
Title: Towards Mechanical Communication in Multi-Agent Locomotive Systems: Principally Kinematic Robots on a Shared Platform Abstract: Many biological multi-agent systems exhibit a mechanism for information exchange among individuals known as mechanical communication, which leads to the emergence of collective behavior within the group. One such example is the swarming behavior of bacteria, where they form rafts […]
Abstract Designing safe and reliable robotic assistance for caregiving is a grand challenge in robotics. A sixth of the United States population is over the age of 65 and in 2014 more than a quarter of the population had a disability. Robotic caregivers could positively benefit society; yet, physical robotic assistance presents several challenges and […]
Abstract: We first consider the problem of estimating context, specifically key features of the human state. We predict engagement-related events in an educational activity before the end of that activity, which could allow the robot to provide feedback early enough to improve the human's experience. We then explore generating nonverbal affective robot behavior by correlating […]
Abstract: In robotics, understanding the link between perception and action is pivotal. Typically, perception systems process sensory data into state representations like segmentations and bounding boxes, which a planner uses to plan actions. However, this state estimation approach can fail in environments with partial observability, and in cases with challenging object properties like transparency and deformability. […]
The RI Picnic will be held at the Vietnam Veteran's Pavilion @ Schenley Park on Overlook Drive, Tuesday, August 29, 1-7pm. SOCIALIZE, EAT, DRINK & BE MERRY! Receive this year's RI giveaway item; witness the exciting final rounds of the annual RI croquet tournament; enjoy lawn games right at our own pavilion area. Plan to spend some time at the […]
Abstract: Humans adapt continuously to the world around us, allowing us to acquire new skills and explore diverse environments seamlessly. Current AI methods, however, cannot attain this versatility. Instead, they are typically trained with vast datasets, and learn all tasks simultaneously. However, the trained models have limited ability to adapt to changing contexts, and are […]
Abstract: Accurate satellite based positioning revolutionized several industries over the past two decades from agriculture to transportation. However, conventional GNSS receivers consume significant amounts of energy and are too large for many applications, including wildlife-tracking which is critical for conservation efforts and improving our understanding of the global climate. To address this capability gap, we […]