Maxim Likhachev's research while affiliated with Carnegie Mellon University and other places

Publications (223)

Preprint
Full-text available
Conflict-Based Search (CBS) is a popular multi-agent path finding (MAPF) solver that employs a low-level single agent planner and a high-level constraint tree to resolve conflicts. The vast majority of modern MAPF solvers focus on improving CBS by reducing the size of this tree through various strategies with few methods modifying the low level pla...
Preprint
We consider the problem of completing a set of $n$ tasks with a human-robot team using minimum effort. In many domains, teaching a robot to be fully autonomous can be counterproductive if there are finitely many tasks to be done. Rather, the optimal strategy is to weigh the cost of teaching a robot and its benefit -- how many new tasks it allows th...
Article
We present the design, integration, and evaluation of a full-stack robotic system called RoMan, which can conduct autonomous field operations involving physical interaction with its environment. RoMan offers autonomous behaviors that can be triggered from succinct, high-level human input such as “open this box and retrieve the bag inside.” The robo...
Preprint
Parallel search algorithms harness the multithreading capability of modern processors to achieve faster planning. One such algorithm is PA*SE (Parallel A* for Slow Expansions), which parallelizes state expansions to achieve faster planning in domains where state expansions are slow. In this work, we propose ePA*SE (Edge-based Parallel A* for Slow E...
Preprint
Full-text available
This work addresses the Multi-Objective Shortest Path Problem (MO-SPP): Given a graph where each edge is associated with a non-negative cost vector, MO-SPP aims to find all the Pareto-optimal paths connecting the given start and goal nodes. To solve MO-SPP, the popular multi-objective A* (MOA*) like algorithms maintain a "frontier" set at any node...
Preprint
Iterative learning control (ILC) is a powerful technique for high performance tracking in the presence of modeling errors for optimal control applications. There is extensive prior work showing its empirical effectiveness in applications such as chemical reactors, industrial robots and quadcopters. However, there is little prior theoretical work th...
Article
Pose estimation of recognized objects is fundamental to tasks such as robotic grasping and manipulation. The need for reliable grasping imposes stringent accuracy requirements on pose estimation in cluttered, occluded scenes in dynamic environments. Modern methods employ large sets of training data to learn features and object templates in order to...
Preprint
Heuristic search-based motion planning algorithms typically discretise the search space in order to solve the shortest path problem. Their performance is closely related to this discretisation. A fine discretisation allows for better approximations of the continuous search space, but makes the search for a solution more computationally costly. A co...
Preprint
Search-based techniques have shown great success in motion planning problems such as robotic navigation by discretizing the state space and precomputing motion primitives. However in domains with complex dynamic constraints, constructing motion primitives in a discretized state space is non-trivial. This requires operating in continuous space which...
Article
Homotopy classes of trajectories, arising due to the presence of obstacles, are defined as sets of trajectories that can be transformed into each other by gradual bending and stretching without colliding with obstacles. The problem of exploring/finding the different homotopy classes in an environment and the problem of finding least-cost paths rest...
Preprint
Lazy search algorithms have been developed to efficiently solve planning problems in domains where the computational effort is dominated by the cost of edge evaluation. The current approaches operate by intelligently balancing computational effort between searching the graph and evaluating edges. However these algorithms are designed to run as a si...
Preprint
Full-text available
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 e...
Article
We focus on long-sighted planning for a class of problems with multiple independent tasks that are partially observable and evolve over time. An example problem that falls into this class is a robot waiting multiple tables, referred to as tasks, in a restaurant where customers' satisfaction is partially observable and evolves over time. Our recent...
Article
In warehouse and manufacturing environments, manipulation platforms are frequently deployed at conveyor belts to perform pick-and-place tasks. Because objects on the conveyor belts are moving, robots have limited time to pick them up. This brings the requirement for fast and reliable motion planners that could provide provable real-time planning gu...
Preprint
Full-text available
We present how we formalize the waiting tables task in a restaurant as a robot planning problem. This formalization was used to test our recently developed algorithms that allow for optimal planning for achieving multiple independent tasks that are partially observable and evolve over time [1], [2].
