Sachin Chitta

SRI International | SRI

Generalizable long-horizon robotic assembly requires reasoning at multiple levels of abstraction. End-to-end imitation learning (IL) has been proven a promising approach, but it requires a large amount of demonstration data for training and often fails to meet the high-precision requirement of assembly tasks. Reinforcement Learning (RL) approaches...

Automated robotic construction of wood frames faces significant challenges, particularly in the perception of large studs and maintaining tight assembly tolerances amidst the natural variability and dimensional instability of wood. To address these challenges, we introduce a novel multi-modal, multi-stage perception strategy for adaptive robotic co...

Industrial insertion tasks are often performed repetitively with parts that are subject to tight tolerances and prone to breakage. In this paper, we present a safe method to learn a visuo-tactile insertion policy that is robust against grasp pose variations while minimizing human inputs and collision between the robot and the environment. We achiev...

We introduce a robotic assembly system that streamlines the design-to-make workflow for going from a CAD model of a product assembly to a fully programmed and adaptive assembly process. Our system captures (in the CAD tool) the intent of the assembly process for a specific robotic workcell and generates a recipe of task-level instructions. By integ...

In this paper, we develop an online motion planning approach which learns from its planning episodes (experiences) a graph, an Experience Graph. On the theoretical side, we show that planning with Experience graphs is complete and provides bounds on suboptimality with respect to the graph that represents the original planning problem. Experimentall...

We present a new collision detection algorithm to perform contact computations between noisy point cloud data. Our approach takes into account the uncertainty that arises due to discretization error and noise, and formulates collision checking as a two-class classification problem. We use techniques from machine learning to compute the collision pr...

MoveIt! is state of the art software for mobile manipulation, incorporating the latest advances in motion planning, manipulation, 3D perception, kinematics, control and navigation. It provides an easy-to-use platform for developing advanced robotics applications, evaluating new robot designs and building integrated robotics products for industrial,...

Co-robots, i.e. robots that work close to people, will need to account for the preferences and expectations of their human co-workers in executing trajectories or actions. Consistent, legible and predictable trajectories are a key factor in making humans comfortable around robots. In this work, we take a data-driven approach towards designing robot...

Heuristic searches such as A* search are a popular means of finding least-cost plans due to their generality, strong theoretical guarantees on completeness and optimality, simplicity in implementation and consistent behavior. In planning for robotic manipulation, however, these techniques are commonly thought of as impractical due to the high-dimen...

Developing robot agnostic software frameworks involves synthesizing the disparate fields of robotic theory and software engineering while simultaneously accounting for a large variability in hardware designs and control paradigms. As the capabilities of robotic software frameworks increase, the setup difficulty and learning curve for new users also...

Heuristic searches such as the A* search are a popular means of finding least-cost plans due to their generality, strong theoretical guarantees on completeness and optimality, simplicity in implementation and consistent behavior. In planning for robotic manipulation, however, these techniques are commonly thought of as impractical due to the high d...

Robots exhibit flexible behavior largely in proportion to their degree of knowledge about the world. Such knowledge is often meticulously hand-coded for a narrow class of tasks, limiting the scope of possible robot competencies. Thus, the primary limiting factor of robot capabilities is often not the physical attributes of the robot, but the limite...

Papers from a flagship conference reflect the latest developments in the field, including work in such rapidly advancing areas as human-robot interaction and formal methods. Robotics: Science and Systems VIII spans a wide spectrum of robotics, bringing together contributions from researchers working on the mathematical foundations of robotics, robo...

Robots operating in real world environments need to find motion plans quickly. Robot motion should also be efficient and, when operating among people, predictable. Min- imizing a cost function, e.g. path length, can produce short, reasonable paths. Anytime planners are ideal for this since they find an initial solution quickly and then improve solu...

Most prior techniques for proximity computations are designed for synthetic models and assume exact geometric representations. However, real robots construct representations of the environment using their sensors, and the generated representations are more cluttered and less precise than synthetic models. Furthermore, this sensor data is updated at...

Opening and navigating through doors remains a challenging problem, particularly in cluttered environments and for spring-loaded doors. Passing through doors, especially spring-loaded doors, requires making and breaking contacts with the door and preventing the door from closing while passing through. In this work, we present a planning framework t...

Many modern sensors used for mapping produce 3D point clouds, which are typically registered together using the iterative closest point (ICP) algorithm. Because ICP has many variants whose performances depend on the environment and the sensor, hundreds ...

Motion planning in high dimensional state spaces, such as for mobile manipulation, is a challenging problem. Con- strained manipulation, e.g. opening articulated objects like doors or drawers, is also hard since sampling states on the constrained manifold is expensive. Further, planning for such tasks requires a combination of planning in free spac...

We present a novel approach to improve the performance of sample-based motion planners by learning from prior instances. Our formulation stores the results of prior collision and local planning queries. This information is used to acceler-ate the performance of planners based on probabilistic collision checking, select new local paths in free space...

Robots executing practical tasks in real environments are often subject to multiple constraints. These constraints include orientation constraints: e.g., keeping a glass of water upright, torque constraints: e.g., not exceeding the torque limits for an arm lifting heavy objects, visibility constraints: e.g., keeping an object in view while moving a...

Randomized planners, search-based planners, potential-field approaches and trajectory optimization based motion planners are just some of the types of approaches that have been developed for motion planning. Given a motion planning problem, choosing the appropriate algorithm to use is a daunting task even for experts since there has been relatively...

Human environments possess a significant amount of underlying structure that is under-utilized in motion planning and mobile manipulation. In domestic environments for example, walls and shelves are static, large objects such as furniture and kitchen appliances most of the time do not move and do not change, and objects are typically placed on a li...

Unstructured human environments present a substantial challenge to effective robotic operation. Mobile manipulation in human environments requires dealing with novel unknown objects, cluttered workspaces, and noisy sensor data. We present an approach to mobile pick and place in such environments using a combination of two-dimensional (2-D) and thre...

Dual-arm manipulation is an increasingly important skill for robots operating in home, retail and industrial environments. Dual-arm manipulation is especially essential for tasks involving large objects which are harder to grasp and manipulate using a single arm. In this work, we address dual-arm manipulation of objects in indoor environments. We a...

We present a new collision and proximity library that integrates several techniques for fast and accurate collision checking and proximity computation. Our library is based on hierarchical representations and designed to perform multiple proximity queries on different model representations. The set of queries includes discrete collision detection,...

— Collision-free navigation in cluttered environments is essential for any mobile manipulation system. Traditional navigation systems have relied on a 2D grid map projected from a 3D representation for efficiency. This approach, however, prevents navigation close to objects in situations where projected 3D configurations are in collision within the...

We present a novel robotic grasp controller that allows a sensorized parallel jaw gripper to gently pick up and set down unknown objects once a grasp location has been selected. Our approach is inspired by the control scheme that humans employ for such actions, which is known to centrally depend on tactile sensation rather than vision or propriocep...

We present a new collision and proximity library that integrates several techniques for fast and accurate collision checking and proximity computation. Our library is based on hierarchical representations and designed to perform multiple proximity queries on different model representations. The set of queries includes discrete collision detection,...

Tactile information is valuable in determining properties of objects that are inaccessible from visual perception. In this paper, we present a tactile perception strategy that allows a mobile robot with tactile sensors in its gripper to measure a generic set of tactile features while manipulating an object. We propose a switching velocity-force con...

In this paper, we present a search-based motion planning algorithm for manipulation that handles the high dimensionality of the problem and minimizes the limitations associated with employing a strict set of pre-defined actions. Our approach employs a set of adaptive motion primitives comprised of static motions with variable dimensionality and on-...

Learning complex motor skills for real world tasks is a hard problem in robotic manipulation that often requires painstaking manual tuning and design by a human expert. In this work, we present a Reinforcement Learning based approach to acquiring new motor skills from demonstration. Our approach allows the robot to learn fine manipulation skills an...