Preprint
Full-text available
Paths planned over grids can often be suboptimal in an Euclidean space and contain a large number of unnecessary turns. Consequently, researchers have looked into post-processing techniques to improve the paths after they are planned. In this paper, we propose a novel post-processing technique, called Homotopic Visibility Graph Planning (HVG) which...
Article
Quadrotors can achieve aggressive flight by tracking complex manuevers and rapidly changing directions. Planning for aggressive flight with trajectory optimization could be incredibly fast, even in higher dimensions, and can account for dynamics of the quadrotor, however, only provides a locally optimal solution. On the other hand, planning with di...
Preprint
Consider a truck filled with boxes of varying size and unknown mass and an industrial robot with end-effectors that can unload multiple boxes from any reachable location. In this work, we investigate how would the robot with the help of a simulator, learn to maximize the number of boxes unloaded by each action. Most high-fidelity robotic simulators...
Preprint
Full-text available
We present the theoretical analysis and proofs of a recently developed algorithm that allows for optimal planning over long and infinite horizons for achieving multiple independent tasks that are partially observable and evolve over time.
Preprint
Robot manipulation in cluttered scenes often requires contact-rich interactions with objects. It can be more economical to interact via non-prehensile actions, for example, push through other objects to get to the desired grasp pose, instead of deliberate prehensile rearrangement of the scene. For each object in a scene, depending on its properties...
Preprint
Quadrotors can achieve aggressive flight by tracking complex maneuvers and rapidly changing directions. Planning for aggressive flight with trajectory optimization could be incredibly fast, even in higher dimensions, and can account for dynamics of the quadrotor, however, only provides a locally optimal solution. On the other hand, planning with di...
Preprint
Full-text available
In warehouse and manufacturing environments, manipulation platforms are frequently deployed at conveyor belts to perform pick and place tasks. Because objects on the conveyor belts are moving, robots have limited time to pick them up. This brings the requirement for fast and reliable motion planners that could provide provable real-time planning gu...
Chapter
Planning for multi-robot coverage seeks to determine collision-free paths for a fleet of robots, enabling them to collectively observe points of interest in an environment. Persistent coverage is a variant of traditional coverage where coverage levels in the environment decay over time. Thus, robots have to continuously revisit parts of the environ...
Preprint
Full-text available
In many applications, including logistics and manufacturing, robot manipulators operate in semi-structured environments alongside humans or other robots. These environments are largely static, but they may contain some movable obstacles that the robot must avoid. Manipulation tasks in these applications are often highly repetitive, but require fast...
Preprint
Zero-shot execution of unseen robotic tasks is an important problem in robotics. One potential approach is through task planning: combining known skills based on their preconditions and effects to achieve a user-specified goal. In this work, we propose such a task planning approach to build a reactive system for multi-step manipulation tasks that c...
Preprint
Path planning for robotic coverage is the task of determining a collision-free robot trajectory that observes all points of interest in an environment. Robots employed for such tasks are often capable of exercising active control over onboard observational sensors during navigation. In this paper, we tackle the problem of planning robot and sensor...
Preprint
Given access to accurate dynamical models, modern planning approaches are effective in computing feasible and optimal plans for repetitive robotic tasks. However, it is difficult to model the true dynamics of the real world before execution, especially for tasks requiring interactions with objects whose parameters are unknown. A recent planning app...
Preprint
Pose estimation of known objects is fundamental to tasks such as robotic grasping and manipulation. The need for reliable grasping imposes stringent accuracy requirements on pose estimation in cluttered, occluded scenes in dynamic environments. Modern methods employ large sets of training data to learn features in order to find correspondence betwe...
Preprint
Full-text available
Heuristic-based graph search algorithms like A* are frequently used to solve motion planning problems in many domains. For most practical applications, it is infeasible and unnecessary to pre-compute the graph representing the whole search space. Instead, these algorithms generate the graph incrementally by applying a fixed set of actions (frequent...
Preprint
Heuristic search-based planning techniques are commonly used for motion planning on discretized spaces. The performance of these algorithms is heavily affected by the resolution at which the search space is discretized. Typically a fixed resolution is chosen for a given domain. While a finer resolution allows for better maneuverability, it signific...
Preprint
Full-text available
In warehousing and manufacturing environments, manipulation platforms are frequently deployed at conveyor belts to perform pick and place tasks. Because objects on the conveyor belts are moving, robots have limited time to pick them up. This brings the requirement for fast and reliable motion planners that could provide provable real-time planning...
Preprint
Use of physics-based simulation as a planning model enables a planner to reason and generate plans that involve non-trivial interactions with the world. For example, grasping a milk container out of a cluttered refrigerator may involve moving a robot manipulator in between other objects, pushing away the ones that are movable and avoiding interacti...
Preprint
Models used in modern planning problems to simulate outcomes of real world action executions are becoming increasingly complex, ranging from simulators that do physics-based reasoning to precomputed analytical motion primitives. However, robots operating in the real world often face situations not modeled by these models before execution. This impe...
Article
A key challenge in autonomous mobile manipulation is the ability to determine, in real time, how to safely execute complex tasks when placed in unknown or changing world. Addressing this issue for Intervention Autonomous Underwater Vehicles (I‐AUVs), operating in potentially unstructured environment is becoming essential. Our research focuses on us...
Preprint
We consider the task of autonomously unloading boxes from trucks using an industrial manipulator robot. There are multiple challenges that arise: (1) real-time motion planning for a complex robotic system carrying two articulated mechanisms, an arm and a scooper, (2) decision-making in terms of what action to execute next given imperfect informatio...
Preprint
Full-text available
Traditional planning and control methods could fail to find a feasible trajectory for an autonomous vehicle to execute amongst dense traffic on roads. This is because the obstacle-free volume in spacetime is very small in these scenarios for the vehicle to drive through. However, that does not mean the task is infeasible since human drivers are kno...
Preprint
Planning for multi-robot coverage seeks to determine collision-free paths for a fleet of robots, enabling them to collectively observe points of interest in an environment. Persistent coverage is a variant of traditional coverage where coverage-levels in the environment decay over time. Thus, robots have to continuously revisit parts of the environ...
Conference Paper
Full-text available
Weighted A* search (wA*) is a popular tool for robot motion-planning. Its efficiency however depends on the quality of heuristic function used. In fact, it has been shown that the correlation between the heuristic function and the true cost-to-goal significantly affects the efficiency of the search, when used with a large weight on the heuristics....
Preprint
Full-text available
In manufacturing and automation settings, robots often have to perform highly-repetitive manipulation tasks in structured environments. In this work we are interested in settings where tasks are similar, yet not identical (e.g., due to uncertain orientation of objects) and motion planning needs to be extremely fast. Preprocessing-based approaches p...
Conference Paper
Full-text available
We consider the problem of planning a collision-free path for a high-dimensional robot. Specifically, we suggest a planning framework where a motion-planning algorithm can obtain guidance from a user. In contrast to existing approaches that try to speed up planning by incorporating experiences or demonstrations ahead of planning, we suggest to seek...
Article
In this work, we present an approach to planning for humanoid mobility. Humanoid mobility is a challenging problem, as the configuration space for a humanoid robot is intractably large, especially if the robot is capable of performing many types of locomotion. For example, a humanoid robot may be able to perform such tasks as bipedal walking, crawl...
Article
Full-text available
Planning the motion for humanoid robots is a computationally-complex task due to the high dimensionality of the system. Thus, a common approach is to first plan in the low-dimensional space induced by the robot's feet--a task referred to as footstep planning. This low-dimensional plan is then used to guide the full motion of the robot. One approach...
Article
Full-text available
We consider the problem of planning a collision-free path for a high-dimensional robot. Specifically, we suggest a planning framework where a motion-planning algorithm can obtain guidance from a user. In contrast to existing approaches, we suggest to seek user guidance only when the planner identifies that it ceases to make significant progress tow...
Article
Algorithms for fixed-wing unmanned aerial systems (UAS) must integrate on-board sensor capabilities and vehicle maneuver constraints to reliably satisfy the objectives of persistent surveillance, path planning, and trajectory management. In many cases, the characteristic dimensions of sensor fields of view are comparable with the turning radius of...
Research
Full-text available
We are interested in the multiple robot surveillance problem where robots must allocate waypoints to be visited among themselves and plan paths through different waypoints while avoiding obstacles. Furthermore, the robots are allocated specific times to reach their respective goal locations and as a result they have to decide which robot has to vis...