Robust navigation in cluttered environments has been well addressed for mobile robotic platforms, but the problem of navigating with a moveable object like a cart has not been widely examined. In this work, we present a planning and control approach to navigation of a humanoid robot while pushing a cart. We show how immediate information about the...

We present a new approach to motion planning using a stochastic trajectory optimization framework. The approach relies on generating noisy trajectories to explore the space around an initial (possibly infeasible) trajectory, which are then combined to produced an updated trajectory with lower cost. A cost function based on a combination of obstacle...

We present a new collision detection algorithm to perform contact computa-tions between noisy point cloud data. Our approach takes into account the uncertainty that arises due to discretization error and noise, and formulates collision checking as a two-class classification problem. We use techniques from machine learning to compute the collision p...

Robotic grasping in unstructured environments requires the ability to select grasps for unknown objects and execute them while dealing with uncertainty due to sensor noise or calibration errors. In this work, we propose a simple but robust approach to grasp selection for unknown objects, and a reactive adjustment approach to deal with uncertainty i...

Computing a motion that enables a mobile manipulator to open a door is challenging because it requires tight coordination between the motions of the arm and the base. Hard-coding the motion, on the other hand, is infeasible since doors vary widely in their sizes and types, some doors are opened by pulling and others by pushing, and indoor spaces of...

Heuristic searches such as A* search are highly popular means of finding least-cost plans due to their generality, strong theoretical guarantees on completeness and optimality and simplicity in the implementation. In planning for robotic manipulation however, these techniques are commonly thought of as impractical due to the high-dimensionality of...

We present a novel combination of motion planning techniques to compute motion plans for robotic arms. We compute plans that move the arm as close as possible to the goal region using sampling-based planning and then switch to a trajectory optimization technique for the last few centimeters necessary to reach the goal region. This combination allow...

Tactile information is valuable in determining properties of objects that are inaccessible from visual perception. In this work, we present a tactile perception strategy that allows any mobile robot with tactile sensors in its gripper to measure a set of generic tactile features while grasping an object. We propose a hybrid velocity-force controlle...

We describe an autonomous robotic system capable of navigating through an office environment, opening doors along the way, and plugging itself into electrical outlets to recharge as needed. We demonstrate through extensive experimentation that our robot executes these tasks reliably, without requiring any modification to the environment. We present...

We present a complete software architecture for reliable grasping of household objects. Our work combines aspects such as scene interpretation from 3D range data, grasp planning, motion planning, and grasp failure identification and recovery using tactile sensors. We build upon, and add several new contributions to the significant prior work in the...

This paper presents significant steps towards the online integration of 3D perception and manipulation for personal robotics applications. We propose a modular and distributed architecture, which seamlessly integrates the creation of 3D maps for collision detection and semantic annotations, with a real-time motion replanning framework. To validate...

In this paper, we present a laser-based approach for door and handle identification. The approach builds on a 3D perception pipeline to annotate doors and their handles solely from sensed laser data, without any a priori model learning. In particular, we segment the parts of interest using robust geometric estimators and statistical methods applied...

We present a search-based planning approach for controlling a quadrupedal robot over rough terrain. Given a start and goal position, we consider the problem of generating a complete joint trajectory that will result in the legged robot successfully moving from the start to the goal. We decompose the problem into two main phases: an initial global p...

Reconfigurable modular robots have the ability to use different gaits and configurations to perform various tasks. A rolling gait is the fastest currently implemented gait available for traversal over level ground and shows dramatic improvements in efficiency. In this work, we analyze and implement a sensor-based feedback controller to achieve dyna...

Recognizing useful modular robot configurations composed of hundreds of modules is a significant challenge. Matching a new modular robot configuration to a library of known configurations is essential in identifying and applying control schemes. We present three different algorithms to address the problem of (a) matching and (b) mapping new robot c...

Quadruped walking robots need to handle high obstacles like steps that are often not kinematically reachable. We present a dynamic leap that allows a quadruped robot to put its front legs up onto a high rock or ledge, a motion we have found is critical to being able to locomote over rough terrain. The leaping motion was optimized using a simulated...

We present a novel method for the localization of a legged robot on known terrain using only proprioceptive sensors such as joint encoders and an inertial measurement unit. In contrast to other proprioceptive pose estimation techniques, this method allows for global localization (i.e., localization with large initial uncertainty) without the use of...

It is well known that skilled bicycle riders can balance and propel themselves forward using motions of the handlebar. We present the complete nonlinear dynamics and control of such a pedal-less bicycle with a rider. Propulsion is achieved not by pedaling but by a cyclic motion of the steering axis of the bicycle. It is shown that this kind of actu...

In this paper we present new experimental results for a novel underactuated system called the ROBOTRIKKE. The ROBOT-RIKKE is a three-wheeled system that can be driven by periodic motion of its front steering wheel combined with rocking side-to-side motion of a robotic rider. We present two new generations of the ROBOTRIKKE including a ABS model mad...

The TRIKKE is a three-wheeled, human-powered scooter that can be propelled by a combination of cyclic motion of its handlebar and swaying motion of the rider. This paper addresses the modeling, dynamics and control of the TRIKKE and the development of a robotic platform called the ROBOTRIKKE that is derived from similar principles. The TRIKKE can b...

This thesis addresses the dynamics, gait generation and motion planning of a class of locomotion systems called modular locomotion systems that consist of a central base module with locomotion modules like legs, powered wheels or passive wheeled skate modules attached to ports on the base. These systems, by virtue of their often unconventional mode...

We present the design and gait generation for an experimental ROLLERBLADER. The ROLLERBLADER is a robot with a central platform mounted on omnidirectional casters and two 3 degree-of-freedom legs. A passive rollerblading wheel is attached to the end of each leg. The wheels give rise to nonholonomic constraints acting on the robot. The legs can be p...

We present the design and gait generation for an experimen-tal ROLLERBLADER. The ROLLERBLADER is a robot with a central platform mounted on omnidirectional casters and two 3 degree of freedom legs. A set of passive rollerblading wheels is attached to the end of each leg. The wheels give rise to nonholo-nomic constraints acting on the robot. The leg...

We develop the dynamic model for a planar rollerblader. The robot consists of a rigid platform and two planar, two degree-of-freedom legs with in-line skates at the foot. The dynamic model consists of two unicycles coupled through the rigid body dynamics of the planar platform. We derive the Lagrangian reduction for the rollerblading robot. We show...

We develop the dynamic model for a planar ROLLERBLADER. The robot consists of a rigid platform and two planar, two degree-of-freedom legs with in-line skates at the foot. The dynamic model consists of two unicycles coupled through the rigid body dynamics of the planar platform. We derive the Lagrangian reduction for the ROLLERBLADING robot. We show...

This paper describes the University of Pennsylvania’s RoboCup 2001 Legged League team, called the UPennalizers. This year’s team was very successful in both the main competition, placing third out of sixteen teams, and the RoboCup Technical Challenges, where we placed second. Much of this success can be credited to our being able to build on a stro...

Addresses the issue of developing a motion planning algorithm for a general class of modular mobile robots. A modular mobile robot is essentially a reconfigurable robot system in which locomotive modules such as legs, wheels, propellers, etc. can be attached at various locations on the body. The equations of motion for the robot are developed in te...

This paper describes the University of Pennsylvania's RoboCup 2001 Legged League team, called the UPennalizers. This year's team was very successful in both the main competition, placing third out of sixteen teams, and the RoboCup Technical Challenges, where we placed second. Much of this success can be credited to our being able to build on a stro...

This paper presents several new insights and experimental results on the problem of generating omnidirectional walking gaits for quadrupedal robots. For statically stable gaits, by placing some minor restrictions on how the leg motions are generated, we develop an easily computable classification of the best gait patterns (leg phasings) to be used...

This report focuses on two different aspects of modular robots, the enumeration of distinct configurations of a modular robot and the generation of gaits for hybrid robots with wheels and legs. Given a particular set of modules from which the robot can be formed, a modular robot made up of these modules can attain a number of different configuratio...